Chaos control applied to cardiac rhythms represented by ECG signals

International Nuclear Information System (INIS)

Borem Ferreira, Bianca; Amorim Savi, Marcelo; Souza de Paula, Aline

2014-01-01

The control of irregular or chaotic heartbeats is a key issue in cardiology. In this regard, chaos control techniques represent a good alternative since they suggest treatments different from those traditionally used. This paper deals with the application of the extended time-delayed feedback control method to stabilize pathological chaotic heart rhythms. Electrocardiogram (ECG) signals are employed to represent the cardiovascular behavior. A mathematical model is employed to generate ECG signals using three modified Van der Pol oscillators connected with time delay couplings. This model provides results that qualitatively capture the general behavior of the heart. Controlled ECG signals show the ability of the strategy either to control or to suppress the chaotic heart dynamics generating less-critical behaviors. (paper)

A mixed signal ECG processing platform with an adaptive sampling ADC for portable monitoring applications.

Science.gov (United States)

Kim, Hyejung; Van Hoof, Chris; Yazicioglu, Refet Firat

2011-01-01

This paper describes a mixed-signal ECG processing platform with an 12-bit ADC architecture that can adapt its sampling rate according to the input signals rate of change. This enables the sampling of ECG signals with significantly reduced data rate without loss of information. The presented adaptive sampling scheme reduces the ADC power consumption, enables the processing of ECG signals with lower power consumption, and reduces the power consumption of the radio while streaming the ECG signals. The test results show that running a CWT-based R peak detection algorithm using the adaptively sampled ECG signals consumes only 45.6 μW and it leads to 36% less overall system power consumption.

ECG signal performance de-noising assessment based on threshold tuning of dual-tree wavelet transform.

Science.gov (United States)

El B'charri, Oussama; Latif, Rachid; Elmansouri, Khalifa; Abenaou, Abdenbi; Jenkal, Wissam

2017-02-07

Since the electrocardiogram (ECG) signal has a low frequency and a weak amplitude, it is sensitive to miscellaneous mixed noises, which may reduce the diagnostic accuracy and hinder the physician's correct decision on patients. The dual tree wavelet transform (DT-WT) is one of the most recent enhanced versions of discrete wavelet transform. However, threshold tuning on this method for noise removal from ECG signal has not been investigated yet. In this work, we shall provide a comprehensive study on the impact of the choice of threshold algorithm, threshold value, and the appropriate wavelet decomposition level to evaluate the ECG signal de-noising performance. A set of simulations is performed on both synthetic and real ECG signals to achieve the promised results. First, the synthetic ECG signal is used to observe the algorithm response. The evaluation results of synthetic ECG signal corrupted by various types of noise has showed that the modified unified threshold and wavelet hyperbolic threshold de-noising method is better in realistic and colored noises. The tuned threshold is then used on real ECG signals from the MIT-BIH database. The results has shown that the proposed method achieves higher performance than the ordinary dual tree wavelet transform into all kinds of noise removal from ECG signal. The simulation results indicate that the algorithm is robust for all kinds of noises with varying degrees of input noise, providing a high quality clean signal. Moreover, the algorithm is quite simple and can be used in real time ECG monitoring.

ECG contamination of EEG signals: effect on entropy.

Science.gov (United States)

Chakrabarti, Dhritiman; Bansal, Sonia

2016-02-01

Entropy™ is a proprietary algorithm which uses spectral entropy analysis of electroencephalographic (EEG) signals to produce indices which are used as a measure of depth of hypnosis. We describe a report of electrocardiographic (ECG) contamination of EEG signals leading to fluctuating erroneous Entropy values. An explanation is provided for mechanism behind this observation by describing the spread of ECG signals in head and neck and its influence on EEG/Entropy by correlating the observation with the published Entropy algorithm. While the Entropy algorithm has been well conceived, there are still instances in which it can produce erroneous values. Such erroneous values and their cause may be identified by close scrutiny of the EEG waveform if Entropy values seem out of sync with that expected at given anaesthetic levels.

Noise Suppression in ECG Signals through Efficient One-Step Wavelet Processing Techniques

Directory of Open Access Journals (Sweden)

E. Castillo

2013-01-01

Full Text Available This paper illustrates the application of the discrete wavelet transform (DWT for wandering and noise suppression in electrocardiographic (ECG signals. A novel one-step implementation is presented, which allows improving the overall denoising process. In addition an exhaustive study is carried out, defining threshold limits and thresholding rules for optimal wavelet denoising using this presented technique. The system has been tested using synthetic ECG signals, which allow accurately measuring the effect of the proposed processing. Moreover, results from real abdominal ECG signals acquired from pregnant women are presented in order to validate the presented approach.

Heritability of ECG Biomarkers in the Netherlands Twin Registry Measured from Holter ECGs.

Directory of Open Access Journals (Sweden)

Emily C Hodkinson

2016-04-01

Full Text Available INTRODUCTIONThe resting ECG is the most commonly used tool to assess cardiac electrophysiology. Previous studies have estimated heritability of ECG parameters based on these snapshots of the cardiac electrical activity. In this study we set out to determine whether analysis of heart rate specific data from Holter ECGs allows more complete assessment of the heritability of ECG parameters.METHODS and RESULTSHolter ECGs were recorded from 221 twin pairs and analyzed using a multi-parameter beat binning approach. Heart rate dependent estimates of heritability for QRS duration, QT interval, Tpeak–Tend and Theight were calculated using structural equation modelling. QRS duration is largely determined by environmental factors whereas repolarization is primarily genetically determined. Heritability estimates of both QT interval and Theight were significantly higher when measured from Holter compared to resting ECGs and the heritability estimate of each was heart rate dependent. Analysis of the genetic contribution to correlation between repolarization parameters demonstrated that covariance of individual ECG parameters at different heart rates overlap but at each specific heart rate there was relatively little overlap in the genetic determinants of the different repolarization parameters.CONCLUSIONSHere we present the first study of heritability of repolarization parameters measured from Holter ECGs. Our data demonstrate that higher heritability can be estimated from the Holter than the resting ECG and reveals rate dependence in the genetic – environmental determinants of the ECG that has not previously been tractable. Future applications include deeper dissection of the ECG of participants with inherited cardiac electrical disease.

Efficient ECG Signal Compression Using Adaptive Heart Model

National Research Council Canada - National Science Library

Szilagyi, S

2001-01-01

This paper presents an adaptive, heart-model-based electrocardiography (ECG) compression method. After conventional pre-filtering the waves from the signal are localized and the model's parameters are determined...

On the application of optimal wavelet filter banks for ECG signal classification

International Nuclear Information System (INIS)

Hadjiloucas, S; Jannah, N; Hwang, F; Galvão, R K H

2014-01-01

This paper discusses ECG signal classification after parametrizing the ECG waveforms in the wavelet domain. Signal decomposition using perfect reconstruction quadrature mirror filter banks can provide a very parsimonious representation of ECG signals. In the current work, the filter parameters are adjusted by a numerical optimization algorithm in order to minimize a cost function associated to the filter cut-off sharpness. The goal consists of achieving a better compromise between frequency selectivity and time resolution at each decomposition level than standard orthogonal filter banks such as those of the Daubechies and Coiflet families. Our aim is to optimally decompose the signals in the wavelet domain so that they can be subsequently used as inputs for training to a neural network classifier

High Resolution of the ECG Signal by Polynomial Approximation

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G. Rozinaj

2006-04-01

Full Text Available Averaging techniques as temporal averaging and space averaging have been successfully used in many applications for attenuating interference [6], [7], [8], [9], [10]. In this paper we introduce interference removing of the ECG signal by polynomial approximation, with smoothing discrete dependencies, to make up for averaging methods. The method is suitable for low-level signals of the electrical activity of the heart often less than 10 m V. Most low-level signals arising from PR, ST and TP segments which can be detected eventually and their physiologic meaning can be appreciated. Of special importance for the diagnostic of the electrical activity of the heart is the activity bundle of His between P and R waveforms. We have established an artificial sine wave to ECG signal between P and R wave. The aim focus is to verify the smoothing method by polynomial approximation if the SNR (signal-to-noise ratio is negative (i.e. a signal is lower than noise.

Self-organized neural network for the quality control of 12-lead ECG signals

International Nuclear Information System (INIS)

Chen, Yun; Yang, Hui

2012-01-01

Telemedicine is very important for the timely delivery of health care to cardiovascular patients, especially those who live in the rural areas of developing countries. However, there are a number of uncertainty factors inherent to the mobile-phone-based recording of electrocardiogram (ECG) signals such as personnel with minimal training and other extraneous noises. PhysioNet organized a challenge in 2011 to develop efficient algorithms that can assess the ECG signal quality in telemedicine settings. This paper presents our efforts in this challenge to integrate multiscale recurrence analysis with a self-organizing map for controlling the ECG signal quality. As opposed to directly evaluating the 12-lead ECG, we utilize an information-preserving transform, i.e. Dower transform, to derive the 3-lead vectorcardiogram (VCG) from the 12-lead ECG in the first place. Secondly, we delineate the nonlinear and nonstationary characteristics underlying the 3-lead VCG signals into multiple time-frequency scales. Furthermore, a self-organizing map is trained, in both supervised and unsupervised ways, to identify the correlations between signal quality and multiscale recurrence features. The efficacy and robustness of this approach are validated using real-world ECG recordings available from PhysioNet. The average performance was demonstrated to be 95.25% for the training dataset and 90.0% for the independent test dataset with unknown labels. (paper)

Fusion of ECG and ABP signals based on wavelet transform for cardiac arrhythmias classification.

Science.gov (United States)

Arvanaghi, Roghayyeh; Daneshvar, Sabalan; Seyedarabi, Hadi; Goshvarpour, Atefeh

2017-11-01

Each of Electrocardiogram (ECG) and Atrial Blood Pressure (ABP) signals contain information of cardiac status. This information can be used for diagnosis and monitoring of diseases. The majority of previously proposed methods rely only on ECG signal to classify heart rhythms. In this paper, ECG and ABP were used to classify five different types of heart rhythms. To this end, two mentioned signals (ECG and ABP) have been fused. These physiological signals have been used from MINIC physioNet database. ECG and ABP signals have been fused together on the basis of the proposed Discrete Wavelet Transformation fusion technique. Then, some frequency features were extracted from the fused signal. To classify the different types of cardiac arrhythmias, these features were given to a multi-layer perceptron neural network. In this study, the best results for the proposed fusion algorithm were obtained. In this case, the accuracy rates of 96.6%, 96.9%, 95.6% and 93.9% were achieved for two, three, four and five classes, respectively. However, the maximum classification rate of 89% was obtained for two classes on the basis of ECG features. It has been found that the higher accuracy rates were acquired by using the proposed fusion technique. The results confirmed the importance of fusing features from different physiological signals to gain more accurate assessments. Copyright © 2017 Elsevier B.V. All rights reserved.

Conditional Random Fields for Morphological Analysis of Wireless ECG Signals

Science.gov (United States)

Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

2015-01-01

Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel approach to the problem of extracting the morphological structure of ECG signals based on the use of dynamically structured conditional random field (CRF) models. We apply this framework to the problem of extracting morphological structure from wireless ECG sensor data collected in a lab-based study of habituated cocaine users. Our results show that the proposed CRF-based approach significantly out-performs independent prediction models using the same features, as well as a widely cited open source toolkit. PMID:26726321

ECG authentication in post-exercise situation.

Science.gov (United States)

Dongsuk Sung; Jeehoon Kim; Myungjun Koh; Kwangsuk Park

2017-07-01

Human authentication based on electrocardiogram (ECG) has been a remarkable issue for recent ten years. This paper proposed an authentication technology with the ECG data recorded after the harsh exercise. 55 subjects voluntarily attended to this experiment. A stepper was used as an exercise equipment. The subjects are asked to do stepper for 5 minutes and their ECG signals are acquired before and after the exercise in rest, sitting posture. Linear discriminant analysis (LDA) was used for both feature extraction and classification. Even though, within the first 1 minute recording, the subject recognition accuracy was 59.64%, which is too low to utilize, after one minute the accuracy was higher than 90% and it increased up to 96.22% within 5 minutes, which is plausible to use in authentication circumstances. Therefore, we have concluded that ECG authentication techniques will be able to be used after 1 minute of catching breath.

A configurable and low-power mixed signal SoC for portable ECG monitoring applications.

Science.gov (United States)

Kim, Hyejung; Kim, Sunyoung; Van Helleputte, Nick; Artes, Antonio; Konijnenburg, Mario; Huisken, Jos; Van Hoof, Chris; Yazicioglu, Refet Firat

2014-04-01

This paper describes a mixed-signal ECG System-on-Chip (SoC) that is capable of implementing configurable functionality with low-power consumption for portable ECG monitoring applications. A low-voltage and high performance analog front-end extracts 3-channel ECG signals and single channel electrode-tissue-impedance (ETI) measurement with high signal quality. This can be used to evaluate the quality of the ECG measurement and to filter motion artifacts. A custom digital signal processor consisting of 4-way SIMD processor provides the configurability and advanced functionality like motion artifact removal and R peak detection. A built-in 12-bit analog-to-digital converter (ADC) is capable of adaptive sampling achieving a compression ratio of up to 7, and loop buffer integration reduces the power consumption for on-chip memory access. The SoC is implemented in 0.18 μm CMOS process and consumes 32 μ W from a 1.2 V while heart beat detection application is running, and integrated in a wireless ECG monitoring system with Bluetooth protocol. Thanks to the ECG SoC, the overall system power consumption can be reduced significantly.

Automatic detection of slow-wave sleep and REM-sleep stages using polysomnographic ECG signals

International Nuclear Information System (INIS)

Khemiri, S.; Aloui, K.; Naceur, M. S.

2011-01-01

We describe in this paper a new approach of classifying the different sleep stages only by focusing on the polysomnographic ECG signals. We show the pre-processing technique of the ECG signals. At the same time the identifcation and elimination of the different types of artifacts which contain the signal and its reconstruction are shown. The automatic classification of the slow-deep sleep and the rapid eye movement sleep called in this work REM-sleep consists in extracting physiological indicators that characterize these two sleep stages through the polysomnographic ECG signal. In other words, this classification is based on the analysis of the cardiac rhythm during a night's sleep.

Intelligent classification of electrocardiogram (ECG) signal using extended Kalman Filter (EKF) based neuro fuzzy system.

Science.gov (United States)

Meau, Yeong Pong; Ibrahim, Fatimah; Narainasamy, Selvanathan A L; Omar, Razali

2006-05-01

This study presents the development of a hybrid system consisting of an ensemble of Extended Kalman Filter (EKF) based Multi Layer Perceptron Network (MLPN) and a one-pass learning Fuzzy Inference System using Look-up Table Scheme for the recognition of electrocardiogram (ECG) signals. This system can distinguish various types of abnormal ECG signals such as Ventricular Premature Cycle (VPC), T wave inversion (TINV), ST segment depression (STDP), and Supraventricular Tachycardia (SVT) from normal sinus rhythm (NSR) ECG signal.

ECG De-noising

DEFF Research Database (Denmark)

Kærgaard, Kevin; Jensen, Søren Hjøllund; Puthusserypady, Sadasivan

2015-01-01

Electrocardiogram (ECG) is a widely used noninvasive method to study the rhythmic activity of the heart and thereby to detect the abnormalities. However, these signals are often obscured by artifacts from various sources and minimization of these artifacts are of paramount important. This paper...... proposes two adaptive techniques, namely the EEMD-BLMS (Ensemble Empirical Mode Decomposition in conjunction with the Block Least Mean Square algorithm) and DWT-NN (Discrete Wavelet Transform followed by Neural Network) methods in minimizing the artifacts from recorded ECG signals, and compares...... their performance. These methods were first compared on two types of simulated noise corrupted ECG signals: Type-I (desired ECG+noise frequencies outside the ECG frequency band) and Type-II (ECG+noise frequencies both inside and outside the ECG frequency band). Subsequently, they were tested on real ECG recordings...

Wavelet-Based Watermarking and Compression for ECG Signals with Verification Evaluation

Directory of Open Access Journals (Sweden)

Kuo-Kun Tseng

2014-02-01

Full Text Available In the current open society and with the growth of human rights, people are more and more concerned about the privacy of their information and other important data. This study makes use of electrocardiography (ECG data in order to protect individual information. An ECG signal can not only be used to analyze disease, but also to provide crucial biometric information for identification and authentication. In this study, we propose a new idea of integrating electrocardiogram watermarking and compression approach, which has never been researched before. ECG watermarking can ensure the confidentiality and reliability of a user’s data while reducing the amount of data. In the evaluation, we apply the embedding capacity, bit error rate (BER, signal-to-noise ratio (SNR, compression ratio (CR, and compressed-signal to noise ratio (CNR methods to assess the proposed algorithm. After comprehensive evaluation the final results show that our algorithm is robust and feasible.

One-Dimensional Signal Extraction Of Paper-Written ECG Image And Its Archiving

Science.gov (United States)

Zhang, Zhi-ni; Zhang, Hong; Zhuang, Tian-ge

1987-10-01

A method for converting paper-written electrocardiograms to one dimensional (1-D) signals for archival storage on floppy disk is presented here. Appropriate image processing techniques were employed to remove the back-ground noise inherent to ECG recorder charts and to reconstruct the ECG waveform. The entire process consists of (1) digitization of paper-written ECGs with an image processing system via a TV camera; (2) image preprocessing, including histogram filtering and binary image generation; (3) ECG feature extraction and ECG wave tracing, and (4) transmission of the processed ECG data to IBM-PC compatible floppy disks for storage and retrieval. The algorithms employed here may also be used in the recognition of paper-written EEG or EMG and may be useful in robotic vision.

Adaptive Fourier decomposition based R-peak detection for noisy ECG Signals.

Science.gov (United States)

Ze Wang; Chi Man Wong; Feng Wan

2017-07-01

An adaptive Fourier decomposition (AFD) based R-peak detection method is proposed for noisy ECG signals. Although lots of QRS detection methods have been proposed in literature, most detection methods require high signal quality. The proposed method extracts the R waves from the energy domain using the AFD and determines the R-peak locations based on the key decomposition parameters, achieving the denoising and the R-peak detection at the same time. Validated by clinical ECG signals in the MIT-BIH Arrhythmia Database, the proposed method shows better performance than the Pan-Tompkin (PT) algorithm in both situations of a native PT and the PT with a denoising process.

Analysis Spectrum of ECG Signal and QRS Detection during Running on Treadmill

Science.gov (United States)

Agung Suhendra, M.; Ilham R., M.; Simbolon, Artha I.; Faizal A., M.; Munandar, A.

2018-03-01

The heart is an important organ in our metabolism in which it controls circulatory and oxygen. The heart exercise is needed one of them using the treadmill to prevent health. To analysis, it using electrocardiograph (ECG) to investigating and diagnosing anomalies of the heart. In this paper, we would like to analysis ECG signals during running on the treadmill with kinds of speeds. There are two analysis ECG signals i.e. QRS detection and power spectrum density (PSD). The result of PSD showed that subject 3 has highly for all subject and the result of QRS detection using pan Tomkins algorithm that a percentage of failed detection is an approaching to 0 % for all subject.

Textile Concentric Ring Electrodes for ECG Recording Based on Screen-Printing Technology

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José Vicente Lidón-Roger

2018-01-01

Full Text Available Among many of the electrode designs used in electrocardiography (ECG, concentric ring electrodes (CREs are one of the most promising due to their enhanced spatial resolution. Their development has undergone a great push due to their use in recent years; however, they are not yet widely used in clinical practice. CRE implementation in textiles will lead to a low cost, flexible, comfortable, and robust electrode capable of detecting high spatial resolution ECG signals. A textile CRE set has been designed and developed using screen-printing technology. This is a mature technology in the textile industry and, therefore, does not require heavy investments. Inks employed as conductive elements have been silver and a conducting polymer (poly (3,4-ethylenedioxythiophene polystyrene sulfonate; PEDOT:PSS. Conducting polymers have biocompatibility advantages, they can be used with flexible substrates, and they are available for several printing technologies. CREs implemented with both inks have been compared by analyzing their electric features and their performance in detecting ECG signals. The results reveal that silver CREs present a higher average thickness and slightly lower skin-electrode impedance than PEDOT:PSS CREs. As for ECG recordings with subjects at rest, both CREs allowed the uptake of bipolar concentric ECG signals (BC-ECG with signal-to-noise ratios similar to that of conventional ECG recordings. Regarding the saturation and alterations of ECGs captured with textile CREs caused by intentional subject movements, silver CREs presented a more stable response (fewer saturations and alterations than those of PEDOT:PSS. Moreover, BC-ECG signals provided higher spatial resolution compared to conventional ECG. This improved spatial resolution was manifested in the identification of P1 and P2 waves of atrial activity in most of the BC-ECG signals. It can be concluded that textile silver CREs are more suitable than those of PEDOT:PSS for obtaining

Textile Concentric Ring Electrodes for ECG Recording Based on Screen-Printing Technology.

Science.gov (United States)

Lidón-Roger, José Vicente; Prats-Boluda, Gema; Ye-Lin, Yiyao; Garcia-Casado, Javier; Garcia-Breijo, Eduardo

2018-01-21

Among many of the electrode designs used in electrocardiography (ECG), concentric ring electrodes (CREs) are one of the most promising due to their enhanced spatial resolution. Their development has undergone a great push due to their use in recent years; however, they are not yet widely used in clinical practice. CRE implementation in textiles will lead to a low cost, flexible, comfortable, and robust electrode capable of detecting high spatial resolution ECG signals. A textile CRE set has been designed and developed using screen-printing technology. This is a mature technology in the textile industry and, therefore, does not require heavy investments. Inks employed as conductive elements have been silver and a conducting polymer (poly (3,4-ethylenedioxythiophene) polystyrene sulfonate; PEDOT:PSS). Conducting polymers have biocompatibility advantages, they can be used with flexible substrates, and they are available for several printing technologies. CREs implemented with both inks have been compared by analyzing their electric features and their performance in detecting ECG signals. The results reveal that silver CREs present a higher average thickness and slightly lower skin-electrode impedance than PEDOT:PSS CREs. As for ECG recordings with subjects at rest, both CREs allowed the uptake of bipolar concentric ECG signals (BC-ECG) with signal-to-noise ratios similar to that of conventional ECG recordings. Regarding the saturation and alterations of ECGs captured with textile CREs caused by intentional subject movements, silver CREs presented a more stable response (fewer saturations and alterations) than those of PEDOT:PSS. Moreover, BC-ECG signals provided higher spatial resolution compared to conventional ECG. This improved spatial resolution was manifested in the identification of P1 and P2 waves of atrial activity in most of the BC-ECG signals. It can be concluded that textile silver CREs are more suitable than those of PEDOT:PSS for obtaining BC-ECG records

Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals.

Science.gov (United States)

Elhaj, Fatin A; Salim, Naomie; Harris, Arief R; Swee, Tan Tian; Ahmed, Taqwa

2016-04-01

Arrhythmia is a cardiac condition caused by abnormal electrical activity of the heart, and an electrocardiogram (ECG) is the non-invasive method used to detect arrhythmias or heart abnormalities. Due to the presence of noise, the non-stationary nature of the ECG signal (i.e. the changing morphology of the ECG signal with respect to time) and the irregularity of the heartbeat, physicians face difficulties in the diagnosis of arrhythmias. The computer-aided analysis of ECG results assists physicians to detect cardiovascular diseases. The development of many existing arrhythmia systems has depended on the findings from linear experiments on ECG data which achieve high performance on noise-free data. However, nonlinear experiments characterize the ECG signal more effectively sense, extract hidden information in the ECG signal, and achieve good performance under noisy conditions. This paper investigates the representation ability of linear and nonlinear features and proposes a combination of such features in order to improve the classification of ECG data. In this study, five types of beat classes of arrhythmia as recommended by the Association for Advancement of Medical Instrumentation are analyzed: non-ectopic beats (N), supra-ventricular ectopic beats (S), ventricular ectopic beats (V), fusion beats (F) and unclassifiable and paced beats (U). The characterization ability of nonlinear features such as high order statistics and cumulants and nonlinear feature reduction methods such as independent component analysis are combined with linear features, namely, the principal component analysis of discrete wavelet transform coefficients. The features are tested for their ability to differentiate different classes of data using different classifiers, namely, the support vector machine and neural network methods with tenfold cross-validation. Our proposed method is able to classify the N, S, V, F and U arrhythmia classes with high accuracy (98.91%) using a combined support

Fault Tolerant Neural Network for ECG Signal Classification Systems

Directory of Open Access Journals (Sweden)

MERAH, M.

2011-08-01

Full Text Available The aim of this paper is to apply a new robust hardware Artificial Neural Network (ANN for ECG classification systems. This ANN includes a penalization criterion which makes the performances in terms of robustness. Specifically, in this method, the ANN weights are normalized using the auto-prune method. Simulations performed on the MIT ? BIH ECG signals, have shown that significant robustness improvements are obtained regarding potential hardware artificial neuron failures. Moreover, we show that the proposed design achieves better generalization performances, compared to the standard back-propagation algorithm.

Extracting the respiration cycle lengths from ECG signal recorded with bed sheet electrodes

International Nuclear Information System (INIS)

Vehkaoja, A; Peltokangas, M; Lekkala, J

2013-01-01

A method for recognizing the respiration cycle lengths from the electrocardiographic (ECG) signal recorded with textile electrodes that are attached to a bed sheet is proposed. The method uses two features extracted from the ECG that are affected by the respiration: respiratory sinus arrhythmia and the amplitude of the R-peaks. The proposed method was tested in one hour long recordings with ten healthy young adults. A relative mean absolute error of 5.6 % was achieved when the algorithm was able to provide a result for approximately 40 % of the time. 90 % of the values were within 0.5 s and 97 % within 1 s from the reference respiration value. In addition to the instantaneous respiration cycle lengths, also the mean values during 1 and 5 minutes epochs are calculated. The effect of the ECG signal source is evaluated by calculating the result also from the simultaneously recorded reference ECG signal. The acquired respiration information can be used in the estimation of sleep quality and the detection of sleep disorders

Design and implementation of a multiband digital filter using FPGA to extract the ECG signal in the presence of different interference signals.

Science.gov (United States)

Aboutabikh, Kamal; Aboukerdah, Nader

2015-07-01

In this paper, we propose a practical way to synthesize and filter an ECG signal in the presence of four types of interference signals: (1) those arising from power networks with a fundamental frequency of 50Hz, (2) those arising from respiration, having a frequency range from 0.05 to 0.5Hz, (3) muscle signals with a frequency of 25Hz, and (4) white noise present within the ECG signal band. This was done by implementing a multiband digital filter (seven bands) of type FIR Multiband Least Squares using a digital programmable device (Cyclone II EP2C70F896C6 FPGA, Altera), which was placed on an education and development board (DE2-70, Terasic). This filter was designed using the VHDL language in the Quartus II 9.1 design environment. The proposed method depends on Direct Digital Frequency Synthesizers (DDFS) designed to synthesize the ECG signal and various interference signals. So that the synthetic ECG specifications would be closer to actual ECG signals after filtering, we designed in a single multiband digital filter instead of using three separate digital filters LPF, HPF, BSF. Thus all interference signals were removed with a single digital filter. The multiband digital filter results were studied using a digital oscilloscope to characterize input and output signals in the presence of differing sinusoidal interference signals and white noise. Copyright © 2015 Elsevier Ltd. All rights reserved.

On the Design of an Efficient Cardiac Health Monitoring System Through Combined Analysis of ECG and SCG Signals.

Science.gov (United States)

Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Lin, Wen-Yen; Chang, Po-Cheng; Lee, Ming-Yih

2018-01-28

Cardiovascular disease (CVD) is a major public concern and socioeconomic problem across the globe. The popular high-end cardiac health monitoring systems such as magnetic resonance imaging (MRI), computerized tomography scan (CT scan), and echocardiography (Echo) are highly expensive and do not support long-term continuous monitoring of patients without disrupting their activities of daily living (ADL). In this paper, the continuous and non-invasive cardiac health monitoring using unobtrusive sensors is explored aiming to provide a feasible and low-cost alternative to foresee possible cardiac anomalies in an early stage. It is learned that cardiac health monitoring based on sole usage of electrocardiogram (ECG) signals may not provide powerful insights as ECG provides shallow information on various cardiac activities in the form of electrical impulses only. Hence, a novel low-cost, non-invasive seismocardiogram (SCG) signal along with ECG signals are jointly investigated for the robust cardiac health monitoring. For this purpose, the in-laboratory data collection model is designed for simultaneous acquisition of ECG and SCG signals followed by mechanisms for the automatic delineation of relevant feature points in acquired ECG and SCG signals. In addition, separate feature points based novel approach is adopted to distinguish between normal and abnormal morphology in each ECG and SCG cardiac cycle. Finally, a combined analysis of ECG and SCG is carried out by designing a Naïve Bayes conditional probability model. Experiments on Institutional Review Board (IRB) approved licensed ECG/SCG signals acquired from real subjects containing 12,000 cardiac cycles show that the proposed feature point delineation mechanisms and abnormal morphology detection methods consistently perform well and give promising results. In addition, experimental results show that the combined analysis of ECG and SCG signals provide more reliable cardiac health monitoring compared to the

On the Design of an Efficient Cardiac Health Monitoring System Through Combined Analysis of ECG and SCG Signals

Directory of Open Access Journals (Sweden)

Prasan Kumar Sahoo

2018-01-01

Full Text Available Cardiovascular disease (CVD is a major public concern and socioeconomic problem across the globe. The popular high-end cardiac health monitoring systems such as magnetic resonance imaging (MRI, computerized tomography scan (CT scan, and echocardiography (Echo are highly expensive and do not support long-term continuous monitoring of patients without disrupting their activities of daily living (ADL. In this paper, the continuous and non-invasive cardiac health monitoring using unobtrusive sensors is explored aiming to provide a feasible and low-cost alternative to foresee possible cardiac anomalies in an early stage. It is learned that cardiac health monitoring based on sole usage of electrocardiogram (ECG signals may not provide powerful insights as ECG provides shallow information on various cardiac activities in the form of electrical impulses only. Hence, a novel low-cost, non-invasive seismocardiogram (SCG signal along with ECG signals are jointly investigated for the robust cardiac health monitoring. For this purpose, the in-laboratory data collection model is designed for simultaneous acquisition of ECG and SCG signals followed by mechanisms for the automatic delineation of relevant feature points in acquired ECG and SCG signals. In addition, separate feature points based novel approach is adopted to distinguish between normal and abnormal morphology in each ECG and SCG cardiac cycle. Finally, a combined analysis of ECG and SCG is carried out by designing a Naïve Bayes conditional probability model. Experiments on Institutional Review Board (IRB approved licensed ECG/SCG signals acquired from real subjects containing 12,000 cardiac cycles show that the proposed feature point delineation mechanisms and abnormal morphology detection methods consistently perform well and give promising results. In addition, experimental results show that the combined analysis of ECG and SCG signals provide more reliable cardiac health monitoring compared to

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

Science.gov (United States)

Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

2017-02-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

Cancelable ECG biometrics using GLRT and performance improvement using guided filter with irreversible guide signal.

Science.gov (United States)

Kim, Hanvit; Minh Phuong Nguyen; Se Young Chun

2017-07-01

Biometrics such as ECG provides a convenient and powerful security tool to verify or identify an individual. However, one important drawback of biometrics is that it is irrevocable. In other words, biometrics cannot be re-used practically once it is compromised. Cancelable biometrics has been investigated to overcome this drawback. In this paper, we propose a cancelable ECG biometrics by deriving a generalized likelihood ratio test (GLRT) detector from a composite hypothesis testing in randomly projected domain. Since it is common to observe performance degradation for cancelable biometrics, we also propose a guided filtering (GF) with irreversible guide signal that is a non-invertibly transformed signal of ECG authentication template. We evaluated our proposed method using ECG-ID database with 89 subjects. Conventional Euclidean detector with original ECG template yielded 93.9% PD1 (detection probability at 1% FAR) while Euclidean detector with 10% compressed ECG (1/10 of the original data size) yielded 90.8% PD1. Our proposed GLRT detector with 10% compressed ECG yielded 91.4%, which is better than Euclidean with the same compressed ECG. GF with our proposed irreversible ECG template further improved the performance of our GLRT with 10% compressed ECG up to 94.3%, which is higher than Euclidean detector with original ECG. Lastly, we showed that our proposed cancelable ECG biometrics practically met cancelable biometrics criteria such as efficiency, re-usability, diversity and non-invertibility.

Multi-purpose ECG telemetry system.

Science.gov (United States)

Marouf, Mohamed; Vukomanovic, Goran; Saranovac, Lazar; Bozic, Miroslav

2017-06-19

The Electrocardiogram ECG is one of the most important non-invasive tools for cardiac diseases diagnosis. Taking advantage of the developed telecommunication infrastructure, several approaches that address the development of telemetry cardiac devices were introduced recently. Telemetry ECG devices allow easy and fast ECG monitoring of patients with suspected cardiac issues. Choosing the right device with the desired working mode, signal quality, and the device cost are still the main obstacles to massive usage of these devices. In this paper, we introduce design, implementation, and validation of a multi-purpose telemetry system for recording, transmission, and interpretation of ECG signals in different recording modes. The system consists of an ECG device, a cloud-based analysis pipeline, and accompanied mobile applications for physicians and patients. The proposed ECG device's mechanical design allows laypersons to easily record post-event short-term ECG signals, using dry electrodes without any preparation. Moreover, patients can use the device to record long-term signals in loop and holter modes, using wet electrodes. In order to overcome the problem of signal quality fluctuation due to using different electrodes types and different placements on subject's chest, customized ECG signal processing and interpretation pipeline is presented for each working mode. We present the evaluation of the novel short-term recorder design. Recording of an ECG signal was performed for 391 patients using a standard 12-leads golden standard ECG and the proposed patient-activated short-term post-event recorder. In the validation phase, a sample of validation signals followed peer review process wherein two experts annotated the signals in terms of signal acceptability for diagnosis.We found that 96% of signals allow detecting arrhythmia and other signal's abnormal changes. Additionally, we compared and presented the correlation coefficient and the automatic QRS delineation results

Classification of a Driver's cognitive workload levels using artificial neural network on ECG signals.

Science.gov (United States)

Tjolleng, Amir; Jung, Kihyo; Hong, Wongi; Lee, Wonsup; Lee, Baekhee; You, Heecheon; Son, Joonwoo; Park, Seikwon

2017-03-01

An artificial neural network (ANN) model was developed in the present study to classify the level of a driver's cognitive workload based on electrocardiography (ECG). ECG signals were measured on 15 male participants while they performed a simulated driving task as a primary task with/without an N-back task as a secondary task. Three time-domain ECG measures (mean inter-beat interval (IBI), standard deviation of IBIs, and root mean squared difference of adjacent IBIs) and three frequencydomain ECG measures (power in low frequency, power in high frequency, and ratio of power in low and high frequencies) were calculated. To compensate for individual differences in heart response during the driving tasks, a three-step data processing procedure was performed to ECG signals of each participant: (1) selection of two most sensitive ECG measures, (2) definition of three (low, medium, and high) cognitive workload levels, and (3) normalization of the selected ECG measures. An ANN model was constructed using a feed-forward network and scaled conjugate gradient as a back-propagation learning rule. The accuracy of the ANN classification model was found satisfactory for learning data (95%) and testing data (82%). Copyright © 2016 Elsevier Ltd. All rights reserved.

FPGA-based electrocardiography (ECG signal analysis system using least-square linear phase finite impulse response (FIR filter

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Mohamed G. Egila

2016-12-01

Full Text Available This paper presents a proposed design for analyzing electrocardiography (ECG signals. This methodology employs highpass least-square linear phase Finite Impulse Response (FIR filtering technique to filter out the baseline wander noise embedded in the input ECG signal to the system. Discrete Wavelet Transform (DWT was utilized as a feature extraction methodology to extract the reduced feature set from the input ECG signal. The design uses back propagation neural network classifier to classify the input ECG signal. The system is implemented on Xilinx 3AN-XC3S700AN Field Programming Gate Array (FPGA board. A system simulation has been done. The design is compared with some other designs achieving total accuracy of 97.8%, and achieving reduction in utilizing resources on FPGA implementation.

The event synchronous canceller algorithm removes maternal ECG from abdominal signals without affecting the fetal ECG

NARCIS (Netherlands)

Ungureanu, G.M.; Bergmans, J.W.M.; Oei, S.G.; Ungureanu, A.; Wolf, W.

2009-01-01

Fetal monitoring using abdominally recorded signals (ADS) allows physicians to detect occurring changes in the well-being state of the fetus from the beginning of pregnancy. Mainly based on the fetal electrocardiogram (fECG), it provides the long-term fetal heart rate (fHR) and assessment of the

Fetal ECG Extraction from Abdominal Signals: A Review on Suppression of Fundamental Power Line Interference Component and Its Harmonics

OpenAIRE

Ţarălungă, Dragoş-Daniel; Ungureanu, Georgeta-Mihaela; Gussi, Ilinca; Strungaru, Rodica; Wolf, Werner

2014-01-01

Interference of power line (PLI) (fundamental frequency and its harmonics) is usually present in biopotential measurements. Despite all countermeasures, the PLI still corrupts physiological signals, for example, electromyograms (EMG), electroencephalograms (EEG), and electrocardiograms (ECG). When analyzing the fetal ECG (fECG) recorded on the maternal abdomen, the PLI represents a particular strong noise component, being sometimes 10 times greater than the fECG signal, and thus impairing the...

Sequential Total Variation Denoising for the Extraction of Fetal ECG from Single-Channel Maternal Abdominal ECG.

Science.gov (United States)

Lee, Kwang Jin; Lee, Boreom

2016-07-01

Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR.

Conditional Random Fields for Morphological Analysis of Wireless ECG Signals

OpenAIRE

Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

2014-01-01

Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel app...

Adaptive EMG noise reduction in ECG signals using noise level approximation

Science.gov (United States)

Marouf, Mohamed; Saranovac, Lazar

2017-12-01

In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.

Fetal ECG Extraction from Abdominal Signals: A Review on Suppression of Fundamental Power Line Interference Component and Its Harmonics

Directory of Open Access Journals (Sweden)

Dragoş-Daniel Ţarălungă

2014-01-01

Full Text Available Interference of power line (PLI (fundamental frequency and its harmonics is usually present in biopotential measurements. Despite all countermeasures, the PLI still corrupts physiological signals, for example, electromyograms (EMG, electroencephalograms (EEG, and electrocardiograms (ECG. When analyzing the fetal ECG (fECG recorded on the maternal abdomen, the PLI represents a particular strong noise component, being sometimes 10 times greater than the fECG signal, and thus impairing the extraction of any useful information regarding the fetal health state. Many signal processing methods for cancelling the PLI from biopotentials are available in the literature. In this review study, six different principles are analyzed and discussed, and their performance is evaluated on simulated data (three different scenarios, based on five quantitative performance indices.

Fetal ECG extraction from abdominal signals: a review on suppression of fundamental power line interference component and its harmonics.

Science.gov (United States)

Ţarălungă, Dragoş-Daniel; Ungureanu, Georgeta-Mihaela; Gussi, Ilinca; Strungaru, Rodica; Wolf, Werner

2014-01-01

Interference of power line (PLI) (fundamental frequency and its harmonics) is usually present in biopotential measurements. Despite all countermeasures, the PLI still corrupts physiological signals, for example, electromyograms (EMG), electroencephalograms (EEG), and electrocardiograms (ECG). When analyzing the fetal ECG (fECG) recorded on the maternal abdomen, the PLI represents a particular strong noise component, being sometimes 10 times greater than the fECG signal, and thus impairing the extraction of any useful information regarding the fetal health state. Many signal processing methods for cancelling the PLI from biopotentials are available in the literature. In this review study, six different principles are analyzed and discussed, and their performance is evaluated on simulated data (three different scenarios), based on five quantitative performance indices.

A GI Proposal to Display ECG Digital Signals Wirelessly Real-time Transmitted onto a Remote PC

Directory of Open Access Journals (Sweden)

Marius Corneliu Rosu

2018-03-01

Full Text Available The sensors, as wireless communication system, comply the 7-layer model Open Systems Interconnection (OSI. In this paper, a point-to-point transmission model was used. The ECG signal is transmitted from the Router Sensor (RS to an end Coordinator Node (CN plugged-in to the laptop via USB port; RS acquires ECG signal in analogical mode, and is also responsible with sampling, quantization and sending it wirelessly direct to CN. The distance between RS and CN is a single-hop transmission, and does not exceed the range of the XBeeS2Pro transceivers. The communication protocol is ZigBee. Remote viewing of the transmitted signal is performed on a Graphical Interface (GI written under MATLAB, after the signal has been digitized; the choice of MATLAB was motivated by future developments. Particular aspects will be highlighted, so that the reader to be edified about the results obtained during laboratory experiments. Recording demonstrate that the purpose exposed in title has been reached: Direct link in Real-Time was established, and the digital ECG signal received is reconstituted accurately on MATLAB GI; signal received on laptop is compared with the analog signal displayed on oscilloscope.

Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains

Directory of Open Access Journals (Sweden)

L.C.M. Vanderlei

2008-10-01

Full Text Available The aim of the present study was to compare heart rate variability (HRV at rest and during exercise using a temporal series obtained with the Polar S810i monitor and a signal from a LYNX® signal conditioner (BIO EMG 1000 model with a channel configured for the acquisition of ECG signals. Fifteen healthy subjects aged 20.9 ± 1.4 years were analyzed. The subjects remained at rest for 20 min and performed exercise for another 20 min with the workload selected to achieve 60% of submaximal heart rate. RR series were obtained for each individual with a Polar S810i instrument and with an ECG analyzed with a biological signal conditioner. The HRV indices (rMSSD, pNN50, LFnu, HFnu, and LF/HF were calculated after signal processing and analysis. The unpaired Student t-test and intraclass correlation coefficient were used for data analysis. No statistically significant differences were observed when comparing the values analyzed by means of the two devices for HRV at rest and during exercise. The intraclass correlation coefficient demonstrated satisfactory correlation between the values obtained by the devices at rest (pNN50 = 0.994; rMSSD = 0.995; LFnu = 0.978; HFnu = 0.978; LF/HF = 0.982 and during exercise (pNN50 = 0.869; rMSSD = 0.929; LFnu = 0.973; HFnu = 0.973; LF/HF = 0.942. The calculation of HRV values by means of temporal series obtained from the Polar S810i instrument appears to be as reliable as those obtained by processing the ECG signal captured with a signal conditioner.

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals.

Science.gov (United States)

Hwang, Bosun; You, Jiwoo; Vaessen, Thomas; Myin-Germeys, Inez; Park, Cheolsoo; Zhang, Byoung-Tak

2018-02-08

Stress recognition using electrocardiogram (ECG) signals requires the intractable long-term heart rate variability (HRV) parameter extraction process. This study proposes a novel deep learning framework to recognize the stressful states, the Deep ECGNet, using ultra short-term raw ECG signals without any feature engineering methods. The Deep ECGNet was developed through various experiments and analysis of ECG waveforms. We proposed the optimal recurrent and convolutional neural networks architecture, and also the optimal convolution filter length (related to the P, Q, R, S, and T wave durations of ECG) and pooling length (related to the heart beat period) based on the optimization experiments and analysis on the waveform characteristics of ECG signals. The experiments were also conducted with conventional methods using HRV parameters and frequency features as a benchmark test. The data used in this study were obtained from Kwangwoon University in Korea (13 subjects, Case 1) and KU Leuven University in Belgium (9 subjects, Case 2). Experiments were designed according to various experimental protocols to elicit stressful conditions. The proposed framework to recognize stress conditions, the Deep ECGNet, outperformed the conventional approaches with the highest accuracy of 87.39% for Case 1 and 73.96% for Case 2, respectively, that is, 16.22% and 10.98% improvements compared with those of the conventional HRV method. We proposed an optimal deep learning architecture and its parameters for stress recognition, and the theoretical consideration on how to design the deep learning structure based on the periodic patterns of the raw ECG data. Experimental results in this study have proved that the proposed deep learning model, the Deep ECGNet, is an optimal structure to recognize the stress conditions using ultra short-term ECG data.

Comparison of different modalities in diagnosis of coronary artery disease (ECG, ETT, Angiography, Rest and Stress Echo. and 99m Tc-MIBI)

International Nuclear Information System (INIS)

Zein, A.A.M.

2002-01-01

This study was conducted in order to compare the most important five investigation modalities commonly used to investigate coronary artery disease, these were ECG, Exercise Tolerance Test (ETT), Echocardiography, SPECT imaging using 99m Tc-Sestamibi, and Angiography. The three test modalities, ECG, Echo, and 99m Tc-MIBI were conducted in both rest and stress conditions. All patients were referred to the hospital (NORI) from cardiology departments of different hospitals for stress/rest 99mTc-MIBI cardiac perfusion study. The decision to proceed with coronary angiography was made by the cardiologist to confirm or exclude diagnosis of CAD, to determine the potential surgical candidates and to assess complications if any. 17 patients were included in the study, 16 males and one female. All of them underwent the five test modalities mentioned, 80% of them were smokers, 47% were hypertensives, 20% were diabetics. The sensitivity of ECG, ETT, and Echocardiography were found to be 60.0%, 73.3%, and 82.4% respectively. Both angiography and 99mTc-Sestamibi were found to be 100% sensitive for detection of CAD. Specificity for all modalities tested was found to be 1, which is unrealistically high due to the small number of normal patients (only two). The predictive value of positive test came to be 1 for all test modalities, where as the predictive value of negative test was calculated to be 0.25, 0.33, and 0.67 for the tests, ECG, ETT, and Echocardiography respectively, but in case of 99mTc-Sestamibi, and coronary angiography it was found to be 1 for both of them. The localization ability of the different test modalities for ischemic and/or infarcted areas was investigated taking coronary angiography as the gold standard. All the three modalities, ECG, Echo, and 99mTc-Sestamibi showed good results in detection of areas supplied by left anterior descending artery, and on the other hand poor results in detection of left circumflex hypoperfused tributaries. The differential

A portable system for acquiring and removing motion artefact from ECG signals

Science.gov (United States)

Griffiths, A.; Das, A.; Fernandes, B.; Gaydecki, P.

2007-07-01

A novel electrocardiograph (ECG) signal acquisition and display system is under development. It is designed for patients ranging from the elderly to athletes. The signals are obtained from electrodes integrated into a vest, amplified, digitally processed and transmitted via Bluetooth to a PC with a Labview ® interface. Digital signal processing is performed to remove movement artefact and electromyographic (EMG) noise, which severely distorts signal morphology and complicates clinical diagnosis. Independent component analysis (ICA) is also used to improve the signal quality. The complete system will integrate the electronics into a single module which will be embedded in the vest.

A portable system for acquiring and removing motion artefact from ECG signals

Energy Technology Data Exchange (ETDEWEB)

Griffiths, A; Das, A; Fernandes, B; Gaydecki, P [School of Electrical and Electronic Engineering, University of Manchester, PO Box 88, Manchester M60 1QD (United Kingdom)

2007-07-15

A novel electrocardiograph (ECG) signal acquisition and display system is under development. It is designed for patients ranging from the elderly to athletes. The signals are obtained from electrodes integrated into a vest, amplified, digitally processed and transmitted via Bluetooth to a PC with a Labview (registered) interface. Digital signal processing is performed to remove movement artefact and electromyographic (EMG) noise, which severely distorts signal morphology and complicates clinical diagnosis. Independent component analysis (ICA) is also used to improve the signal quality. The complete system will integrate the electronics into a single module which will be embedded in the ves000.

High Resolution ECG for Evaluation of Heart Function During Exposure to Subacute Hypobaric Hypoxia

Science.gov (United States)

Zupet, Petra; Finderle, Zarko; Schlegel, Todd T.; Princi, Tanja; Starc, Vito

2010-01-01

High altitude climbing presents a wide spectrum of health risks, including exposure to hypobaric hypoxia. Risks are also typically exacerbated by the difficulty in appropriately monitoring for early signs of organ dysfunction in remote areas. We investigated whether high resolution advanced ECG analysis might be helpful as a non-invasive and easy-to-use tool (e.g., instead of Doppler echocardiography) for evaluating early signs of heart overload in hypobaric hypoxia. Nine non-acclimatized healthy trained alpine rescuers (age 43.7 plus or minus 7.3 years) climbed in four days to the altitude of 4,200 m on Mount Ararat. Five-minute high-resolution 12-lead electrocardiograms (ECGs) were recorded (Cardiosoft) in each subject at rest in the supine position on different days but at the same time of day at four different altitudes: 400 m (reference altitude), 1,700 m, 3,200 m and 4,200 m. Changes in conventional and advanced resting ECG parameters, including in beat-to-beat QT and RR variability, waveform complexity, signal-averaged, high-frequency and spatial/spatiotemporal ECG was estimated by calculation of the regression coefficients in independent linear regression models. A p-value of less than 0.05 was adopted as statistically significant. As expected, the RR interval and its variability both decreased with increasing altitude, with trends k = -96 ms/1000 m with p = 0.000 and k = -9 ms/1000 m with p = 0.001, respectively. Significant changes were found in P-wave amplitude, which nearly doubled from the lowest to the highest altitude (k = 41.6 microvolt/1000 m with p = 0.000), and nearly significant changes in P-wave duration (k = 2.9 ms/1000 m with p = 0.059). Changes were less significant or non-significant in other studied parameters including those of waveform complexity, signal-averaged, high-frequency and spatial/spatiotemporal ECG. High resolution ECG analysis, particularly of the P wave, shows promise as a tool for monitoring early changes in heart function

Variable threshold method for ECG R-peak detection.

Science.gov (United States)

Kew, Hsein-Ping; Jeong, Do-Un

2011-10-01

In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.

Efficient algorithm for baseline wander and powerline noise removal from ECG signals based on discrete Fourier series.

Science.gov (United States)

Bahaz, Mohamed; Benzid, Redha

2018-03-01

Electrocardiogram (ECG) signals are often contaminated with artefacts and noises which can lead to incorrect diagnosis when they are visually inspected by cardiologists. In this paper, the well-known discrete Fourier series (DFS) is re-explored and an efficient DFS-based method is proposed to reduce contribution of both baseline wander (BW) and powerline interference (PLI) noises in ECG records. In the first step, the determination of the exact number of low frequency harmonics contributing in BW is achieved. Next, the baseline drift is estimated by the sum of all associated Fourier sinusoids components. Then, the baseline shift is discarded efficiently by a subtraction of its approximated version from the original biased ECG signal. Concerning the PLI, the subtraction of the contributing harmonics calculated in the same manner reduces efficiently such type of noise. In addition of visual quality results, the proposed algorithm shows superior performance in terms of higher signal-to-noise ratio and smaller mean square error when faced to the DCT-based algorithm.

A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

Science.gov (United States)

Yildirim, Özal

2018-05-01

Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was proposed for classifying electrocardiogram (ECG) signals. For this purpose, a new wavelet-based layer is implemented to generate ECG signal sequences. The ECG signals were decomposed into frequency sub-bands at different scales in this layer. These sub-bands are used as sequences for the input of LSTM networks. New network models that include unidirectional (ULSTM) and bidirectional (BLSTM) structures are designed for performance comparisons. Experimental studies have been performed for five different types of heartbeats obtained from the MIT-BIH arrhythmia database. These five types are Normal Sinus Rhythm (NSR), Ventricular Premature Contraction (VPC), Paced Beat (PB), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB). The results show that the DBLSTM-WS model gives a high recognition performance of 99.39%. It has been observed that the wavelet-based layer proposed in the study significantly improves the recognition performance of conventional networks. This proposed network structure is an important approach that can be applied to similar signal processing problems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Can Functional Cardiac Age be Predicted from ECG in a Normal Healthy Population

Science.gov (United States)

Schlegel, Todd; Starc, Vito; Leban, Manja; Sinigoj, Petra; Vrhovec, Milos

2011-01-01

In a normal healthy population, we desired to determine the most age-dependent conventional and advanced ECG parameters. We hypothesized that changes in several ECG parameters might correlate with age and together reliably characterize the functional age of the heart. Methods: An initial study population of 313 apparently healthy subjects was ultimately reduced to 148 subjects (74 men, 84 women, in the range from 10 to 75 years of age) after exclusion criteria. In all subjects, ECG recordings (resting 5-minute 12-lead high frequency ECG) were evaluated via custom software programs to calculate up to 85 different conventional and advanced ECG parameters including beat-to-beat QT and RR variability, waveform complexity, and signal-averaged, high-frequency and spatial/spatiotemporal ECG parameters. The prediction of functional age was evaluated by multiple linear regression analysis using the best 5 univariate predictors. Results: Ignoring what were ultimately small differences between males and females, the functional age was found to be predicted (R2= 0.69, P ECGs, functional cardiac age can be estimated by multiple linear regression analysis of mostly advanced ECG results. Because some parameters in the regression formula, such as QTcorr, high frequency QRS amplitude and P-wave width also change with disease in the same direction as with increased age, increased functional age of the heart may reflect subtle age-related pathologies in cardiac electrical function that are usually hidden on conventional ECG.

Heart Rate Variability and Wavelet-based Studies on ECG Signals from Smokers and Non-smokers

Science.gov (United States)

Pal, K.; Goel, R.; Champaty, B.; Samantray, S.; Tibarewala, D. N.

2013-12-01

The current study deals with the heart rate variability (HRV) and wavelet-based ECG signal analysis of smokers and non-smokers. The results of HRV indicated dominance towards the sympathetic nervous system activity in smokers. The heart rate was found to be higher in case of smokers as compared to non-smokers ( p smokers from the non-smokers. The results indicated that when RMSSD, SD1 and RR-mean features were used concurrently a classification efficiency of > 90 % was achieved. The wavelet decomposition of the ECG signal was done using the Daubechies (db 6) wavelet family. No difference was observed between the smokers and non-smokers which apparently suggested that smoking does not affect the conduction pathway of heart.

[Investigation of fast filter of ECG signals with lifting wavelet and smooth filter].

Science.gov (United States)

Li, Xuefei; Mao, Yuxing; He, Wei; Yang, Fan; Zhou, Liang

2008-02-01

The lifting wavelet is used to decompose the original ECG signals and separate them into the approach signals with low frequency and the detail signals with high frequency, based on frequency characteristic. Parts of the detail signals are ignored according to the frequency characteristic. To avoid the distortion of QRS Complexes, the approach signals are filtered by an adaptive smooth filter with a proper threshold value. Through the inverse transform of the lifting wavelet, the reserved approach signals are reconstructed, and the three primary kinds of noise are limited effectively. In addition, the method is fast and there is no time delay between input and output.

Design of a Continuous Blood Pressure Measurement System Based on Pulse Wave and ECG Signals.

Science.gov (United States)

Li, Jian-Qiang; Li, Rui; Chen, Zhuang-Zhuang; Deng, Gen-Qiang; Wang, Huihui; Mavromoustakis, Constandinos X; Song, Houbing; Ming, Zhong

2018-01-01

With increasingly fierce competition for jobs, the pressures on people have risen in recent years, leading to lifestyle and diet disorders that result in significantly higher risks of cardiovascular disease. Hypertension is one of the common chronic cardiovascular diseases; however, mainstream blood pressure measurement devices are relatively heavy. When multiple measurements are required, the user experience and the measurement results may be unsatisfactory. In this paper, we describe the design of a signal collection module that collects pulse waves and electrocardiograph (ECG) signals. The collected signals are input into a signal processing module to filter the noise and amplify the useful physiological signals. Then, we use a wavelet transform to eliminate baseline drift noise and detect the feature points of the pulse waves and ECG signals. We propose the concept of detecting the wave shape associated with an instance, an approach that minimizes the impact of atypical pulse waves on blood pressure measurements. Finally, we propose an improved method for measuring blood pressure based on pulse wave velocity that improves the accuracy of blood pressure measurements by 58%. Moreover, the results meet the american medical instrument promotion association standards, which demonstrate the feasibility of our measurement system.

Flexible Graphene Electrodes for Prolonged Dynamic ECG Monitoring

Directory of Open Access Journals (Sweden)

Cunguang Lou

2016-11-01

Full Text Available This paper describes the development of a graphene-based dry flexible electrocardiography (ECG electrode and a portable wireless ECG measurement system. First, graphene films on polyethylene terephthalate (PET substrates and graphene paper were used to construct the ECG electrode. Then, a graphene textile was synthesized for the fabrication of a wearable ECG monitoring system. The structure and the electrical properties of the graphene electrodes were evaluated using Raman spectroscopy, scanning electron microscopy (SEM, and alternating current impedance spectroscopy. ECG signals were then collected from healthy subjects using the developed graphene electrode and portable measurement system. The results show that the graphene electrode was able to acquire the typical characteristics and features of human ECG signals with a high signal-to-noise (SNR ratio in different states of motion. A week-long continuous wearability test showed no degradation in the ECG signal quality over time. The graphene-based flexible electrode demonstrates comfortability, good biocompatibility, and high electrophysiological detection sensitivity. The graphene electrode also combines the potential for use in long-term wearable dynamic cardiac activity monitoring systems with convenience and comfort for use in home health care of elderly and high-risk adults.

Multistage principal component analysis based method for abdominal ECG decomposition

International Nuclear Information System (INIS)

Petrolis, Robertas; Krisciukaitis, Algimantas; Gintautas, Vladas

2015-01-01

Reflection of fetal heart electrical activity is present in registered abdominal ECG signals. However this signal component has noticeably less energy than concurrent signals, especially maternal ECG. Therefore traditionally recommended independent component analysis, fails to separate these two ECG signals. Multistage principal component analysis (PCA) is proposed for step-by-step extraction of abdominal ECG signal components. Truncated representation and subsequent subtraction of cardio cycles of maternal ECG are the first steps. The energy of fetal ECG component then becomes comparable or even exceeds energy of other components in the remaining signal. Second stage PCA concentrates energy of the sought signal in one principal component assuring its maximal amplitude regardless to the orientation of the fetus in multilead recordings. Third stage PCA is performed on signal excerpts representing detected fetal heart beats in aim to perform their truncated representation reconstructing their shape for further analysis. The algorithm was tested with PhysioNet Challenge 2013 signals and signals recorded in the Department of Obstetrics and Gynecology, Lithuanian University of Health Sciences. Results of our method in PhysioNet Challenge 2013 on open data set were: average score: 341.503 bpm 2 and 32.81 ms. (paper)

Evaluation by means of ECG-gated cardiac blood pool scintigraphy of global and regional left ventricular function at rest and during exercise in patients with coronary artery disease

International Nuclear Information System (INIS)

Sauer, E.; Sebening, H.; Lutilsky, L.; Dressler, H.; Hoer, G.; Pabst, H.W.; Bloemer, H.; Technische Univ. Muenchen

1978-01-01

ECG-gated cardiac blood pool scintigraphy permits a non-invasive determination of the end-diastolic and end-systolic ventricular volumens and of the ejection fraction as well as a qualitative description of regional ventricular wall motion at rest and during exercise. In 6 healthy persons a significant increase of the ejection fraction from 66 +- 7% at rest to 78 +- 3% during exercise (p [de

Robust QRS peak detection by multimodal information fusion of ECG and blood pressure signals.

Science.gov (United States)

Ding, Quan; Bai, Yong; Erol, Yusuf Bugra; Salas-Boni, Rebeca; Zhang, Xiaorong; Hu, Xiao

2016-11-01

QRS peak detection is a challenging problem when ECG signal is corrupted. However, additional physiological signals may also provide information about the QRS position. In this study, we focus on a unique benchmark provided by PhysioNet/Computing in Cardiology Challenge 2014 and Physiological Measurement focus issue: robust detection of heart beats in multimodal data, which aimed to explore robust methods for QRS detection in multimodal physiological signals. A dataset of 200 training and 210 testing records are used, where the testing records are hidden for evaluating the performance only. An information fusion framework for robust QRS detection is proposed by leveraging existing ECG and ABP analysis tools and combining heart beats derived from different sources. Results show that our approach achieves an overall accuracy of 90.94% and 88.66% on the training and testing datasets, respectively. Furthermore, we observe expected performance at each step of the proposed approach, as an evidence of the effectiveness of our approach. Discussion on the limitations of our approach is also provided.

Estimating actigraphy from motion artifacts in ECG and respiratory effort signals.

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Fonseca, Pedro; Aarts, Ronald M; Long, Xi; Rolink, Jérôme; Leonhardt, Steffen

2016-01-01

Recent work in unobtrusive sleep/wake classification has shown that cardiac and respiratory features can help improve classification performance. Nevertheless, actigraphy remains the single most discriminative modality for this task. Unfortunately, it requires the use of dedicated devices in addition to the sensors used to measure electrocardiogram (ECG) or respiratory effort. This paper proposes a method to estimate actigraphy from the body movement artifacts present in the ECG and respiratory inductance plethysmography (RIP) based on the time-frequency analysis of those signals. Using a continuous wavelet transform to analyze RIP, and ECG and RIP combined, it provides a surrogate measure of actigraphy with moderate correlation (for ECG+RIP, ρ = 0.74, p  <  0.001) and agreement (mean bias ratio of 0.94 and 95% agreement ratios of 0.11 and 8.45) with reference actigraphy. More important, it can be used as a replacement of actigraphy in sleep/wake classification: after cross-validation with a data set comprising polysomnographic (PSG) recordings of 15 healthy subjects and 25 insomniacs annotated by an external sleep technician, it achieves a statistically non-inferior classification performance when used together with respiratory features (average κ of 0.64 for 15 healthy subjects, and 0.50 for a dataset with 40 healthy and insomniac subjects), and when used together with respiratory and cardiac features (average κ of 0.66 for 15 healthy subjects, and 0.56 for 40 healthy and insomniac subjects). Since this method eliminates the need for a dedicated actigraphy device, it reduces the number of sensors needed for sleep/wake classification to a single sensor when using respiratory features, and to two sensors when using respiratory and cardiac features without any loss in performance. It offers a major benefit in terms of comfort for long-term home monitoring and is immediately applicable for legacy ECG and RIP monitoring devices already used in clinical

Development of a portable wireless system for bipolar concentric ECG recording

International Nuclear Information System (INIS)

Prats-Boluda, G; Ye-Lin, Y; Bueno Barrachina, J M; Senent, E; Rodriguez de Sanabria, R; Garcia-Casado, J

2015-01-01

Cardiovascular diseases (CVDs) remain the biggest cause of deaths worldwide. ECG monitoring is a key tool for early diagnosis of CVDs. Conventional monitors use monopolar electrodes resulting in poor spatial resolution surface recordings and requiring extensive wiring. High-spatial resolution surface electrocardiographic recordings provide valuable information for the diagnosis of a wide range of cardiac abnormalities, including infarction and arrhythmia. The aim of this work was to develop and test a wireless recording system for acquiring high spatial resolution ECG signals, based on a flexible tripolar concentric electrode (TCE) without cable wiring or external reference electrode which would make more comnfortable its use in clinical practice. For this, a portable, wireless sensor node for analogue conditioning, digitalization and transmission of a bipolar concentric ECG signal (BC-ECG) using a TCE and a Mason-likar Lead-I ECG (ML-Lead-I ECG) signal was developed. Experimental results from a total of 32 healthy volunteers showed that the ECG fiducial points in the BC-ECG signals, recorded with external and internal reference electrode, are consistent with those of simultaneous ML-Lead-I ECG. No statistically significant difference was found in either signal amplitude or morphology, regardless of the reference electrode used, being the signal-to-noise similar to that of ML-Lead-I ECG. Furthermore, it has been observed that BC-ECG signals contain information that could not available in conventional records, specially related to atria activity. The proposed wireless sensor node provides non-invasive high-local resolution ECG signals using only a TCE without additional wiring, which would have great potential in medical diagnosis of diseases such as atrial or ventricular fibrillations or arrhythmias that currently require invasive diagnostic procedures (catheterization). (paper)

The PLR-DTW method for ECG based biometric identification.

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Shen, Jun; Bao, Shu-Di; Yang, Li-Cai; Li, Ye

2011-01-01

There has been a surge of research on electrocardiogram (ECG) signal based biometric for person identification. Though most of the existing studies claimed that ECG signal is unique to an individual and can be a viable biometric, one of the main difficulties for real-world applications of ECG biometric is the accuracy performance. To address this problem, this study proposes a PLR-DTW method for ECG biometric, where the Piecewise Linear Representation (PLR) is used to keep important information of an ECG signal segment while reduce the data dimension at the same time if necessary, and the Dynamic Time Warping (DTW) is used for similarity measures between two signal segments. The performance evaluation was carried out on three ECG databases, and the existing method using wavelet coefficients, which was proved to have good accuracy performance, was selected for comparison. The analysis results show that the PLR-DTW method achieves an accuracy rate of 100% for identification, while the one using wavelet coefficients achieved only around 93%.

PIC microcontroller-based RF wireless ECG monitoring system.

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Oweis, R J; Barhoum, A

2007-01-01

This paper presents a radio-telemetry system that provides the possibility of ECG signal transmission from a patient detection circuit via an RF data link. A PC then receives the signal through the National Instrument data acquisition card (NIDAQ). The PC is equipped with software allowing the received ECG signals to be saved, analysed, and sent by email to another part of the world. The proposed telemetry system consists of a patient unit and a PC unit. The amplified and filtered ECG signal is sampled 360 times per second, and the A/D conversion is performed by a PIC16f877 microcontroller. The major contribution of the final proposed system is that it detects, processes and sends patients ECG data over a wireless RF link to a maximum distance of 200 m. Transmitted ECG data with different numbers of samples were received, decoded by means of another PIC microcontroller, and displayed using MATLAB program. The designed software is presented in a graphical user interface utility.

Sparse Matrix for ECG Identification with Two-Lead Features

Directory of Open Access Journals (Sweden)

Kuo-Kun Tseng

2015-01-01

Full Text Available Electrocardiograph (ECG human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods.

Low-complexity R-peak detection in ECG signals : a preliminary step towards ambulatory fetal monitoring

NARCIS (Netherlands)

Rooijakkers, M.J.; Rabotti, C.; Bennebroek, M.; Meerbergen, van J.; Mischi, M.

2011-01-01

Non-invasive fetal health monitoring during pregnancy has become increasingly important. Recent advances in signal processing technology have enabled fetal monitoring during pregnancy, using abdominal ECG recordings. Ubiquitous ambulatory monitoring for continuous fetal health measurement is however

Fully Textile, PEDOT:PSS Based Electrodes for Wearable ECG Monitoring Systems.

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Pani, Danilo; Dessi, Alessia; Saenz-Cogollo, Jose F; Barabino, Gianluca; Fraboni, Beatrice; Bonfiglio, Annalisa

2016-03-01

To evaluate a novel kind of textile electrodes based on woven fabrics treated with PSS, through an easy fabrication process, testing these electrodes for biopotential recordings. Fabrication is based on raw fabric soaking in PSS using a second dopant, squeezing and annealing. The electrodes have been tested on human volunteers, in terms of both skin contact impedance and quality of the ECG signals recorded at rest and during physical activity (power spectral density, baseline wandering, QRS detectability, and broadband noise). The electrodes are able to operate in both wet and dry conditions. Dry electrodes are more prone to noise artifacts, especially during physical exercise and mainly due to the unstable contact between the electrode and the skin. Wet (saline) electrodes present a stable and reproducible behavior, which is comparable or better than that of traditional disposable gelled Ag/AgCl electrodes. The achieved results reveal the capability of this kind of electrodes to work without the electrolyte, providing a valuable interface with the skin, due to mixed electronic and ionic conductivity of PSS. These electrodes can be effectively used for acquiring ECG signals. Textile electrodes based on PSS represent an important milestone in wearable monitoring, as they present an easy and reproducible fabrication process, very good performance in wet and dry (at rest) conditions and a superior level of comfort with respect to textile electrodes proposed so far. This paves the way to their integration into smart garments.

ECG Identification System Using Neural Network with Global and Local Features

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Tseng, Kuo-Kun; Lee, Dachao; Chen, Charles

2016-01-01

This paper proposes a human identification system via extracted electrocardiogram (ECG) signals. Two hierarchical classification structures based on global shape feature and local statistical feature is used to extract ECG signals. Global shape feature represents the outline information of ECG signals and local statistical feature extracts the…

A wearable 12-lead ECG acquisition system with fabric electrodes.

Science.gov (United States)

Haoshi Zhang; Lan Tian; Huiyang Lu; Ming Zhou; Haiqing Zou; Peng Fang; Fuan Yao; Guanglin Li

2017-07-01

Continuous electrocardiogram (ECG) monitoring is significant for prevention of heart disease and is becoming an important part of personal and family health care. In most of the existing wearable solutions, conventional metal sensors and corresponding chips are simply integrated into clothes and usually could only collect few leads of ECG signals that could not provide enough information for diagnosis of cardiac diseases such as arrhythmia and myocardial ischemia. In this study, a wearable 12-lead ECG acquisition system with fabric electrodes was developed and could simultaneously process 12 leads of ECG signals. By integrating the fabric electrodes into a T-shirt, the wearable system would provide a comfortable and convenient user interface for ECG recording. For comparison, the proposed fabric electrode and the gelled traditional metal electrodes were used to collect ECG signals on a subject, respectively. The approximate entropy (ApEn) of ECG signals from both types of electrodes were calculated. The experimental results show that the fabric electrodes could achieve similar performance as the gelled metal electrodes. This preliminary work has demonstrated that the developed ECG system with fabric electrodes could be utilized for wearable health management and telemedicine applications.

Evaluation of a Multichannel Non-Contact ECG System and Signal Quality Algorithms for Sleep Apnea Detection and Monitoring

Directory of Open Access Journals (Sweden)

Ivan D. Castro

2018-02-01

Full Text Available Sleep-related conditions require high-cost and low-comfort diagnosis at the hospital during one night or longer. To overcome this situation, this work aims to evaluate an unobtrusive monitoring technique for sleep apnea. This paper presents, for the first time, the evaluation of contactless capacitively-coupled electrocardiography (ccECG signals for the extraction of sleep apnea features, together with a comparison of different signal quality indicators. A multichannel ccECG system is used to collect signals from 15 subjects in a sleep environment from different positions. Reference quality labels were assigned for every 30-s segment. Quality indicators were calculated, and their signal classification performance was evaluated. Features for the detection of sleep apnea were extracted from capacitive and reference signals. Sleep apnea features related to heart rate and heart rate variability achieved high similarity to the reference values, with p-values of 0.94 and 0.98, which is in line with the more than 95% beat-matching obtained. Features related to signal morphology presented lower similarity with the reference, although signal similarity metrics of correlation and coherence were relatively high. Quality-based automatic classification of the signals had a maximum accuracy of 91%. Best-performing quality indicators were based on template correlation and beat-detection. Results suggest that using unobtrusive cardiac signals for the automatic detection of sleep apnea can achieve similar performance as contact signals, and indicates clinical value of ccECG. Moreover, signal segments can automatically be classified by the proposed quality metrics as a pre-processing step. Including contactless respiration signals is likely to improve the performance and provide a complete unobtrusive cardiorespiratory monitoring solution; this is a promising alternative that will allow the screening of more patients with higher comfort, for a longer time, and at

Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

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Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

2017-07-01

Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

FastICA peel-off for ECG interference removal from surface EMG.

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Chen, Maoqi; Zhang, Xu; Chen, Xiang; Zhu, Mingxing; Li, Guanglin; Zhou, Ping

2016-06-13

Multi-channel recording of surface electromyographyic (EMG) signals is very likely to be contaminated by electrocardiographic (ECG) interference, specifically when the surface electrode is placed on muscles close to the heart. A novel fast independent component analysis (FastICA) based peel-off method is presented to remove ECG interference contaminating multi-channel surface EMG signals. Although demonstrating spatial variability in waveform shape, the ECG interference in different channels shares the same firing instants. Utilizing the firing information estimated from FastICA, ECG interference can be separated from surface EMG by a "peel off" processing. The performance of the method was quantified with synthetic signals by combining a series of experimentally recorded "clean" surface EMG and "pure" ECG interference. It was demonstrated that the new method can remove ECG interference efficiently with little distortion to surface EMG amplitude and frequency. The proposed method was also validated using experimental surface EMG signals contaminated by ECG interference. The proposed FastICA peel-off method can be used as a new and practical solution to eliminating ECG interference from multichannel EMG recordings.

A model-based Bayesian framework for ECG beat segmentation

International Nuclear Information System (INIS)

Sayadi, O; Shamsollahi, M B

2009-01-01

The study of electrocardiogram (ECG) waveform amplitudes, timings and patterns has been the subject of intense research, for it provides a deep insight into the diagnostic features of the heart's functionality. In some recent works, a Bayesian filtering paradigm has been proposed for denoising and compression of ECG signals. In this paper, it is shown that this framework may be effectively used for ECG beat segmentation and extraction of fiducial points. Analytic expressions for the determination of points and intervals are derived and evaluated on various real ECG signals. Simulation results show that the method can contribute to and enhance the clinical ECG beat segmentation performance

Aiding the Detection of QRS Complex in ECG Signals by Detecting S Peaks Independently.

Science.gov (United States)

Sabherwal, Pooja; Singh, Latika; Agrawal, Monika

2018-03-30

In this paper, a novel algorithm for the accurate detection of QRS complex by combining the independent detection of R and S peaks, using fusion algorithm is proposed. R peak detection has been extensively studied and is being used to detect the QRS complex. Whereas, S peaks, which is also part of QRS complex can be independently detected to aid the detection of QRS complex. In this paper, we suggest a method to first estimate S peak from raw ECG signal and then use them to aid the detection of QRS complex. The amplitude of S peak in ECG signal is relatively weak than corresponding R peak, which is traditionally used for the detection of QRS complex, therefore, an appropriate digital filter is designed to enhance the S peaks. These enhanced S peaks are then detected by adaptive thresholding. The algorithm is validated on all the signals of MIT-BIH arrhythmia database and noise stress database taken from physionet.org. The algorithm performs reasonably well even for the signals highly corrupted by noise. The algorithm performance is confirmed by sensitivity and positive predictivity of 99.99% and the detection accuracy of 99.98% for QRS complex detection. The number of false positives and false negatives resulted while analysis has been drastically reduced to 80 and 42 against the 98 and 84 the best results reported so far.

Decomposition of ECG by linear filtering.

Science.gov (United States)

Murthy, I S; Niranjan, U C

1992-01-01

A simple method is developed for the delineation of a given electrocardiogram (ECG) signal into its component waves. The properties of discrete cosine transform (DCT) are exploited for the purpose. The transformed signal is convolved with appropriate filters and the component waves are obtained by computing the inverse transform (IDCT) of the filtered signals. The filters are derived from the time signal itself. Analysis of continuous strips of ECG signals with various arrhythmias showed that the performance of the method is satisfactory both qualitatively and quantitatively. The small amplitude P wave usually had a high percentage rms difference (PRD) compared to the other large component waves.

Hardware-efficient robust biometric identification from 0.58 second template and 12 features of limb (Lead I) ECG signal using logistic regression classifier.

Science.gov (United States)

Sahadat, Md Nazmus; Jacobs, Eddie L; Morshed, Bashir I

2014-01-01

The electrocardiogram (ECG), widely known as a cardiac diagnostic signal, has recently been proposed for biometric identification of individuals; however reliability and reproducibility are of research interest. In this paper, we propose a template matching technique with 12 features using logistic regression classifier that achieved high reliability and identification accuracy. Non-invasive ECG signals were captured using our custom-built ambulatory EEG/ECG embedded device (NeuroMonitor). ECG data were collected from healthy subjects (10), between 25-35 years, for 10 seconds per trial. The number of trials from each subject was 10. From each trial, only 0.58 seconds of Lead I ECG data were used as template. Hardware-efficient fiducial point detection technique was implemented for feature extraction. To obtain repeated random sub-sampling validation, data were randomly separated into training and testing sets at a ratio of 80:20. Test data were used to find the classification accuracy. ECG template data with 12 extracted features provided the best performance in terms of accuracy (up to 100%) and processing complexity (computation time of 1.2ms). This work shows that a single limb (Lead I) ECG can robustly identify an individual quickly and reliably with minimal contact and data processing using the proposed algorithm.

Near Field Communication-based telemonitoring with integrated ECG recordings.

Science.gov (United States)

Morak, J; Kumpusch, H; Hayn, D; Leitner, M; Scherr, D; Fruhwald, F M; Schreier, G

2011-01-01

Telemonitoring of vital signs is an established option in treatment of patients with chronic heart failure (CHF). In order to allow for early detection of atrial fibrillation (AF) which is highly prevalent in the CHF population telemonitoring programs should include electrocardiogram (ECG) signals. It was therefore the aim to extend our current home monitoring system based on mobile phones and Near Field Communication technology (NFC) to enable patients acquiring their ECG signals autonomously in an easy-to-use way. We prototypically developed a sensing device for the concurrent acquisition of blood pressure and ECG signals. The design of the device equipped with NFC technology and Bluetooth allowed for intuitive interaction with a mobile phone based patient terminal. This ECG monitoring system was evaluated in the course of a clinical pilot trial to assess the system's technical feasibility, usability and patient's adherence to twice daily usage. 21 patients (4f, 54 ± 14 years) suffering from CHF were included in the study and were asked to transmit two ECG recordings per day via the telemonitoring system autonomously over a monitoring period of seven days. One patient dropped out from the study. 211 data sets were transmitted over a cumulative monitoring period of 140 days (overall adherence rate 82.2%). 55% and 8% of the transmitted ECG signals were sufficient for ventricular and atrial rhythm assessment, respectively. Although ECG signal quality has to be improved for better AF detection the developed communication design of joining Bluetooth and NFC technology in our telemonitoring system allows for ambulatory ECG acquisition with high adherence rates and system usability in heart failure patients.

WAVELET ANALYSIS OF ABNORMAL ECGS

Directory of Open Access Journals (Sweden)

Vasudha Nannaparaju

2014-02-01

Full Text Available Detection of the warning signals by the heart can be diagnosed from ECG. An accurate and reliable diagnosis of ECG is very important however which is cumbersome and at times ambiguous in time domain due to the presence of noise. Study of ECG in wavelet domain using both continuous Wavelet transform (CWT and discrete Wavelet transform (DWT, with well known wavelet as well as a wavelet proposed by the authors for this investigation is found to be useful and yields fairly reliable results. In this study, Wavelet analysis of ECGs of Normal, Hypertensive, Diabetic and Cardiac are carried out. The salient feature of the study is that detection of P and T phases in wavelet domain is feasible which are otherwise feeble or absent in raw ECGs.

[An Algorithm to Eliminate Power Frequency Interference in ECG Using Template].

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Shi, Guohua; Li, Jiang; Xu, Yan; Feng, Liang

2017-01-01

Researching an algorithm to eliminate power frequency interference in ECG. The algorithm first creates power frequency interference template, then, subtracts the template from the original ECG signals, final y, the algorithm gets the ECG signals without interference. Experiment shows the algorithm can eliminate interference effectively and has none side effect to normal signal. It’s efficient and suitable for practice.

Statistical performance evaluation of ECG transmission using wireless networks.

Science.gov (United States)

Shakhatreh, Walid; Gharaibeh, Khaled; Al-Zaben, Awad

2013-07-01

This paper presents simulation of the transmission of biomedical signals (using ECG signal as an example) over wireless networks. Investigation of the effect of channel impairments including SNR, pathloss exponent, path delay and network impairments such as packet loss probability; on the diagnosability of the received ECG signal are presented. The ECG signal is transmitted through a wireless network system composed of two communication protocols; an 802.15.4- ZigBee protocol and an 802.11b protocol. The performance of the transmission is evaluated using higher order statistics parameters such as kurtosis and Negative Entropy in addition to the common techniques such as the PRD, RMS and Cross Correlation.

Programming a DSP card for generating an ECG signal with possibility of anomalies

International Nuclear Information System (INIS)

Hamrouni, Sayma

2013-01-01

This project consists of programming a DSP designed to generate an ECG signal with a probability of anomaly. To begin with, we get to know the characteristics of a DSP card and its architecture. As a second step, we programmed the DSP32C using the compiler D3CC associated with Textpad in order to obtain an analog signal in the respective outputs. And then finally, we developed a graphical user interface using the programming software LabVIEW that aims controlling the good operation of DSP. The tests previously made have proved the good operation of the application.

Low-power analog integrated circuits for wireless ECG acquisition systems.

Science.gov (United States)

Tsai, Tsung-Heng; Hong, Jia-Hua; Wang, Liang-Hung; Lee, Shuenn-Yuh

2012-09-01

This paper presents low-power analog ICs for wireless ECG acquisition systems. Considering the power-efficient communication in the body sensor network, the required low-power analog ICs are developed for a healthcare system through miniaturization and system integration. To acquire the ECG signal, a low-power analog front-end system, including an ECG signal acquisition board, an on-chip low-pass filter, and an on-chip successive-approximation analog-to-digital converter for portable ECG detection devices is presented. A quadrature CMOS voltage-controlled oscillator and a 2.4 GHz direct-conversion transmitter with a power amplifier and upconversion mixer are also developed to transmit the ECG signal through wireless communication. In the receiver, a 2.4 GHz fully integrated CMOS RF front end with a low-noise amplifier, differential power splitter, and quadrature mixer based on current-reused folded architecture is proposed. The circuits have been implemented to meet the specifications of the IEEE 802.15.4 2.4 GHz standard. The low-power ICs of the wireless ECG acquisition systems have been fabricated using a 0.18 μm Taiwan Semiconductor Manufacturing Company (TSMC) CMOS standard process. The measured results on the human body reveal that ECG signals can be acquired effectively by the proposed low-power analog front-end ICs.

ECG artifact cancellation in surface EMG signals by fractional order calculus application.

Science.gov (United States)

Miljković, Nadica; Popović, Nenad; Djordjević, Olivera; Konstantinović, Ljubica; Šekara, Tomislav B

2017-03-01

New aspects for automatic electrocardiography artifact removal from surface electromyography signals by application of fractional order calculus in combination with linear and nonlinear moving window filters are explored. Surface electromyography recordings of skeletal trunk muscles are commonly contaminated with spike shaped artifacts. This artifact originates from electrical heart activity, recorded by electrocardiography, commonly present in the surface electromyography signals recorded in heart proximity. For appropriate assessment of neuromuscular changes by means of surface electromyography, application of a proper filtering technique of electrocardiography artifact is crucial. A novel method for automatic artifact cancellation in surface electromyography signals by applying fractional order calculus and nonlinear median filter is introduced. The proposed method is compared with the linear moving average filter, with and without prior application of fractional order calculus. 3D graphs for assessment of window lengths of the filters, crest factors, root mean square differences, and fractional calculus orders (called WFC and WRC graphs) have been introduced. For an appropriate quantitative filtering evaluation, the synthetic electrocardiography signal and analogous semi-synthetic dataset have been generated. The examples of noise removal in 10 able-bodied subjects and in one patient with muscle dystrophy are presented for qualitative analysis. The crest factors, correlation coefficients, and root mean square differences of the recorded and semi-synthetic electromyography datasets showed that the most successful method was the median filter in combination with fractional order calculus of the order 0.9. Statistically more significant (p ECG peak reduction was obtained by the median filter application compared to the moving average filter in the cases of low level amplitude of muscle contraction compared to ECG spikes. The presented results suggest that the

Low-complexity R-peak detection in ECG signals: a preliminary step towards ambulatory fetal monitoring.

Science.gov (United States)

Rooijakkers, Michiel; Rabotti, Chiara; Bennebroek, Martijn; van Meerbergen, Jef; Mischi, Massimo

2011-01-01

Non-invasive fetal health monitoring during pregnancy has become increasingly important. Recent advances in signal processing technology have enabled fetal monitoring during pregnancy, using abdominal ECG recordings. Ubiquitous ambulatory monitoring for continuous fetal health measurement is however still unfeasible due to the computational complexity of noise robust solutions. In this paper an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, while increasing the R-peak detection quality compared to existing R-peak detection schemes. Validation of the algorithm is performed on two manually annotated datasets, the MIT/BIH Arrhythmia database and an in-house abdominal database. Both R-peak detection quality and computational complexity are compared to state-of-the-art algorithms as described in the literature. With a detection error rate of 0.22% and 0.12% on the MIT/BIH Arrhythmia and in-house databases, respectively, the quality of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

Automatic ECG quality scoring methodology: mimicking human annotators

International Nuclear Information System (INIS)

Johannesen, Lars; Galeotti, Loriano

2012-01-01

An algorithm to determine the quality of electrocardiograms (ECGs) can enable inexperienced nurses and paramedics to record ECGs of sufficient diagnostic quality. Previously, we proposed an algorithm for determining if ECG recordings are of acceptable quality, which was entered in the PhysioNet Challenge 2011. In the present work, we propose an improved two-step algorithm, which first rejects ECGs with macroscopic errors (signal absent, large voltage shifts or saturation) and subsequently quantifies the noise (baseline, powerline or muscular noise) on a continuous scale. The performance of the improved algorithm was evaluated using the PhysioNet Challenge database (1500 ECGs rated by humans for signal quality). We achieved a classification accuracy of 92.3% on the training set and 90.0% on the test set. The improved algorithm is capable of detecting ECGs with macroscopic errors and giving the user a score of the overall quality. This allows the user to assess the degree of noise and decide if it is acceptable depending on the purpose of the recording. (paper)

Improving Remote Health Monitoring: A Low-Complexity ECG Compression Approach.

Science.gov (United States)

Elgendi, Mohamed; Al-Ali, Abdulla; Mohamed, Amr; Ward, Rabab

2018-01-16

Recent advances in mobile technology have created a shift towards using battery-driven devices in remote monitoring settings and smart homes. Clinicians are carrying out diagnostic and screening procedures based on the electrocardiogram (ECG) signals collected remotely for outpatients who need continuous monitoring. High-speed transmission and analysis of large recorded ECG signals are essential, especially with the increased use of battery-powered devices. Exploring low-power alternative compression methodologies that have high efficiency and that enable ECG signal collection, transmission, and analysis in a smart home or remote location is required. Compression algorithms based on adaptive linear predictors and decimation by a factor B / K are evaluated based on compression ratio (CR), percentage root-mean-square difference (PRD), and heartbeat detection accuracy of the reconstructed ECG signal. With two databases (153 subjects), the new algorithm demonstrates the highest compression performance ( CR = 6 and PRD = 1.88 ) and overall detection accuracy (99.90% sensitivity, 99.56% positive predictivity) over both databases. The proposed algorithm presents an advantage for the real-time transmission of ECG signals using a faster and more efficient method, which meets the growing demand for more efficient remote health monitoring.

Improving Remote Health Monitoring: A Low-Complexity ECG Compression Approach

Directory of Open Access Journals (Sweden)

Mohamed Elgendi

2018-01-01

Full Text Available Recent advances in mobile technology have created a shift towards using battery-driven devices in remote monitoring settings and smart homes. Clinicians are carrying out diagnostic and screening procedures based on the electrocardiogram (ECG signals collected remotely for outpatients who need continuous monitoring. High-speed transmission and analysis of large recorded ECG signals are essential, especially with the increased use of battery-powered devices. Exploring low-power alternative compression methodologies that have high efficiency and that enable ECG signal collection, transmission, and analysis in a smart home or remote location is required. Compression algorithms based on adaptive linear predictors and decimation by a factor B / K are evaluated based on compression ratio (CR, percentage root-mean-square difference (PRD, and heartbeat detection accuracy of the reconstructed ECG signal. With two databases (153 subjects, the new algorithm demonstrates the highest compression performance ( CR = 6 and PRD = 1.88 and overall detection accuracy (99.90% sensitivity, 99.56% positive predictivity over both databases. The proposed algorithm presents an advantage for the real-time transmission of ECG signals using a faster and more efficient method, which meets the growing demand for more efficient remote health monitoring.

Alexander fractional differential window filter for ECG denoising.

Science.gov (United States)

Verma, Atul Kumar; Saini, Indu; Saini, Barjinder Singh

2018-06-01

The electrocardiogram (ECG) non-invasively monitors the electrical activities of the heart. During the process of recording and transmission, ECG signals are often corrupted by various types of noises. Minimizations of these noises facilitate accurate detection of various anomalies. In the present paper, Alexander fractional differential window (AFDW) filter is proposed for ECG signal denoising. The designed filter is based on the concept of generalized Alexander polynomial and the R-L differential equation of fractional calculus. This concept is utilized to formulate a window that acts as a forward filter. Thereafter, the backward filter is constructed by reversing the coefficients of the forward filter. The proposed AFDW filter is then obtained by averaging of the forward and backward filter coefficients. The performance of the designed AFDW filter is validated by adding the various type of noise to the original ECG signal obtained from MIT-BIH arrhythmia database. The two non-diagnostic measure, i.e., SNR, MSE, and one diagnostic measure, i.e., wavelet energy based diagnostic distortion (WEDD) have been employed for the quantitative evaluation of the designed filter. Extensive experimentations on all the 48-records of MIT-BIH arrhythmia database resulted in average SNR of 22.014 ± 3.806365, 14.703 ± 3.790275, 13.3183 ± 3.748230; average MSE of 0.001458 ± 0.00028, 0.0078 ± 0.000319, 0.01061 ± 0.000472; and average WEDD value of 0.020169 ± 0.01306, 0.1207 ± 0.061272, 0.1432 ± 0.073588, for ECG signal contaminated by the power line, random, and the white Gaussian noise respectively. A new metric named as morphological power preservation measure (MPPM) is also proposed that account for the power preservance (as indicated by PSD plots) and the QRS morphology. The proposed AFDW filter retained much of the original (clean) signal power without any significant morphological distortion as validated by MPPM measure that were 0

ECG denoising with adaptive bionic wavelet transform.

Science.gov (United States)

Sayadi, Omid; Shamsollahi, Mohammad Bagher

2006-01-01

In this paper a new ECG denoising scheme is proposed using a novel adaptive wavelet transform, named bionic wavelet transform (BWT), which had been first developed based on a model of the active auditory system. There has been some outstanding features with the BWT such as nonlinearity, high sensitivity and frequency selectivity, concentrated energy distribution and its ability to reconstruct signal via inverse transform but the most distinguishing characteristic of BWT is that its resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential. Besides by optimizing the BWT parameters parallel to modifying a new threshold value, one can handle ECG denoising with results comparing to those of wavelet transform (WT). Preliminary tests of BWT application to ECG denoising were constructed on the signals of MIT-BIH database which showed high performance of noise reduction.

Visualization of neonatal coronary arteries on multidetector row CT: ECG-gated versus non-ECG-gated technique

International Nuclear Information System (INIS)

Tsai, I.C.; Lee, Tain; Chen, Min-Chi; Fu, Yun-Ching; Jan, Sheng-Lin; Wang, Chung-Chi; Chang, Yen

2007-01-01

Multidetector CT (MDCT) seems to be a promising tool for detection of neonatal coronary arteries, but whether the ECG-gated or non-ECG-gated technique should be used has not been established. To compare the detection rate and image quality of neonatal coronary arteries on MDCT using ECG-gated and non-ECG-gated techniques. Twelve neonates with complex congenital heart disease were included. The CT scan was acquired using an ECG-gated technique, and the most quiescent phase of the RR interval was selected to represent the ECG-gated images. The raw data were then reconstructed without the ECG signal to obtain non-ECG-gated images. The detection rate and image quality of nine coronary artery segments in the two sets of images were then compared. A two-tailed paired t test was used with P values <0.05 considered as statistically significant. In all coronary segments the ECG-gated technique had a better detection rate and produced images of better quality. The difference between the two techniques ranged from 25% in the left main coronary artery to 100% in the distal right coronary artery. For neonates referred for MDCT, if evaluation of coronary artery anatomy is important for the clinical management or surgical planning, the ECG-gated technique should be used because it can reliably detect the coronary arteries. (orig.)

QRS detection based ECG quality assessment

International Nuclear Information System (INIS)

Hayn, Dieter; Jammerbund, Bernhard; Schreier, Günter

2012-01-01

Although immediate feedback concerning ECG signal quality during recording is useful, up to now not much literature describing quality measures is available. We have implemented and evaluated four ECG quality measures. Empty lead criterion (A), spike detection criterion (B) and lead crossing point criterion (C) were calculated from basic signal properties. Measure D quantified the robustness of QRS detection when applied to the signal. An advanced Matlab-based algorithm combining all four measures and a simplified algorithm for Android platforms, excluding measure D, were developed. Both algorithms were evaluated by taking part in the Computing in Cardiology Challenge 2011. Each measure's accuracy and computing time was evaluated separately. During the challenge, the advanced algorithm correctly classified 93.3% of the ECGs in the training-set and 91.6 % in the test-set. Scores for the simplified algorithm were 0.834 in event 2 and 0.873 in event 3. Computing time for measure D was almost five times higher than for other measures. Required accuracy levels depend on the application and are related to computing time. While our simplified algorithm may be accurate for real-time feedback during ECG self-recordings, QRS detection based measures can further increase the performance if sufficient computing power is available. (paper)

Low-cost compact ECG with graphic LCD and phonocardiogram system design.

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Kara, Sadik; Kemaloğlu, Semra; Kirbaş, Samil

2006-06-01

Till today, many different ECG devices are made in developing countries. In this study, low cost, small size, portable LCD screen ECG device, and phonocardiograph were designed. With designed system, heart sounds that take synchronously with ECG signal are heard as sensitive. Improved system consist three units; Unit 1, ECG circuit, filter and amplifier structure. Unit 2, heart sound acquisition circuit. Unit 3, microcontroller, graphic LCD and ECG signal sending unit to computer. Our system can be used easily in different departments of the hospital, health institution and clinics, village clinic and also in houses because of its small size structure and other benefits. In this way, it is possible that to see ECG signal and hear heart sounds as synchronously and sensitively. In conclusion, heart sounds are heard on the part of both doctor and patient because sounds are given to environment with a tiny speaker. Thus, the patient knows and hears heart sounds him/herself and is acquainted by doctor about healthy condition.

Leptin signaling in skeletal muscle after bed rest in healthy humans

DEFF Research Database (Denmark)

Guerra, Borja; Ponce-Gonzalez, Jesus Gustavo; Morales-Alamo, David

2014-01-01

. Leptin receptor isoforms (OB-Rs), suppressor of cytokine signaling 3 (SOCS3) and protein tyrosine phosphatase 1B (PTP1B) protein expression and signal transducer and activator of transcription 3 (STAT3) phosphorylation were analyzed by Western blot. RESULTS: After bed rest basal insulin concentration.......4-fold after bed rest (P PTP1B in the deltoid. PTP1B was increased by 90% with bed rest in the vastus lateralis (P ... between the increase in vastus lateralis PTP1B and the increase in both basal insulin concentrations (r = 0.66, P

[Study for portable dynamic ECG monitor and recorder].

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Yang, Pengcheng; Li, Yongqin; Chen, Bihua

2012-09-01

This Paper presents a portable dynamic ECG monitor system based on MSP430F149 microcontroller. The electrocardiogram detecting system consists of ECG detecting circuit, man-machine interaction module, MSP430F149 and upper computer software. The ECG detecting circuit including a preamplifier, second-order Butterworth low-pass filter, high-pass filter, and 50Hz trap circuit to detects electrocardiogram and depresses various kinds of interference effectively. A microcontroller is used to collect three channel analog signals which can be displayed on TFT LCD. A SD card is used to record real-time data continuously and implement the FTA16 file system. In the end, a host computer system interface is also designed to analyze the ECG signal and the analysis results can provide diagnosis references to clinical doctors.

A noise reconfigurable current-reuse resistive feedback amplifier with signal-dependent power consumption for fetal ECG monitoring

NARCIS (Netherlands)

Song, Shuang; Rooijakkers, M.J.; Harpe, P.; Rabotti, C.; Mischi, M.; Van Roermund, A.H.M.; Cantatore, E.

2016-01-01

This paper presents a noise-reconfigurable resistive feedback amplifier with current-reuse technique for fetal ECG monitoring. The proposed amplifier allows for both tuning of the noise level and changing the power consumption according to the signal properties, minimizing the total power

Prospective ECG triggering versus low-dose retrospective ECG-gated 128-channel CT coronary angiography: comparison of image quality and radiation dose

International Nuclear Information System (INIS)

Feng, Q.; Yin, Y.; Hua, X.; Zhu, R.; Hua, J.; Xu, J.

2010-01-01

Aim: To evaluate image quality and radiation dose for 128-detector prospective electrocardiogram (ECG)-gated computed tomography coronary angiography (CTCA) compared with a low-dose retrospective ECG-gated imaging protocol. Materials and methods: Thirty-one and 47 patients suspected of having coronary artery disease were enrolled into groups examined using prospective and low-dose retrospective ECG-gated CT protocols respectively. All examinations were performed on a 128-detector CT system (Definition AS, Siemens Healthcare, Forchheim, Germany). Prospective CTCA was performed using following parameters: tube voltage 100 kV; tube current 205 mAs; centre of acquisition window 70% of the RR interval. The tube current for low-dose retrospective ECG-gated CTCA was full dose during 40-70% of the RR interval and partial dose for the rest of RR interval. The pitch varied between 0.2 and 0.5 depending on heart rate and patient size. Image quality of coronary arteries was evaluated using a four-point grading scale. The signal-to-noise ratios (SNRs) of enhanced arteries and myocardium were also measured, corresponding contrast-to-noise ratios (CNRs) were calculated, and the radiation doses received were recorded. Results: There was a significant difference in the image quality scores between the retrospective and prospective gating protocols (Chi-square = 15.331, p = 0.009). There was no significant difference between the SNRs of the contrasted artery and myocardium in these two groups, but the CNRs were increased in the prospective group. The mean radiation dose of prospective gating group was 2.71 ± 0.67 mSv (range, 1.67-3.59 mSv), which was significantly lower than that of the retrospective group (p < 0.001). Conclusion: Prospective CT angiography can achieve lower radiation dose than that of low-dose retrospective CT angiography, with preserved image quality.

Prospective ECG triggering versus low-dose retrospective ECG-gated 128-channel CT coronary angiography: comparison of image quality and radiation dose

Energy Technology Data Exchange (ETDEWEB)

Feng, Q.; Yin, Y.; Hua, X.; Zhu, R.; Hua, J. [Department of Radiology, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai (China); Xu, J., E-mail: xujianr@hotmail.co [Department of Radiology, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai (China)

2010-10-15

Aim: To evaluate image quality and radiation dose for 128-detector prospective electrocardiogram (ECG)-gated computed tomography coronary angiography (CTCA) compared with a low-dose retrospective ECG-gated imaging protocol. Materials and methods: Thirty-one and 47 patients suspected of having coronary artery disease were enrolled into groups examined using prospective and low-dose retrospective ECG-gated CT protocols respectively. All examinations were performed on a 128-detector CT system (Definition AS, Siemens Healthcare, Forchheim, Germany). Prospective CTCA was performed using following parameters: tube voltage 100 kV; tube current 205 mAs; centre of acquisition window 70% of the RR interval. The tube current for low-dose retrospective ECG-gated CTCA was full dose during 40-70% of the RR interval and partial dose for the rest of RR interval. The pitch varied between 0.2 and 0.5 depending on heart rate and patient size. Image quality of coronary arteries was evaluated using a four-point grading scale. The signal-to-noise ratios (SNRs) of enhanced arteries and myocardium were also measured, corresponding contrast-to-noise ratios (CNRs) were calculated, and the radiation doses received were recorded. Results: There was a significant difference in the image quality scores between the retrospective and prospective gating protocols (Chi-square = 15.331, p = 0.009). There was no significant difference between the SNRs of the contrasted artery and myocardium in these two groups, but the CNRs were increased in the prospective group. The mean radiation dose of prospective gating group was 2.71 {+-} 0.67 mSv (range, 1.67-3.59 mSv), which was significantly lower than that of the retrospective group (p < 0.001). Conclusion: Prospective CT angiography can achieve lower radiation dose than that of low-dose retrospective CT angiography, with preserved image quality.

Development of a portable Linux-based ECG measurement and monitoring system.

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Tan, Tan-Hsu; Chang, Ching-Su; Huang, Yung-Fa; Chen, Yung-Fu; Lee, Cheng

2011-08-01

This work presents a portable Linux-based electrocardiogram (ECG) signals measurement and monitoring system. The proposed system consists of an ECG front end and an embedded Linux platform (ELP). The ECG front end digitizes 12-lead ECG signals acquired from electrodes and then delivers them to the ELP via a universal serial bus (USB) interface for storage, signal processing, and graphic display. The proposed system can be installed anywhere (e.g., offices, homes, healthcare centers and ambulances) to allow people to self-monitor their health conditions at any time. The proposed system also enables remote diagnosis via Internet. Additionally, the system has a 7-in. interactive TFT-LCD touch screen that enables users to execute various functions, such as scaling a single-lead or multiple-lead ECG waveforms. The effectiveness of the proposed system was verified by using a commercial 12-lead ECG signal simulator and in vivo experiments. In addition to its portability, the proposed system is license-free as Linux, an open-source code, is utilized during software development. The cost-effectiveness of the system significantly enhances its practical application for personal healthcare.

A low-power portable ECG sensor interface with dry electrodes

International Nuclear Information System (INIS)

Pu Xiaofei; Wan Lei; Zhang Hui; Qin Yajie; Hong Zhiliang

2013-01-01

This paper describes a low-power portable sensor interface dedicated to sensing and processing electrocardiogram (ECG) signals. Dry electrodes were employed in this ECG sensor, which eliminates the need of conductive gel and avoids complicated and mandatory skin preparation before electrode attachment. This ECG sensor system consists of two ICs, an analog front-end (AFE) and a successive approximation register analog-to-digital converter (SAR ADC) containing a relaxation oscillator. This proposed design was fabricated in a 0.18 μm 1P6M standard CMOS process. The AFE for extracting the biopotential signals is essential in this ECG sensor. In measurements, the AFE obtains a mid-band gain of 45 dB, a bandwidth from 0.6 to 160 Hz, and a total input referred noise of 2.8 μV rms while consuming 1 μW from the 1.8 V supply. The noise efficiency factor (NEF) of our design is 3.4. After conditioning, the amplified ECG signal is digitized by a 12-bit SAR ADC with 61.8 dB SNDR and 220 fJ/conversion-step. Finally, a complete ECG sensor interface with three dry copper electrodes is demonstrated in real-word setting, showing successful recordings of a capture ECG waveform. (semiconductor integrated circuits)

The morphological classification of heartbeats as dominant and non-dominant in ECG signals

International Nuclear Information System (INIS)

Chiarugi, Franco; Emmanouilidou, Dimitra; Tsamardinos, Ioannis

2010-01-01

Surface electrocardiography (ECG) is the art of analyzing the heart's electrical activity by applying electrodes to certain positions on the body and measuring potentials at the body surface resulting from this electrical activity. Usually, significant clinical information can be obtained from analysis of the dominant beat morphology. In this respect, identification of the dominant beats and their averaging can be very helpful, allowing clinicians to carry out the measurement of amplitudes and intervals on a beat much cleaner from noise than a generic beat selected from the entire ECG recording. In this paper a standard clustering algorithm for the morphological grouping of heartbeats has been analyzed based on K-means, different signal representations, distance metrics and validity indices. The algorithm has been tested on all the records of the MIT-BIH Arrhythmia Database (MIT-BIH AD) obtaining satisfying performances in terms of averaged dominant beat estimation, but the results have not been fully satisfactory in terms of sensitivity and specificity. In order to improve the clustering accuracy, an ad hoc algorithm based on a two-phase decision tree, which integrates additional specific knowledge related to the ECG domain, has been implemented. Similarity features extracted from every beat have been used in the decision trees for the identification of different morphological classes of ECG beats. The results, in terms of dominant beat discrimination, have been evaluated on all annotated beats of the MIT-BIH AD with sensitivity = 99.05%, specificity = 93.94%, positive predictive value = 99.32% and negative predictive value = 91.69%. Further tests have shown a very slight decrement of the performances on all detected beats of the same database using an already published QRS detector, demonstrating the validity of the algorithm in real unsupervised clustering situations where annotated beat positions are not available but beats are detected with a high

ECG telemetry in conscious guinea pigs.

Science.gov (United States)

Ruppert, Sabine; Vormberge, Thomas; Igl, Bernd-Wolfgang; Hoffmann, Michael

2016-01-01

During preclinical drug development, monitoring of the electrocardiogram (ECG) is an important part of cardiac safety assessment. To detect potential pro-arrhythmic liabilities of a drug candidate and for internal decision-making during early stage drug development an in vivo model in small animals with translatability to human cardiac function is required. Over the last years, modifications/improvements regarding animal housing, ECG electrode placement, and data evaluation have been introduced into an established model for ECG recordings using telemetry in conscious, freely moving guinea pigs. Pharmacological validation using selected reference compounds affecting different mechanisms relevant for cardiac electrophysiology (quinidine, flecainide, atenolol, dl-sotalol, dofetilide, nifedipine, moxifloxacin) was conducted and findings were compared with results obtained in telemetered Beagle dogs. Under standardized conditions, reliable ECG data with low variability allowing largely automated evaluation were obtained from the telemetered guinea pig model. The model is sensitive to compounds blocking cardiac sodium channels, hERG K(+) channels and calcium channels, and appears to be even more sensitive to β-blockers as observed in dogs at rest. QT interval correction according to Bazett and Sarma appears to be appropriate methods in conscious guinea pigs. Overall, the telemetered guinea pig is a suitable model for the conduct of early stage preclinical ECG assessment. Copyright © 2016 Elsevier Inc. All rights reserved.

Src-family kinases negatively regulate NFAT signaling in resting human T cells.

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Alan Baer

Full Text Available T cell signaling is required for activation of both natural and therapeutic T cells including chimeric antigen receptor (CAR T cells. Identification of novel factors and pathways regulating T cell signaling may aid in development of effective T cell therapies. In resting human T cells, the majority of Src-family of tyrosine kinases (SFKs are inactive due to phosphorylation of a conserved carboxy-terminal tyrosine residue. Recently, a pool of enzymatically active SFKs has been identified in resting T cells; however, the significance of these is incompletely understood. Here, we characterized the role of active SFKs in resting human T cells. Pharmacologic inhibition of active SFKs enhanced distal TCR signaling as measured by IL-2 release and CD25 surface expression following TCR-independent activation. Mechanistically, inhibition of the active pool of SFKs induced nuclear translocation of NFAT1, and enhanced NFAT1-dependent signaling in resting T cells. The negative regulation of NFAT1 signaling was in part mediated by the Src-kinase Lck as human T cells lacking Lck had increased levels of nuclear NFAT1 and demonstrated enhanced NFAT1-dependent gene expression. Inhibition of active SFKs in resting primary human T cells also increased nuclear NFAT1 and enhanced NFAT1-dependent signaling. Finally, the calcineurin inhibitor FK506 and Cyclosporin A reversed the effect of SFKs inhibition on NFAT1. Together, these data identified a novel role of SFKs in preventing aberrant NFAT1 activation in resting T cells, and suggest that maintaining this pool of active SFKs in therapeutic T cells may increase the efficacy of T cell therapies.

Portable ECG design and application based on wireless sensor network

Directory of Open Access Journals (Sweden)

Gül Fatma TÜRKER

2016-05-01

Full Text Available In this study, in order to follow the heart signals of patients that needs to be monitored instantly and continuously without mobility restrictions, a portable electrocardiogram circuit is designed. After performing the detection, upgrading, cleaning and digitizing of ECG signal received from patient via disposable electrodes, ECG signals was performed that transmit to a central node with Wireless Sensor Network (WSN based on ZigBee 802.11.4 standard. Central node is connected to the serial port of a computer. Received data from the central node is processed on computer and continuous flow graph is obtained. The obligation to use wires for tracing patients’ ECG has been removed with this portable system. As it can be seen in this study, thanks to WSN’s property of forming network by itself and its augmentable loop property, the restrain of ECG signals to reach far away distances can be surmounted. The transmission of biological signals with WSN will light on many studies that follow of patients from a distance.

Energy Analysis of Decoders for Rakeness-Based Compressed Sensing of ECG Signals.

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Pareschi, Fabio; Mangia, Mauro; Bortolotti, Daniele; Bartolini, Andrea; Benini, Luca; Rovatti, Riccardo; Setti, Gianluca

2017-12-01

In recent years, compressed sensing (CS) has proved to be effective in lowering the power consumption of sensing nodes in biomedical signal processing devices. This is due to the fact the CS is capable of reducing the amount of data to be transmitted to ensure correct reconstruction of the acquired waveforms. Rakeness-based CS has been introduced to further reduce the amount of transmitted data by exploiting the uneven distribution to the sensed signal energy. Yet, so far no thorough analysis exists on the impact of its adoption on CS decoder performance. The latter point is of great importance, since body-area sensor network architectures may include intermediate gateway nodes that receive and reconstruct signals to provide local services before relaying data to a remote server. In this paper, we fill this gap by showing that rakeness-based design also improves reconstruction performance. We quantify these findings in the case of ECG signals and when a variety of reconstruction algorithms are used either in a low-power microcontroller or a heterogeneous mobile computing platform.

Manifold learning based ECG-free free-breathing cardiac CINE MRI.

Science.gov (United States)

Usman, Muhammad; Atkinson, David; Kolbitsch, Christoph; Schaeffter, Tobias; Prieto, Claudia

2015-06-01

To present and validate a manifold learning (ML)-based method that can estimate both cardiac and respiratory navigator signals from electrocardiogram (ECG)-free free-breathing cardiac magnetic resonance imaging (MRI) data to achieve self-gated retrospective CINE reconstruction. In this work the use of the ML method is demonstrated for 2D cardiac CINE to achieve both cardiac and respiratory self-gating without the need of an external navigator or ECG signal. This is achieved by sequentially applying ML to two sets of retrospectively reconstructed real-time images with differing temporal resolutions. A 1D cardiac signal is estimated by applying ML to high temporal resolution real-time images reconstructed from the acquired data. Using the estimated cardiac signal, a 1D respiratory signal was obtained by applying the ML method to low temporal resolution images reconstructed from the same acquired data for each cardiac cycle. Data were acquired in five volunteers with a 2D golden angle radial trajectory in a balanced steady-state free precession (b-SSFP) acquisition. The accuracy of the estimated cardiac signal was calculated as the standard deviation of the temporal difference between the estimated signal and the recorded ECG. The correlation between the estimated respiratory signal and standard pencil beam navigator signal was evaluated. Gated CINE reconstructions (20 cardiac phases per cycle, temporal resolution ∼30 msec) using the estimated cardiac and respiratory signals were qualitatively compared against conventional ECG-gated breath-hold CINE acquisitions. Accurate cardiac signals were estimated with the proposed method, with an error standard deviation in comparison to ECG lower than 20 msec. Respiratory signals estimated with the proposed method achieved a mean cross-correlation of 94% with respect to standard pencil beam navigator signals. Good quality visual scores of 2.80 ± 0.45 (scores from 0, bad, to 4, excellent quality) were observed for the

Influence of Mobile Phones on the Quality of ECG Signal Acquired by Medical Devices

Science.gov (United States)

Buczkowski, T.; Janusek, D.; Zavala-Fernandez, H.; Skrok, M.; Kania, M.; Liebert, A.

2013-10-01

Health aspects of the use of radiating devices, like mobile phones, are still a public concern. Stand-alone electrocardiographic systems and those built-in, more sophisticated, medical devices have become a standard tool used in everyday medical practice. GSM mobile phones might be a potential source of electromagnetic interference (EMI) which may affect reliability of medical appliances. Risk of such event is particularly high in places remote from GSM base stations in which the signal received by GSM mobile phone is weak. In such locations an increase in power of transmitted radio signal is necessary to enhance quality of the communication. In consequence, the risk of interference of electronic devices increases because of the high level of EMI. In the present paper the spatial, temporal, and spectral characteristics of the interference have been examined. The influence of GSM mobile phone on multilead ECG recordings was studied. It was observed that the electrocardiographic system was vulnerable to the interference generated by the GSM mobile phone working with maximum transmit power and in DTX mode when the device was placed in a distance shorter than 7.5 cm from the ECG electrode located on the surface of the chest. Negligible EMI was encountered at any longer distance.

ECG acquisition and automated remote processing

CERN Document Server

Gupta, Rajarshi; Bera, Jitendranath

2014-01-01

The book is focused on the area of remote processing of ECG in the context of telecardiology, an emerging area in the field of Biomedical Engineering Application. Considering the poor infrastructure and inadequate numbers of physicians in rural healthcare clinics in India and other developing nations, telemedicine services assume special importance. Telecardiology, a specialized area of telemedicine, is taken up in this book considering the importance of cardiac diseases, which is prevalent in the population under discussion. The main focus of this book is to discuss different aspects of ECG acquisition, its remote transmission and computerized ECG signal analysis for feature extraction. It also discusses ECG compression and application of standalone embedded systems, to develop a cost effective solution of a telecardiology system.

A Novel Approach to ECG Classification Based upon Two-Layered HMMs in Body Sensor Networks

Science.gov (United States)

Liang, Wei; Zhang, Yinlong; Tan, Jindong; Li, Yang

2014-01-01

This paper presents a novel approach to ECG signal filtering and classification. Unlike the traditional techniques which aim at collecting and processing the ECG signals with the patient being still, lying in bed in hospitals, our proposed algorithm is intentionally designed for monitoring and classifying the patient's ECG signals in the free-living environment. The patients are equipped with wearable ambulatory devices the whole day, which facilitates the real-time heart attack detection. In ECG preprocessing, an integral-coefficient-band-stop (ICBS) filter is applied, which omits time-consuming floating-point computations. In addition, two-layered Hidden Markov Models (HMMs) are applied to achieve ECG feature extraction and classification. The periodic ECG waveforms are segmented into ISO intervals, P subwave, QRS complex and T subwave respectively in the first HMM layer where expert-annotation assisted Baum-Welch algorithm is utilized in HMM modeling. Then the corresponding interval features are selected and applied to categorize the ECG into normal type or abnormal type (PVC, APC) in the second HMM layer. For verifying the effectiveness of our algorithm on abnormal signal detection, we have developed an ECG body sensor network (BSN) platform, whereby real-time ECG signals are collected, transmitted, displayed and the corresponding classification outcomes are deduced and shown on the BSN screen. PMID:24681668

A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm

Directory of Open Access Journals (Sweden)

Bohui Zhu

2013-01-01

Full Text Available This paper presents a novel maximum margin clustering method with immune evolution (IEMMC for automatic diagnosis of electrocardiogram (ECG arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm. Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy. Compared with K-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias.

Performance evaluation of carbon black based electrodes for underwater ECG monitoring.

Science.gov (United States)

Reyes, Bersain A; Posada-Quintero, Hugo F; Bales, Justin R; Chon, Ki H

2014-01-01

Underwater electrocardiogram (ECG) monitoring currently uses Ag/AgCl electrodes and requires sealing of the electrodes to avoid water intrusion, but this procedure is time consuming and often results in severe irritations or even tearing of the skin. To alleviate these problems, our research team developed hydrophobic electrodes comprised of a mixture of carbon black powder (CB) and polydimethylsiloxane (PDMS) that provide all morphological waveforms without distortion of an ECG signal for dry and water-immersed conditions. Performance comparison of CB/PDMS electrodes to adhesive Ag/AgCl hydrogel electrodes was carried out in three different scenarios which included recordings from a dry surface, water immersion, and post-water immersion conditions. CB/PDMS electrodes were able to acquire ECG signals highly correlated with those from adhesive Ag/AgCl electrodes during all conditions. Statistical reduction in ECG amplitude (pelectrodes when compared to Ag/AgCl electrodes sealed with their waterproof adhesive tape. Besides this reduction readability of the recordings was not obscured and all morphological waveforms of the ECG signal were discernible. The advantages of our CB/PDMS electrodes are that they are reusable, can be fabricated economically, and most importantly, high-fidelity underwater ECG signals can be acquired without relying on the heavy use of waterproof sealing.

A real time ECG signal processing application for arrhythmia detection on portable devices

Science.gov (United States)

Georganis, A.; Doulgeraki, N.; Asvestas, P.

2017-11-01

Arrhythmia describes the disorders of normal heart rate, which, depending on the case, can even be fatal for a patient with severe history of heart disease. The purpose of this work is to develop an application for heart signal visualization, processing and analysis in Android portable devices e.g. Mobile phones, tablets, etc. The application is able to retrieve the signal initially from a file and at a later stage this signal is processed and analysed within the device so that it can be classified according to the features of the arrhythmia. In the processing and analysing stage, different algorithms are included among them the Moving Average and Pan Tompkins algorithm as well as the use of wavelets, in order to extract features and characteristics. At the final stage, testing is performed by simulating our application in real-time records, using the TCP network protocol for communicating the mobile with a simulated signal source. The classification of ECG beat to be processed is performed by neural networks.

Designing ECG-based physical unclonable function for security of wearable devices.

Science.gov (United States)

Shihui Yin; Chisung Bae; Sang Joon Kim; Jae-Sun Seo

2017-07-01

As a plethora of wearable devices are being introduced, significant concerns exist on the privacy and security of personal data stored on these devices. Expanding on recent works of using electrocardiogram (ECG) as a modality for biometric authentication, in this work, we investigate the possibility of using personal ECG signals as the individually unique source for physical unclonable function (PUF), which eventually can be used as the key for encryption and decryption engines. We present new signal processing and machine learning algorithms that learn and extract maximally different ECG features for different individuals and minimally different ECG features for the same individual over time. Experimental results with a large 741-subject in-house ECG database show that the distributions of the intra-subject (same person) Hamming distance of extracted ECG features and the inter-subject Hamming distance have minimal overlap. 256-b random numbers generated from the ECG features of 648 (out of 741) subjects pass the NIST randomness tests.

Comparative study of measured heart cycle phase durations: standard lead ECG versus original ascending aorta lead ECG

Directory of Open Access Journals (Sweden)

Sergey V. Kolmakov

2012-11-01

Full Text Available Aims The present paper aims at evaluating the existing difference in duration measurements of the same heart cycle phases in the standard V3, V4, V5, V6 leads ECG versus original HDA lead ECG of the ascending aorta. Materials and methods The method of changing the filter pass band is used. Its essence is in artificial changing of the conditions of the signal recording carrying the informative indications of the initial information used in hemodynamic equations. The method also enables calculating the percentage deviation from the initial values. The principle of balance of the blood volume entering the heart and the blood volume leaving the heart is used to trace the minimal deviations and their respective recording conditions. Results In each of the V3, V4, V5, V6 ECG leads durations of the same phases have different values. The values measured on the ECG of the ascending aorta and those measured using the standard V4 ECG lead differ slightly. Conclusion For heart cycle phase analysis it is possible to use only the ECG of the ascending aorta and V4 standard lead ECG. Using conventional standard ECG leads causes an error up to 25%.

Artifact reduction in maternal abdominal ECG recordings for fetal ECG estimation.

NARCIS (Netherlands)

Vullings, R.; Peters, C.H.L.; Mischi, M.; Sluijter, R.J.; Oei, S.G.; Bergmans, J.W.M.

2010-01-01

Monitoring the fetal electrocardiogram (1ECG) is currently one of the most promising methods to assess fetal health. However, the main problem associated with this method is that the signals recorded from the maternal abdomen are affected by noise and interferences: the maternal electrocardiogram

Parametric modelling of cardiac system multiple measurement signals: an open-source computer framework for performance evaluation of ECG, PCG and ABP event detectors.

Science.gov (United States)

Homaeinezhad, M R; Sabetian, P; Feizollahi, A; Ghaffari, A; Rahmani, R

2012-02-01

The major focus of this study is to present a performance accuracy assessment framework based on mathematical modelling of cardiac system multiple measurement signals. Three mathematical algebraic subroutines with simple structural functions for synthetic generation of the synchronously triggered electrocardiogram (ECG), phonocardiogram (PCG) and arterial blood pressure (ABP) signals are described. In the case of ECG signals, normal and abnormal PQRST cycles in complicated conditions such as fascicular ventricular tachycardia, rate dependent conduction block and acute Q-wave infarctions of inferior and anterolateral walls can be simulated. Also, continuous ABP waveform with corresponding individual events such as systolic, diastolic and dicrotic pressures with normal or abnormal morphologies can be generated by another part of the model. In addition, the mathematical synthetic PCG framework is able to generate the S4-S1-S2-S3 cycles in normal and in cardiac disorder conditions such as stenosis, insufficiency, regurgitation and gallop. In the PCG model, the amplitude and frequency content (5-700 Hz) of each sound and variation patterns can be specified. The three proposed models were implemented to generate artificial signals with varies abnormality types and signal-to-noise ratios (SNR), for quantitative detection-delineation performance assessment of several ECG, PCG and ABP individual event detectors designed based on the Hilbert transform, discrete wavelet transform, geometric features such as area curve length (ACLM), the multiple higher order moments (MHOM) metric, and the principal components analysed geometric index (PCAGI). For each method the detection-delineation operating characteristics were obtained automatically in terms of sensitivity, positive predictivity and delineation (segmentation) error rms and checked by the cardiologist. The Matlab m-file script of the synthetic ECG, ABP and PCG signal generators are available in the Appendix.

A Novel 12-Lead ECG T-Shirt with Active Electrodes

Directory of Open Access Journals (Sweden)

Anna Boehm

2016-11-01

Full Text Available We developed an ECG T-shirt with a portable recorder for unobtrusive and long-term multichannel ECG monitoring with active electrodes. A major drawback of conventional 12-lead ECGs is the use of adhesive gel electrodes, which are uncomfortable during long-term application and may even cause skin irritations and allergic reactions. Therefore, we integrated comfortable patches of conductive textile into the ECG T-shirt in order to replace the adhesive gel electrodes. In order to prevent signal deterioration, as reported for other textile ECG systems, we attached active circuits on the outside of the T-shirt to further improve the signal quality of the dry electrodes. Finally, we validated the ECG T-shirt against a commercial Holter ECG with healthy volunteers during phases of lying down, sitting, and walking. The 12-lead ECG was successfully recorded with a resulting mean relative error of the RR intervals of 0.96% and mean coverage of 96.6%. Furthermore, the ECG waves of the 12 leads were analyzed separately and showed high accordance. The P-wave had a correlation of 0.703 for walking subjects, while the T-wave demonstrated lower correlations for all three scenarios (lying: 0.817, sitting: 0.710, walking: 0.403. The other correlations for the P, Q, R, and S-waves were all higher than 0.9. This work demonstrates that our ECG T-shirt is suitable for 12-lead ECG recordings while providing a higher level of comfort compared with a commercial Holter ECG.

ECG movement artefacts can be greatly reduced with the aid of a movement absorbing device

DEFF Research Database (Denmark)

Harrison, Adrian Paul; Wandall, Kirsten; Thorball, Jørgen

2007-01-01

Accurate ECG signal analysis can be confounded by electric lead, and/or electrode movements varying in origin from, for example, hiccups, tremor or patient restlessness. ECG signals recorded using either a conventional electrode holder or with the aid of an electrode holder capable of absorbing...... movement artefacts, were measured on a healthy human subject. Results show a greatly improved stability of the ECG signal recorded using an electrode holder capable of absorbing movement artefacts during periods of lead disturbance, and highlight the movement artefacts that develop when the recording lead...... of a conventional ECG electrode holder is tugged or pulled during theperiod of monitoring. It is concluded that the new design of ECG electrode holder will not only enable clearer signal recordings for clinical assessment, but will reduce the ECG artefacts associated with the transportation of patients, and may...

A novel ECG data compression method based on adaptive Fourier decomposition

Science.gov (United States)

Tan, Chunyu; Zhang, Liming

2017-12-01

This paper presents a novel electrocardiogram (ECG) compression method based on adaptive Fourier decomposition (AFD). AFD is a newly developed signal decomposition approach, which can decompose a signal with fast convergence, and hence reconstruct ECG signals with high fidelity. Unlike most of the high performance algorithms, our method does not make use of any preprocessing operation before compression. Huffman coding is employed for further compression. Validated with 48 ECG recordings of MIT-BIH arrhythmia database, the proposed method achieves the compression ratio (CR) of 35.53 and the percentage root mean square difference (PRD) of 1.47% on average with N = 8 decomposition times and a robust PRD-CR relationship. The results demonstrate that the proposed method has a good performance compared with the state-of-the-art ECG compressors.

A Novel Approach to ECG Classification Based upon Two-Layered HMMs in Body Sensor Networks

Directory of Open Access Journals (Sweden)

Wei Liang

2014-03-01

Full Text Available This paper presents a novel approach to ECG signal filtering and classification. Unlike the traditional techniques which aim at collecting and processing the ECG signals with the patient being still, lying in bed in hospitals, our proposed algorithm is intentionally designed for monitoring and classifying the patient’s ECG signals in the free-living environment. The patients are equipped with wearable ambulatory devices the whole day, which facilitates the real-time heart attack detection. In ECG preprocessing, an integral-coefficient-band-stop (ICBS filter is applied, which omits time-consuming floating-point computations. In addition, two-layered Hidden Markov Models (HMMs are applied to achieve ECG feature extraction and classification. The periodic ECG waveforms are segmented into ISO intervals, P subwave, QRS complex and T subwave respectively in the first HMM layer where expert-annotation assisted Baum-Welch algorithm is utilized in HMM modeling. Then the corresponding interval features are selected and applied to categorize the ECG into normal type or abnormal type (PVC, APC in the second HMM layer. For verifying the effectiveness of our algorithm on abnormal signal detection, we have developed an ECG body sensor network (BSN platform, whereby real-time ECG signals are collected, transmitted, displayed and the corresponding classification outcomes are deduced and shown on the BSN screen.

Performance Analysis of Ten Common QRS Detectors on Different ECG Application Cases

Directory of Open Access Journals (Sweden)

Feifei Liu

2018-01-01

Full Text Available A systematical evaluation work was performed on ten widely used and high-efficient QRS detection algorithms in this study, aiming at verifying their performances and usefulness in different application situations. Four experiments were carried on six internationally recognized databases. Firstly, in the test of high-quality ECG database versus low-quality ECG database, for high signal quality database, all ten QRS detection algorithms had very high detection accuracy (F1 >99%, whereas the F1 results decrease significantly for the poor signal-quality ECG signals (all 95% except RS slope algorithm with 94.24% on normal ECG database and 94.44% on arrhythmia database. Thirdly, for the paced rhythm ECG database, all ten algorithms were immune to the paced beats (>94% except the RS slope method, which only output a low F1 result of 78.99%. At last, the detection accuracies had obvious decreases when dealing with the dynamic telehealth ECG signals (all <80% except OKB algorithm with 80.43%. Furthermore, the time costs from analyzing a 10 s ECG segment were given as the quantitative index of the computational complexity. All ten algorithms had high numerical efficiency (all <4 ms except RS slope (94.07 ms and sixth power algorithms (8.25 ms. And OKB algorithm had the highest numerical efficiency (1.54 ms.

ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

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Kora, Padmavathi; Sri Rama Krishna, K.

2016-12-01

Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

Prevalence and associated factors of resting electrocardiogram abnormalities among systemic lupus erythematosus patients without cardiovascular disease

OpenAIRE

Al Rayes, Hanan; Harvey, Paula J.; Gladman, Dafna D.; Su, Jiandong; Sabapathy, Arthy; Urowitz, Murray B.; Touma, Zahi

2017-01-01

Background Electrocardiogram (ECG) cardiovascular disease (CVD) abnormalities (ECG-CVD) are predictive of subsequent CVD events in the general population. Systemic lupus erythematosus (SLE) patients are vulnerable to CVD. We aimed to determine the prevalence of ECG-CVD in SLE patients and to examine the risk factors associated with ECG-CVD. Methods A 12-lead resting supine ECG was performed on consecutive adult patients attending the clinic. One cardiologist interpreted the ECGs. ECG-CVD were...

ECG-manifest and ECG-silent dipyridamole technetium-99m sestamibi SPET perfusion defects in patients with ischaemic heart disease

International Nuclear Information System (INIS)

Galli, M.; Marcassa, C.; Bosimini, E.; Zoccarato, O.; Comazzi, F.; Giannuzzi, P.

1997-01-01

To investigate the relationship between ECG changes and perfusion abnormalities, body surface maps were recorded during dipyridamole infusion in 55 subjects (11 normals and 44 patients with ischaemic heart disease) undergoing dipyridamole technetium-99m sestamibi single-photon emission tomography (SPET). All had a normal resting ECG. The extent and severity of the sestamibi defect were quantified. New negative areas in the isointegral maps and rest-dipyridamole map differences >2 SD from normal limits were considered abnormal. After dipyridamole in normals, neither perfusion defects nor ≥1 mm ST segment depression on 12-lead ECG nor new negative areas in isointegral maps occurred. In patients, dipyridamole induced new perfusion defects in 35 (80%) but ST segment depression in only 18 (41%, P<0.001). Of the 35 patients with perfusion defects, 17 (49%, group 1) showed ST segment depression, while the other 18 (51%, group 2) did not. Abnormal body surface maps were found in 100% of group 1 and 88% of group 2 patients (NS). In group 1, the provoked hypoperfusion was of greater extent (P=0.007) and severity (P=0.01) and the onset of map abnormalities was significantly earlier (P<0.001) than in group 2; time to map abnormalities was also significantly shorter than time to ST segment depression (P=0.01). In the 35 patients with complete scintigraphic, body map and angiographic data, the severity of reversible perfusion defect proved to be the strongest correlate of ST segment depression upon logistic regression analysis. Thus, sestamibi SPET abnormalities after dipyridamole are almost always associated with electrical changes on body surface maps, suggesting myocardial ischaemia as their cause. The much less common 12-lead ECG changes are slower to appear and reflect a more severe hypoperfusion. (orig./MG). With 5 figs., 4 tabs

Early detection of myocardial ischaemia in the emergency department by rest or exercise 99mTc tracer myocardial SPET in patients with chest pain and non-diagnostic ECG

International Nuclear Information System (INIS)

Conti, A.; Paladini, B.; Francois, C.; Grifoni, S.; Berni, G.; Gallini, C.; Costanzo, E.; Ferri, P.; Matteini, M.; Pieroni, C.; Migliorini, A.; Antoniucci, D.

2001-01-01

Chest pain (CP) represents a frequent reason for presentation at the emergency department (ED). A large proportion of patients have non-diagnostic ECG on presentation, and in many cases several hours have elapsed since onset of symptoms. Acute rest myocardial scintigraphy (rest SPET) has been shown to have a relevant role in the detection of patients at risk for coronary events, but its sensitivity and negative predictive value are optimal only within the first 3 h following onset of symptoms. In those with delayed presentation, exercise SPET alone, as a screening approach, appears more promising, but its feasibility and diagnostic role in the ED are still unresolved. A total of 231 consecutive patients with a recent-onset (<24 h) first episode of CP had a negative first-line work-up including ECG, troponins, creatine kinase-MB and echocardiography. These patients were considered at low risk for short-term coronary events. Patients were studied with rest SPET if they presented <3 h after onset of CP and exercise SPET if they presented after ≥3 h. The end-points of the study were detection of significant coronary artery disease (CAD) by angiography and major coronary events or cardiac death at 6 months. Eighty patients (35%) underwent rest SPET, while 151 (65%) underwent exercise SPET. Two of the 159 patients with negative SPET had evidence of critical CAD at 6-month follow-up (one patient in the rest SPET group and one in the exercise SPET group; P=NS). Of the 72 patients (31%) with a positive scan, 34 (15%) had documented CAD (16 patients in the rest SPET group and 18 in the exercise SPET group; P=NS). Sensitivity, specificity, accuracy and predictive value were not statistically different between the two groups. In conclusion, the accuracy of exercise SPET in patients with CP and delayed presentation to the ED is comparable to that of validated rest SPET in patients with early presentation. Owing to the high negative predictive value (99%), exercise SPET is

A capacitive ECG array with visual patient feedback.

Science.gov (United States)

Eilebrecht, Benjamin; Schommartz, Antje; Walter, Marian; Wartzek, Tobias; Czaplik, Michael; Leonhardt, Steffen

2010-01-01

Capacitive electrocardiogram (ECG) sensing is a promising technique for less constraining vital signal measurement and close to a commercial application. Even bigger trials testing the diagnostic significance were already done with single lead systems. Anyway, most applications to be found in research are limited to one channel and thus limited in its diagnostic relevance as only diseases coming along with a change of the heart rate can be diagnosed adequately. As a consequence the need for capacitive multi-channel ECGs combining the diagnostic relevance and the advantages of capacitive ECG sensing emerges. This paper introduces a capacitive ECG measurement system which allows the recording of standardized ECG leads according to Einthoven and Goldberger by means of an electrode array with nine electrodes.

Retrospectively ECG-gated multi-detector row CT of the chest: does ECG-gating improve three-dimensional visualization of the bronchial tree?

International Nuclear Information System (INIS)

Schertler, T.; Wildermuth, S.; Willmann, J.K.; Crook, D.W.; Marincek, B.; Boehm, T.

2004-01-01

Purpose: To determine the impact of retrospectively ECG-gated multi-detector row CT (MDCT) on three-dimensional (3D) visualization of the bronchial tree and virtual bronchoscopy (VB) as compared to non-ECG-gated data acquisition. Materials and Methods: Contrast-enhanced retrospectively ECG-gated and non-ECG-gated MDCT of the chest was performed in 25 consecutive patients referred for assessment of coronary artery bypass grafts and pathology of the ascending aorta. ECG-gated MDCT data were reconstructed in diastole using an absolute reverse delay of -400 msec in all patients. In 10 patients additional reconstructions at -200 msec, -300 msec, and -500 msec prior to the R-wave were performed. Shaded surface display (SSD) and virtual bronchoscopy (VB) for visualization of the bronchial segments was performed with ECG-gated and non-ECG-gated MDCT data. The visualization of the bronchial tree underwent blinded scoring. Effective radiation dose and signal-to-noise ratio (SNR) for both techniques were compared. Results: There was no significant difference in visualizing single bronchial segments using ECG-gated compared to non-ECG-gated MDCT data. However, the total sum of scores for all bronchial segments visualized with non-ECG-gated MDCT was significantly higher compared to ECG-gated MDCT (P [de

Fetal ECG extraction using independent component analysis by Jade approach

Science.gov (United States)

Giraldo-Guzmán, Jader; Contreras-Ortiz, Sonia H.; Lasprilla, Gloria Isabel Bautista; Kotas, Marian

2017-11-01

Fetal ECG monitoring is a useful method to assess the fetus health and detect abnormal conditions. In this paper we propose an approach to extract fetal ECG from abdomen and chest signals using independent component analysis based on the joint approximate diagonalization of eigenmatrices approach. The JADE approach avoids redundancy, what reduces matrix dimension and computational costs. Signals were filtered with a high pass filter to eliminate low frequency noise. Several levels of decomposition were tested until the fetal ECG was recognized in one of the separated sources output. The proposed method shows fast and good performance.

The resting electrocardiogram of t. cruzi-infected rats

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Reinaldo B. Bestetti

1987-08-01

Full Text Available A total of 125 rats were infected with the Colômbia strain of T. cruzi (2000 parasites/g shortly after weaning. Of these, 58 survived the acute phase and were used in the present experiment. Twenty eight similar but not infected rats served as controls. All rats were submitted to the resting ECG When they were 6 months old. Classic and 3 precordial leads were employed in order to record the ECG as completely as possible. Electrocardiographic changes similar to those found in human chronic Chagas' heart disease and not previously described in this model were found in 44% of the T. cruzi-infected rats: left axis deviation (22%, right axis deviation (7%, lengthened and bizarre QRS complex (14% and abnormal J point elevation (3%. On the basis of these results, we believe that the resting ECG constitutes a valuable tool for studying experimental chronic Chagas' heart disease in rats.

Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery

Science.gov (United States)

Sivaraks, Haemwaan

2015-01-01

Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods. PMID:25688284

Measurement of ECG abnormalities and cardiovascular risk classification: a cohort study of primary care patients in the Netherlands

NARCIS (Netherlands)

de Groot, A.; Bots, M.L.; Rutten, F.H.; den Ruijter, H.M.; Numans, M.E.; Vaartjes, I.

2015-01-01

Background: GPs need accurate tools for cardiovascular (CV) risk assessment. Abnormalities in resting electrocardiograms (ECGs) relate to increased CV risk. Aim: To determine whether measurement of ECG abnormalities on top of established risk estimation (SCORE) improves CV risk classification in a

The Development of a Portable ECG Monitor Based on DSP

Science.gov (United States)

Nan, CHI Jian; Tao, YAN Yan; Meng Chen, LIU; Li, YANG

With the advent of global information, researches of Smart Home system are in the ascendant, the ECG real-time detection, and wireless transmission of ECG become more useful. In order to achieve the purpose we developed a portable ECG monitor which achieves the purpose of cardiac disease remote monitoring, and will be used in the physical and psychological disease surveillance in smart home system, we developed this portable ECG Monitor, based on the analysis of existing ECG Monitor, using TMS320F2812 as the core controller, which complete the signal collection, storage, processing, waveform display and transmission.

[Implementation of ECG Monitoring System Based on Internet of Things].

Science.gov (United States)

Lu, Liangliang; Chen, Minya

2015-11-01

In order to expand the capabilities of hospital's traditional ECG device and enhance medical staff's work efficiency, an ECG monitoring system based on internet of things is introduced. The system can monitor ECG signals in real time and analyze data using ECG sensor, PDA, Web servers, which embeds C language, Android systems, .NET, wireless network and other technologies. After experiments, it can be showed that the system has high reliability and stability and can bring the convenience to medical staffs.

From Pacemaker to Wearable: Techniques for ECG Detection Systems.

Science.gov (United States)

Kumar, Ashish; Komaragiri, Rama; Kumar, Manjeet

2018-01-11

With the alarming rise in the deaths due to cardiovascular diseases (CVD), present medical research scenario places notable importance on techniques and methods to detect CVDs. As adduced by world health organization, technological proceeds in the field of cardiac function assessment have become the nucleus and heart of all leading research studies in CVDs in which electrocardiogram (ECG) analysis is the most functional and convenient tool used to test the range of heart-related irregularities. Most of the approaches present in the literature of ECG signal analysis consider noise removal, rhythm-based analysis, and heartbeat detection to improve the performance of a cardiac pacemaker. Advancements achieved in the field of ECG segments detection and beat classification have a limited evaluation and still require clinical approvals. In this paper, approaches on techniques to implement on-chip ECG detector for a cardiac pacemaker system are discussed. Moreover, different challenges regarding the ECG signal morphology analysis deriving from medical literature is extensively reviewed. It is found that robustness to noise, wavelet parameter choice, numerical efficiency, and detection performance are essential performance indicators required by a state-of-the-art ECG detector. Furthermore, many algorithms described in the existing literature are not verified using ECG data from the standard databases. Some ECG detection algorithms show very high detection performance with the total number of detected QRS complexes. However, the high detection performance of the algorithm is verified using only a few datasets. Finally, gaps in current advancements and testing are identified, and the primary challenge remains to be implementing bullseye test for morphology analysis evaluation.

Spatiotemporal representation of cardiac vectorcardiogram (VCG signals

Directory of Open Access Journals (Sweden)

Yang Hui

2012-03-01

Full Text Available Abstract Background Vectorcardiogram (VCG signals monitor both spatial and temporal cardiac electrical activities along three orthogonal planes of the body. However, the absence of spatiotemporal resolution in conventional VCG representations is a major impediment for medical interpretation and clinical usage of VCG. This is especially so because time-domain features of 12-lead ECG, instead of both spatial and temporal characteristics of VCG, are widely used for the automatic assessment of cardiac pathological patterns. Materials and methods We present a novel representation approach that captures critical spatiotemporal heart dynamics by displaying the real time motion of VCG cardiac vectors in a 3D space. Such a dynamic display can also be realized with only one lead ECG signal (e.g., ambulatory ECG through an alternative lag-reconstructed ECG representation from nonlinear dynamics principles. Furthermore, the trajectories are color coded with additional dynamical properties of space-time VCG signals, e.g., the curvature, speed, octant and phase angles to enhance the information visibility. Results In this investigation, spatiotemporal VCG signal representation is used to characterize various spatiotemporal pathological patterns for healthy control (HC, myocardial infarction (MI, atrial fibrillation (AF and bundle branch block (BBB. The proposed color coding scheme revealed that the spatial locations of the peak of T waves are in the Octant 6 for the majority (i.e., 74 out of 80 of healthy recordings in the PhysioNet PTB database. In contrast, the peak of T waves from 31.79% (117/368 of MI subjects are found to remain in Octant 6 and the rest (68.21% spread over all other octants. The spatiotemporal VCG signal representation is shown to capture the same important heart characteristics as the 12-lead ECG plots and more. Conclusions Spatiotemporal VCG signal representation is shown to facilitate the characterization of space-time cardiac

Deployment of an Advanced Electrocardiographic Analysis (A-ECG) to Detect Cardiovascular Risk in Career Firefighters

Science.gov (United States)

Dolezal, B. A.; Storer, T. W.; Abrazado, M.; Watne, R.; Schlegel, T. T.; Batalin, M.; Kaiser, W.; Smith, D. L.; Cooper, C. B.

2011-01-01

INTRODUCTION: Sudden cardiac death is the leading cause of line of duty death among firefighters, accounting for approximately 45% of fatalities annually. Firefighters perform strenuous muscular work while wearing heavy, encapsulating personal protective equipment in high ambient temperatures, under chaotic and emotionally stressful conditions. These factors can precipitate sudden cardiac events like myocardial infarction, serious dysrhythmias, or cerebrovascular accidents in firefighters with underlying cardiovascular disease. PURPOSE: The purpose of this study was to deploy and then evaluate the contribution of resting advanced ECG (A-ECG) in addition to other screening tools (family history, lipid profiles, and cardiopulmonary exercise tests, XT) in assessment of an individual fs cardiac risk profile. METHODS: Forty-four career firefighters were recruited to perform comprehensive baseline assessments including tests of aerobic performance, fasting lipids and glucose. Five-min resting 12-lead A-ECGs were obtained in a subset of firefighters (n=21) and transmitted over a secure networked system to a NASA physician collaborator. Using myocardial perfusion and other imaging as the gold standard, A-ECG scoring has been proven useful in accurately identifying a number of cardiac pathologies including coronary artery disease (CAD), left ventricular hypertrophy, hypertrophic cardiomyopathy, and non-ischemic and ischemic cardiomyopathy. RESULTS: Subjects f mean (SD) age was 43 (8) years, weight 91 (13) kg, and BMI 28 (3) kg/m2. Fifty-one percent of subjects had .3 cardiovascular risk factors. One subject had ST depression on XT ECG, at least one positive A-ECG score for CAD, and documented CAD based on cardiology referral. While all other subjects, including those with fewer risk factors, higher aerobic fitness, and normal exercise ECGs, were classified as healthy by A-ECG, there was no trend for association between risk factors and any of 20 A-ECG parameters in the

Performance of human body communication-based wearable ECG with capacitive coupling electrodes.

Science.gov (United States)

Sakuma, Jun; Anzai, Daisuke; Wang, Jianqing

2016-09-01

Wearable electrocardiogram (ECG) is attracting much attention in daily healthcare applications, and human body communication (HBC) technology provides an evident advantage in making the sensing electrodes of ECG also working for transmission through the human body. In view of actual usage in daily life, however, non-contact electrodes to the human body are desirable. In this Letter, the authors discussed the ECG circuit structure in the HBC-based wearable ECG for removing the common mode noise when employing non-contact capacitive coupling electrodes. Through the comparison of experimental results, they have shown that the authors' proposed circuit structure with the third electrode directly connected to signal ground can provide an effect on common mode noise reduction similar to the usual drive-right-leg circuit, and a sufficiently good acquisition performance of ECG signals.

Transform Domain Robust Variable Step Size Griffiths' Adaptive Algorithm for Noise Cancellation in ECG

Science.gov (United States)

Hegde, Veena; Deekshit, Ravishankar; Satyanarayana, P. S.

2011-12-01

The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts or noise. Noise severely limits the utility of the recorded ECG and thus needs to be removed, for better clinical evaluation. In the present paper a new noise cancellation technique is proposed for removal of random noise like muscle artifact from ECG signal. A transform domain robust variable step size Griffiths' LMS algorithm (TVGLMS) is proposed for noise cancellation. For the TVGLMS, the robust variable step size has been achieved by using the Griffiths' gradient which uses cross-correlation between the desired signal contaminated with observation or random noise and the input. The algorithm is discrete cosine transform (DCT) based and uses symmetric property of the signal to represent the signal in frequency domain with lesser number of frequency coefficients when compared to that of discrete Fourier transform (DFT). The algorithm is implemented for adaptive line enhancer (ALE) filter which extracts the ECG signal in a noisy environment using LMS filter adaptation. The proposed algorithm is found to have better convergence error/misadjustment when compared to that of ordinary transform domain LMS (TLMS) algorithm, both in the presence of white/colored observation noise. The reduction in convergence error achieved by the new algorithm with desired signal decomposition is found to be lower than that obtained without decomposition. The experimental results indicate that the proposed method is better than traditional adaptive filter using LMS algorithm in the aspects of retaining geometrical characteristics of ECG signal.

ECG fiducial point extraction using switching Kalman filter.

Science.gov (United States)

Akhbari, Mahsa; Ghahjaverestan, Nasim Montazeri; Shamsollahi, Mohammad B; Jutten, Christian

2018-04-01

In this paper, we propose a novel method for extracting fiducial points (FPs) of the beats in electrocardiogram (ECG) signals using switching Kalman filter (SKF). In this method, according to McSharry's model, ECG waveforms (P-wave, QRS complex and T-wave) are modeled with Gaussian functions and ECG baselines are modeled with first order auto regressive models. In the proposed method, a discrete state variable called "switch" is considered that affects only the observation equations. We denote a mode as a specific observation equation and switch changes between 7 modes and corresponds to different segments of an ECG beat. At each time instant, the probability of each mode is calculated and compared among two consecutive modes and a path is estimated, which shows the relation of each part of the ECG signal to the mode with the maximum probability. ECG FPs are found from the estimated path. For performance evaluation, the Physionet QT database is used and the proposed method is compared with methods based on wavelet transform, partially collapsed Gibbs sampler (PCGS) and extended Kalman filter. For our proposed method, the mean error and the root mean square error across all FPs are 2 ms (i.e. less than one sample) and 14 ms, respectively. These errors are significantly smaller than those obtained using other methods. The proposed method achieves lesser RMSE and smaller variability with respect to others. Copyright © 2018 Elsevier B.V. All rights reserved.

Wireless Self-Acquistion of 12-Lead ECG via Android Smart Phone

Science.gov (United States)

Schlegel, Todd T.

2012-01-01

Researchers at NASA s Johnson Space Center and at Orbital Research, Inc. (a NASA SBIR grant recipient) have recently developed a dry-electrode harness that allows for self-acquisition of resting 12-lead ECGs by minimally trained laypersons. When used in conjunction with commercial wireless (e.g., Bluetooth(TM) or 802.11-enabled) 12-lead ECG devices and custom smart phone-based software, the collected 12-lead ECG data can also immediately be forwarded from any geographic location within cellular range to the user s physician(s) of choice. The system can also be used to immediately forward to central receiving stations 12-lead ECG data collected during space flight or during activities in any remote terrestrial location supported by an internet or cellular phone infrastructure. The main novel aspects of the system are first, the dry-electrode 12-lead ECG harness itself, and second, an accompanying Android(TM) smart phone-based wireless 12-lead ECG capability. The ECG harness nominally employs dry electrodes manufactured by Orbital Research, Inc, recently cleared through the Food and Drug Administration (FDA). However, other dry electrodes that are not yet FDA cleared, for example those recently developed by Nanosonic, Inc as part of another NASA SBIR grant, can also be used. The various advantageous features of the harness include: 1) laypersons can be quickly instructed on its correct use, remotely if necessary; 2) all tangled "leadwire spaghetti" is eliminated, as is the common clinical problem of "leadwire reversal"; 3) all adhesives and disposables are also eliminated, the harness being fully reusable; if multiple individuals intend to use use the same harness, then standard antimicrobial wipes can be employed to sterilize the dry electrodes (and harness surface if needed) between users; 5) padded cushions at the lateral sides of the torso function to press the left arm (LA) and right arm (RA) dry electrodes mounted on the cushions against sideward or downward-rested

E-Bra system for women ECG measurement with GPRS communication, Nanosensor, and motion artifact remove algorithm

Science.gov (United States)

Kwon, Hyeokjun; Oh, Sechang; Kumar, Prashanth S.; Varadan, Vijay K.

2012-10-01

CardioVascular Disease(CVD)s lead the sudden cardiac death due to irregular phenomenon of the cardiac signal by the abnormal case of blood vessel and cardiac structure. For last two decades, cardiac disease research for man is under active discussion. As a result, the death rate by cardiac disease in men has been falling gradually compared with relatively increasing the women death rate due to CVD[2]. The main reason of this phenomenon causes the lack a sense of the seriousness to female CVD and different symptom of female CVD compared with the symptoms of male CVD. Usually, because the women CVD accompanies with ordinary symptoms unrecognizing the heart abnormality signal such as unusual fatigue, sleep disturbances, shortness of breath, anxiety, chest discomfort, and indigestion dyspepsia, most women CVD patients do not realize that these symptoms are related to the CVD symptoms. Therefore, periodic ECG signal observation is required for women cardiac disease patients. ElectroCardioGram(ECG) detection, treadmill test/exercise ECG, nuclear scan, coronary angiography, and intracoronary ultrasound are used to diagnose abnormality of heart. Among the medical checkup methods for CVDs checkup, it is very effective method for the diagnosis of cardiac disease and the early detection of heart abnormality to monitor ECG periodically. This paper suggests the effective ECG monitoring system for woman by attaching the system on woman's brassiere by using augmented chest lead attachment method. The suggested system in this paper consists of ECG signal transmission system and a server program to display and analyze the transmitted ECG. The ECG signal transmission system consists of three parts such as ECG physical signal detection part with two electrodes made by gold nanowire structure, data acquisition with AD converter, and data transmission part with GPRS(General Packet Radio Service) communication. Usually, to detect human bio signal, Ag/AgCl or gold cup electrodes are used

Integrated processing of ECG's in a hospital information system

NARCIS (Netherlands)

Helder, J.C.; Schram, P.H.; Verwey, H.; Meijler, F.L.; Robles de Medina, E.O.

The ECG handling in the University Hospital of Utrecht is composed by a system consisting of acquisition and storage of ECG signals, computer analysis, data management, and storage of readings in a patient data base. The last two modules are part of a Hospital Information System (HIS). The modular

CNT/PDMS composite flexible dry electrodes for long-term ECG monitoring.

Science.gov (United States)

Jung, Ha-Chul; Moon, Jin-Hee; Baek, Dong-Hyun; Lee, Jae-Hee; Choi, Yoon-Young; Hong, Joung-Sook; Lee, Sang-Hoon

2012-05-01

We fabricated a carbon nanotube (CNT)/ polydimethylsiloxane (PDMS) composite-based dry ECG electrode that can be readily connected to conventional ECG devices, and showed its long-term wearable monitoring capability and robustness to motion and sweat. While the dispersion of CNTs in PDMS is challenging, we optimized the process to disperse untreated CNTs within PDMS by mechanical force only. The electrical and mechanical characteristics of the CNT/PDMS electrode were tested according to the concentration of CNTs and its thickness. The performances of ECG electrodes were evaluated by using 36 types of electrodes which were fabricated with different concentrations of CNTs, and with a differing diameter and thickness. The ECG signals were obtained by using electrodes of diverse sizes to observe the effects of motion and sweat, and the proposed electrode was shown to be robust to both factors. The CNT concentration and diameter of the electrodes were critical parameters in obtaining high-quality ECG signals. The electrode was shown to be biocompatible from the cytotoxicity test. A seven-day continuous wearability test showed that the quality of the ECG signal did not degrade over time, and skin reactions such as itching or erythema were not observed. This electrode could be used for the long-term measurement of other electrical biosignals for ubiquitous health monitoring including EMG, EEG, and ERG.

Unobtrusive ECG monitoring in the NICU using a capacitive sensing array

International Nuclear Information System (INIS)

Atallah, L; Meftah, M; Schellekens, M; Serteyn, A; Vullings, R; Bergmans, J W M; Osagiator, A; Oetomo, S Bambang

2014-01-01

The thin skin of preterm babies is easily damaged by adhesive electrodes, tapes, chest drains and needle-marks. The scars caused could be disfiguring or disabling to 10% of preterm newborns. Capacitive sensors present an attractive option for pervasively monitoring neonatal ECG, and can be embedded in a support system or even a garment worn by the neonate. This could improve comfort and reduce pain aiding better recovery as well as avoiding the scars caused by adhesive electrodes. In this work, we investigate the use of an array of capacitive sensors unobtrusively embedded in a mattress and used in a clinical environment for 15 preterm neonates. We also describe the analysis framework including the fusion of information from all sensors to provide a more accurate ECG signal. We propose a channel selection strategy as well as a method using physiological information to obtain a reliable ECG signal. When sensor coverage is well attained, results for both instantaneous heart rate and ECG signal shape analysis are very encouraging. The study also provides several insights on important factors affecting the results. These include the effect of textile type, number of layers, interferences (e.g. people walking by), motion severity and interventions. Incorporating this knowledge in the design of a capacitive sensing system would be crucial in ensuring that these sensors provide a reliable ECG signal when embedded in a neonatal support system. (paper)

A multi-step method with signal quality assessment and fine-tuning procedure to locate maternal and fetal QRS complexes from abdominal ECG recordings

International Nuclear Information System (INIS)

Liu, Chengyu; Li, Peng; Zhao, Lina; Di Maria, Costanzo; Zhang, Henggui; Chen, Zhiqing

2014-01-01

Non-invasive monitoring of fetal electrocardiogram (fECG) plays an important role in detecting and diagnosing fetal diseases. This study aimed to develop a multi-step method for locating both maternal and fetal QRS complexes from abdominal ECG (aECG) recordings. The proposed method included four major steps: abdominal ECG pre-processing, maternal QRS complex locating, maternal ECG cancellation and fetal QRS complex locating. Signal quality assessment (SQA) and fine-tuning for maternal ECG (FTM) were implemented in the first and third steps, respectively. The method was then evaluated using 75 non-invasive 4-channel aECG recordings provided by the PhysioNet/Computing in Cardiology Challenge 2013. The F 1 measure, which is a new index introduced by Behar et al (2013 Proc. Comput. Cardiol. 40 297–300), was used to assess the locating accuracy. The other two indices, mean squared error of heart rate (MSE H R) between the fetal HR signals estimated from the reference and our method (MSE H R in bpm 2 ) and root mean squared difference between the corresponding fetal RR intervals (MSE R R in ms) were also used to assess the locating accuracy. Overall, for the maternal QRS complex, the F 1 measure was 98.4% from the method without the implementation of SQA, and it was improved to 99.8% with SQA. For the fetal QRS complex, the F 1 measure, MSE H R and MSE R R were 84.9%, 185.6 bpm 2 and 19.4 ms for the method without both SQA and FTM procedures. They were improved to 93.9%, 47.5 bpm 2 and 7.6 ms with both SQA and FTM procedures. These improvements were observed from each individual subject. It can be concluded that implementing both SQA and FTM procedures could achieve better performance for locating both maternal and fetal QRS complexes. (paper)

Thallium-201 myocardial perfusion imaging at rest and during exercise. Comparative sensitivity to electrocardiography in coronary artery disease

International Nuclear Information System (INIS)

Bailey, I.K.; Griffith, L.S.C.; Rouleau, J.; Strauss, H.W.; Pitt, B.

1977-01-01

The sensitivity of myocardial perfusion imaging (MPI) using thallium-201 injected both at rest and during peak exercise was compared to simultaneously recorded 12 lead electrocardiography (ECG) for the detection of transient ischemia in 20 normal subjects and 63 patients with coronary artery disease (CAD). No significant perfusion defects or ECG changes were seen on either the rest or exercise studies in any of the normal subjects. Fifty-six percent of patients with CAD developed new perfusion defects with exercise compared to 38 percent who developed ischemic ST-segment depression (P < 0.02). However, when chest pain and/or ST depression were considered indices of ischemia, the sensitivity of exercise testing and thallium-201 MPI was similar. The increased sensitivity of MPI compared to ST-segment depression on the ECG was due to patients with baseline ECG abnormalities and those who failed to achieve 85 percent of predicted maximum heart rate with exercise. Analysis of the exercise results according to the extent of coronary artery disease revealed a progressive increase in both positive ECGs and MPI with the number of vessels involved. In patients with single vessel disease the MPI was more sensitive than the ECG (P < 0.02). The combination of the rest and exercise ECG, MPI and chest pain during exercise failed to identify 11 percent of patients with CAD. Exercise thallium-201 MPI is a useful adjunct to conventional exercise testing particularly when evaluating patients with abnormal resting ECGs, those who develop ventricular conduction defects or arrhythmias during exercise, and those who fail to achieve their predicted heart rate because of fatigue or breathlessness

Correlation of Respiratory Signals and Electrocardiogram Signals via Empirical Mode Decomposition

KAUST Repository

El Fiky, Ahmed Osama

2011-05-24

Recently Electrocardiogram (ECG) signals are being broadly used as an essential diagnosing tool in different clinical applications as they carry a reliable representation not only for cardiac activities, but also for other associated biological processes, like respiration. However, the process of recording and collecting them has usually suffered from the presence of some undesired noises, which in turn affects the reliability of such representations.Therefore, de-noising ECG signals became a hot research field for signal processing experts to ensure better and clear representation of the different cardiac activities. Given the nonlinear and non-stationary properties of ECGs, it is not a simple task to cancel the undesired noise terms without affecting the biological physics of them. In this study, we are interested in correlating the ECG signals with respiratory parameters, specifically the lung volume and lung pressure. We have focused on the concept of de-noising ECG signals by means of signal decomposition using an algorithm called the Empirical Mode Decomposition (EMD) where the original ECG signals are being decomposed into a set of intrinsic mode functions (IMF). Then, we have provided criteria based on which some of these IMFs have been adapted to reconstruct de-noised ECG version. Finally, we have utilized de-noised ECGs as well as IMFs for to study the correlation with lung volume and lung pressure. These correlation studies have showed some clear resemblance especially between the oscillations of ECGs and lung pressures.

Compressed sensing of ECG signal for wireless system with new fast iterative method.

Science.gov (United States)

Tawfic, Israa; Kayhan, Sema

2015-12-01

Recent experiments in wireless body area network (WBAN) show that compressive sensing (CS) is a promising tool to compress the Electrocardiogram signal ECG signal. The performance of CS is based on algorithms use to reconstruct exactly or approximately the original signal. In this paper, we present two methods work with absence and presence of noise, these methods are Least Support Orthogonal Matching Pursuit (LS-OMP) and Least Support Denoising-Orthogonal Matching Pursuit (LSD-OMP). The algorithms achieve correct support recovery without requiring sparsity knowledge. We derive an improved restricted isometry property (RIP) based conditions over the best known results. The basic procedures are done by observational and analytical of a different Electrocardiogram signal downloaded them from PhysioBankATM. Experimental results show that significant performance in term of reconstruction quality and compression rate can be obtained by these two new proposed algorithms, and help the specialist gathering the necessary information from the patient in less time if we use Magnetic Resonance Imaging (MRI) application, or reconstructed the patient data after sending it through the network. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Washable and Reliable Textile Electrodes Embedded into Underwear Fabric for Electrocardiography (ECG) Monitoring

OpenAIRE

Amale Ankhili; Xuyuan Tao; Cédric Cochrane; David Coulon; Vladan Koncar

2018-01-01

A medical quality electrocardiogram (ECG) signal is necessary for permanent monitoring, and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The ...

ECG Holter monitor with alert system and mobile application

Science.gov (United States)

Teron, Abigail C.; Rivera, Pedro A.; Goenaga, Miguel A.

2016-05-01

This paper proposes a new approach on the Holter monitor by creating a portable Electrocardiogram (ECG) Holter monitor that will alert the user by detecting abnormal heart beats using a digital signal processing software. The alarm will be triggered when the patient experiences arrhythmias such as bradycardia and tachycardia. The equipment is simple, comfortable and small in size that fit in the hand. It can be used at any time and any moment by placing three leads to the person's chest which is connected to an electronic circuit. The ECG data will be transmitted via Bluetooth to the memory of a selected mobile phone using an application that will store the collected data for up to 24 hrs. The arrhythmia is identified by comparing the reference signals with the user's signal. The diagnostic results demonstrate that the ECG Holter monitor alerts the user when an arrhythmia is detected thru the Holter monitor and mobile application.

Detection of driving fatigue by using noncontact EMG and ECG signals measurement system.

Science.gov (United States)

Fu, Rongrong; Wang, Hong

2014-05-01

Driver fatigue can be detected by constructing a discriminant mode using some features obtained from physiological signals. There exist two major challenges of this kind of methods. One is how to collect physiological signals from subjects while they are driving without any interruption. The other is to find features of physiological signals that are of corresponding change with the loss of attention caused by driver fatigue. Driving fatigue is detected based on the study of surface electromyography (EMG) and electrocardiograph (ECG) during the driving period. The noncontact data acquisition system was used to collect physiological signals from the biceps femoris of each subject to tackle the first challenge. Fast independent component analysis (FastICA) and digital filter were utilized to process the original signals. Based on the statistical analysis results given by Kolmogorov-Smirnov Z test, the peak factor of EMG (p fatigue of drivers. The discriminant criterion of fatigue was obtained from the training samples by using Mahalanobis distance, and then the average classification accuracy was given by 10-fold cross-validation. The results showed that the method proposed in this paper can give well performance in distinguishing the normal state and fatigue state. The noncontact, onboard vehicle drivers' fatigue detection system was developed to reduce fatigue-related risks.

IIR digital filter design for powerline noise cancellation of ECG signal using arduino platform

Science.gov (United States)

Rahmatillah, Akif; Ataulkarim

2017-05-01

Powerline noise has been one of significant noises of Electrocardiogram (ECG) signal measurement. This noise is characterized by a sinusoidal signal which has 50 Hz of noise and 0.3 mV of maximum amplitude. This paper describes the design of IIR Notch filter design to reject a 50 Hz power line noise. IIR filter coefficients were calculated using pole placement method with three variations of band stop cut off frequencies of (49-51)Hz, (48 - 52)Hz, and (47 - 53)Hz. The algorithm and coefficients of filter were embedded to Arduino DUE (ARM 32 bit microcontroller). IIR notch filter designed has been able to reject power line noise with average square of error value of 0.225 on (49-51) Hz filter design and 0.2831 on (48 - 52)Hz filter design.

3D Finite Element Electrical Model of Larval Zebrafish ECG Signals

Science.gov (United States)

Crowcombe, James; Dhillon, Sundeep Singh; Hurst, Rhiannon Mary; Egginton, Stuart; Müller, Ferenc; Sík, Attila; Tarte, Edward

2016-01-01

Assessment of heart function in zebrafish larvae using electrocardiography (ECG) is a potentially useful tool in developing cardiac treatments and the assessment of drug therapies. In order to better understand how a measured ECG waveform is related to the structure of the heart, its position within the larva and the position of the electrodes, a 3D model of a 3 days post fertilisation (dpf) larval zebrafish was developed to simulate cardiac electrical activity and investigate the voltage distribution throughout the body. The geometry consisted of two main components; the zebrafish body was modelled as a homogeneous volume, while the heart was split into five distinct regions (sinoatrial region, atrial wall, atrioventricular band, ventricular wall and heart chambers). Similarly, the electrical model consisted of two parts with the body described by Laplace’s equation and the heart using a bidomain ionic model based upon the Fitzhugh-Nagumo equations. Each region of the heart was differentiated by action potential (AP) parameters and activation wave conduction velocities, which were fitted and scaled based on previously published experimental results. ECG measurements in vivo at different electrode recording positions were then compared to the model results. The model was able to simulate action potentials, wave propagation and all the major features (P wave, R wave, T wave) of the ECG, as well as polarity of the peaks observed at each position. This model was based upon our current understanding of the structure of the normal zebrafish larval heart. Further development would enable us to incorporate features associated with the diseased heart and hence assist in the interpretation of larval zebrafish ECGs in these conditions. PMID:27824910

A method to determine the necessity for global signal regression in resting-state fMRI studies.

Science.gov (United States)

Chen, Gang; Chen, Guangyu; Xie, Chunming; Ward, B Douglas; Li, Wenjun; Antuono, Piero; Li, Shi-Jiang

2012-12-01

In resting-state functional MRI studies, the global signal (operationally defined as the global average of resting-state functional MRI time courses) is often considered a nuisance effect and commonly removed in preprocessing. This global signal regression method can introduce artifacts, such as false anticorrelated resting-state networks in functional connectivity analyses. Therefore, the efficacy of this technique as a correction tool remains questionable. In this article, we establish that the accuracy of the estimated global signal is determined by the level of global noise (i.e., non-neural noise that has a global effect on the resting-state functional MRI signal). When the global noise level is low, the global signal resembles the resting-state functional MRI time courses of the largest cluster, but not those of the global noise. Using real data, we demonstrate that the global signal is strongly correlated with the default mode network components and has biological significance. These results call into question whether or not global signal regression should be applied. We introduce a method to quantify global noise levels. We show that a criteria for global signal regression can be found based on the method. By using the criteria, one can determine whether to include or exclude the global signal regression in minimizing errors in functional connectivity measures. Copyright © 2012 Wiley Periodicals, Inc.

Efficacy and safety of dextrose-insulin in unmasking non-diagnostic Brugada ECG patterns.

Science.gov (United States)

Velázquez-Rodríguez, Enrique; Rodríguez-Piña, Horacio; Pacheco-Bouthillier, Alex; Jiménez-Cruz, Marcelo Paz

Typical diagnostic, coved-type 1, Brugada ECG patterns fluctuate spontaneously over time with a high proportion of non-diagnostic ECG patterns. Insulin modulates ion transport mechanisms and causes hyperpolarization of the resting potential. We report our experience with unmasking J-ST changes in response to a dextrose-insulin test. Nine patients, mean age 40.5±19.4years (range: 15-65years), presented initially with a non-diagnostic ECG pattern, which was suggestive of Brugada syndrome (group I). They were compared with 10 patients with normal ECG patterns (group II). Participants received an infusion of 50g of 50% dextrose, followed by 10IU of intravenous regular insulin. Positive changes were defined by conversion to a diagnostic ECG pattern. The dextrose-insulin test was positive in six of seven (85.7%) patients (kappa 0.79, p=0.02) that was confirmed with a pharmacologic test (kappa 1, p=0.003). One had an inconclusive test, and two with a negative test had an early repolarization ECG pattern. All subjects in group II had a negative test (pECG patterns. Copyright © 2016 Elsevier Inc. All rights reserved.

Using Intracardiac Vectorcardiographic Loop for Surface ECG Synthesis

Directory of Open Access Journals (Sweden)

G. Carrault

2008-09-01

Full Text Available Current cardiac implantable devices offer improved processing power and recording capabilities. Some of these devices already provide basic telemonitoring features that may help to reduce health care expenditure. A challenge is posed in particular for the telemonitoring of the patient's cardiac electrical activity. Indeed, only intracardiac electrograms (EGMs are acquired by the implanted device and these signals are difficult to analyze directly by clinicians. In this paper, we propose a patient-specific method to synthesize the surface electrocardiogram (ECG from a set of EGM signals, based on a 3D representation of the cardiac electrical activity and principal component analysis (PCA. The results, in the case of sinus rhythm, show a correlation coefficient between the real ECG and the synthesized ECG of about 0.85. Moreover, the application of the proposed method to the patients who present an abnormal heart rhythm exhibits promising results, especially for characterizing the bundle branch blocs. Finally, in order to evaluate the behavior of our procedure in some practical situations, the quality of the ECG reconstruction is studied as a function of the number of EGM electrodes provided by the CIDs.

Using Intracardiac Vectorcardiographic Loop for Surface ECG Synthesis

Science.gov (United States)

Kachenoura, A.; Porée, F.; Hernández, A. I.; Carrault, G.

2008-12-01

Current cardiac implantable devices offer improved processing power and recording capabilities. Some of these devices already provide basic telemonitoring features that may help to reduce health care expenditure. A challenge is posed in particular for the telemonitoring of the patient's cardiac electrical activity. Indeed, only intracardiac electrograms (EGMs) are acquired by the implanted device and these signals are difficult to analyze directly by clinicians. In this paper, we propose a patient-specific method to synthesize the surface electrocardiogram (ECG) from a set of EGM signals, based on a 3D representation of the cardiac electrical activity and principal component analysis (PCA). The results, in the case of sinus rhythm, show a correlation coefficient between the real ECG and the synthesized ECG of about 0.85. Moreover, the application of the proposed method to the patients who present an abnormal heart rhythm exhibits promising results, especially for characterizing the bundle branch blocs. Finally, in order to evaluate the behavior of our procedure in some practical situations, the quality of the ECG reconstruction is studied as a function of the number of EGM electrodes provided by the CIDs.

An Investigation on the Effect of Extremely Low Frequency Pulsed Electromagnetic Fields on Human Electrocardiograms (ECGs).

Science.gov (United States)

Fang, Qiang; Mahmoud, Seedahmed S; Yan, Jiayong; Li, Hui

2016-11-23

For this investigation, we studied the effects of extremely low frequency pulse electromagnetic fields (ELF-PEMF) on the human cardiac signal. Electrocardiograms (ECGs) of 22 healthy volunteers before and after a short duration of ELF-PEMF exposure were recorded. The experiment was conducted under single-blind conditions. The root mean square (RMS) value of the recorded data was considered as comparison criteria. We also measured and analysed four important ECG time intervals before and after ELF-PEMF exposure. Results revealed that the RMS value of the ECG recordings from 18 participants (81.8% of the total participants) increased with a mean value of 3.72%. The increase in ECG voltage levels was then verified by a second experimental protocol with a control exposure. In addition to this, we used hyperbolic T-distributions (HTD) in the analysis of ECG signals to verify the change in the RR interval. It was found that there were small shifts in the frequency-domain signal before and after EMF exposure. This shift has an influence on all frequency components of the ECG signals, as all spectrums were shifted. It is shown from this investigation that a short time exposure to ELF-PEMF can affect the properties of ECG signals. Further study is needed to consolidate this finding and discover more on the biological effects of ELF-PEMF on human physiological processes.

Real-time QRS detection using integrated variance for ECG gated cardiac MRI

Directory of Open Access Journals (Sweden)

Schmidt Marcus

2016-09-01

Full Text Available During magnetic resonance imaging (MRI, a patient’s vital signs are required for different purposes. In cardiac MRI (CMR, an electrocardiogram (ECG of the patient is required for triggering the image acquisition process. However, a reliable QRS detection of an ECG signal acquired inside an MRI scanner is a challenging task due to the magnetohydrodynamic (MHD effect which interferes with the ECG. The aim of this work was to develop a reliable QRS detector usable inside the MRI which also fulfills the standards for medical devices (IEC 60601-2-27. Therefore, a novel real-time QRS detector based on integrated variance measurements is presented. The algorithm was trained on ANSI/AAMI EC13 test waveforms and was then applied to two databases with 12-lead ECG signals recorded inside and outside an MRI scanner. Reliable results for both databases were achieved for the ECG signals recorded inside (DBMRI: sensitivity Se = 99.94%, positive predictive value +P = 99.84% and outside (DBInCarT: Se = 99.29%, +P = 99.72% the MRI. Due to the accurate R-peak detection in real-time this can be used for monitoring and triggering in MRI exams.

Improvement of emotional healthcare system with stress detection from ECG signal.

Science.gov (United States)

Tivatansakul, S; Ohkura, M

2015-01-01

Our emotional healthcare system is designed to cope with users' negative emotions in daily life. To make the system more intelligent, we integrated emotion recognition by facial expression to provide appropriate services based on user's current emotional state. Our emotion recognition by facial expression has confusion issue to recognize some positive, neutral and negative emotions that make the emotional healthcare system provide a relaxation service even though users don't have negative emotions. Therefore, to increase the effectiveness of the system to provide the relaxation service, we integrate stress detection from ECG signal. The stress detection might be able to address the confusion issue of emotion recognition by facial expression to provide the service. Indeed, our results show that integration of stress detection increases the effectiveness and efficiency of the emotional healthcare system to provide services.

Optimisation algorithms for ECG data compression.

Science.gov (United States)

Haugland, D; Heber, J G; Husøy, J H

1997-07-01

The use of exact optimisation algorithms for compressing digital electrocardiograms (ECGs) is demonstrated. As opposed to traditional time-domain methods, which use heuristics to select a small subset of representative signal samples, the problem of selecting the subset is formulated in rigorous mathematical terms. This approach makes it possible to derive algorithms guaranteeing the smallest possible reconstruction error when a bounded selection of signal samples is interpolated. The proposed model resembles well-known network models and is solved by a cubic dynamic programming algorithm. When applied to standard test problems, the algorithm produces a compressed representation for which the distortion is about one-half of that obtained by traditional time-domain compression techniques at reasonable compression ratios. This illustrates that, in terms of the accuracy of decoded signals, existing time-domain heuristics for ECG compression may be far from what is theoretically achievable. The paper is an attempt to bridge this gap.

Matrix of regularity for improving the quality of ECGs

International Nuclear Information System (INIS)

Xia, Henian; Garcia, Gabriel A; Zhao, Xiaopeng; Bains, Jujhar; Wortham, Dale C

2012-01-01

The 12-lead electrocardiography (ECG) is the gold standard for diagnosis of abnormalities of the heart. However, the ECG is susceptible to artifacts, which may lead to wrong diagnosis and thus mistreatment. It is a clinical challenge of great significance differentiating ECG artifacts from patterns of diseases. We propose a computational framework, called the matrix of regularity, to evaluate the quality of ECGs. The matrix of regularity is a novel mechanism to fuse results from multiple tests of signal quality. Moreover, this method can produce a continuous grade, which can more accurately represent the quality of an ECG. When tested on a dataset from the Computing in Cardiology/PhysioNet Challenge 2011, the algorithm achieves up to 95% accuracy. The area under the receiver operating characteristic curve is 0.97. The developed framework and computer program have the potential to improve the quality of ECGs collected using conventional and portable devices. (paper)

An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm.

Science.gov (United States)

Qin, Qin; Li, Jianqing; Yue, Yinggao; Liu, Chengyu

2017-01-01

R-peak detection is crucial in electrocardiogram (ECG) signal analysis. This study proposed an adaptive and time-efficient R-peak detection algorithm for ECG processing. First, wavelet multiresolution analysis was applied to enhance the ECG signal representation. Then, ECG was mirrored to convert large negative R-peaks to positive ones. After that, local maximums were calculated by the first-order forward differential approach and were truncated by the amplitude and time interval thresholds to locate the R-peaks. The algorithm performances, including detection accuracy and time consumption, were tested on the MIT-BIH arrhythmia database and the QT database. Experimental results showed that the proposed algorithm achieved mean sensitivity of 99.39%, positive predictivity of 99.49%, and accuracy of 98.89% on the MIT-BIH arrhythmia database and 99.83%, 99.90%, and 99.73%, respectively, on the QT database. By processing one ECG record, the mean time consumptions were 0.872 s and 0.763 s for the MIT-BIH arrhythmia database and QT database, respectively, yielding 30.6% and 32.9% of time reduction compared to the traditional Pan-Tompkins method.

Design of Low Power Algorithms for Automatic Embedded Analysis of Patch ECG Signals

DEFF Research Database (Denmark)

Saadi, Dorthe Bodholt

, several different cable-free wireless patch-type ECG recorders have recently reached the market. One of these recorders is the ePatch designed by the Danish company DELTA. The extended monitoring period available with the patch recorders has demonstrated to increase the diagnostic yield of outpatient ECG....... Such algorithms could allow the real-time transmission of clinically relevant information to a central monitoring station. The first step in embedded ECG interpretation is the automatic detection of each individual heartbeat. An important part of this project was therefore to design a novel algorithm...

A method of ECG template extraction for biometrics applications.

Science.gov (United States)

Zhou, Xiang; Lu, Yang; Chen, Meng; Bao, Shu-Di; Miao, Fen

2014-01-01

ECG has attracted widespread attention as one of the most important non-invasive physiological signals in healthcare-system related biometrics for its characteristics like ease-of-monitoring, individual uniqueness as well as important clinical value. This study proposes a method of dynamic threshold setting to extract the most stable ECG waveform as the template for the consequent ECG identification process. With the proposed method, the accuracy of ECG biometrics using the dynamic time wraping for difference measures has been significantly improved. Analysis results with the self-built electrocardiogram database show that the deployment of the proposed method was able to reduce the half total error rate of the ECG biometric system from 3.35% to 1.45%. Its average running time on the platform of android mobile terminal was around 0.06 seconds, and thus demonstrates acceptable real-time performance.

New approach to ECG's features recognition involving neural network

International Nuclear Information System (INIS)

Babloyantz, A.; Ivanov, V.V.; Zrelov, P.V.

2001-01-01

A new approach for the detection of slight changes in the form of the ECG signal is proposed. It is based on the approximation of raw ECG data inside each RR-interval by the expansion in polynomials of special type and on the classification of samples represented by sets of expansion coefficients using a layered feed-forward neural network. The transformation applied provides significantly simpler data structure, stability to noise and to other accidental factors. A by-product of the method is the compression of ECG data with factor 5

The Normal Electrocardiogram: Resting 12-Lead and Electrocardiogram Monitoring in the Hospital.

Science.gov (United States)

Harris, Patricia R E

2016-09-01

The electrocardiogram (ECG) is a well-established diagnostic tool extensively used in clinical settings. Knowledge of cardiac rhythm and mastery of cardiac waveform interpretation are fundamental for intensive care nurses. Recognition of the normal findings for the 12-lead ECG and understanding the significance of changes from baseline in continuous cardiac monitoring are essential steps toward ensuring safe patient care. This article highlights historical developments in electrocardiography, describes the normal resting 12-lead ECG, and discusses the need for continuous cardiac monitoring. In addition, future directions for the ECG are explored briefly. Copyright © 2016 Elsevier Inc. All rights reserved.

The effect of 50/60 Hz notch filter application on human and rat ECG recordings

International Nuclear Information System (INIS)

Vale-Cardoso, A S; Guimarães, H N

2010-01-01

Power-line interference is always present in indoor biopotential measurements, even when its extremely low magnitude makes it imperceptible. In special situations, this kind of interference can be neglected, but this is not a general rule. In laboratory experiments and clinical analysis, it is hard (and expensive) to isolate the subject of measurement from electrical fields produced by a power line. In human biopotential recordings, it is common practice to apply a 50/60 Hz notch filter to reduce this kind of interference. In such cases, there is no considerable distortion observed on the recorded signal. However, experiments showed that it is not true for rat ECG recordings. Several kinds of notch filters (analog and digital) were implemented for evaluation of the distortion caused on ECG signals. These filters were applied to ECGs of humans and rats and then distortion estimates were computed from their resulting signals. The comparison of these estimates showed that, as experimentally observed, rat ECG signals are significantly distorted and deformed when a 50/60 Hz notch filter is applied to them, while human ECGs are not. The major goal of this paper is to show that the use of a notch filter for power-line interference rejection, when applied to rat ECG recordings, can severely deform the QRS complex of such signals, warning researchers against its non-deliberate usage

Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring.

Science.gov (United States)

Everss-Villalba, Estrella; Melgarejo-Meseguer, Francisco Manuel; Blanco-Velasco, Manuel; Gimeno-Blanes, Francisco Javier; Sala-Pla, Salvador; Rojo-Álvarez, José Luis; García-Alberola, Arcadi

2017-10-25

Noise and artifacts are inherent contaminating components and are particularly present in Holter electrocardiogram (ECG) monitoring. The presence of noise is even more significant in long-term monitoring (LTM) recordings, as these are collected for several days in patients following their daily activities; hence, strong artifact components can temporarily impair the clinical measurements from the LTM recordings. Traditionally, the noise presence has been dealt with as a problem of non-desirable component removal by means of several quantitative signal metrics such as the signal-to-noise ratio (SNR), but current systems do not provide any information about the true impact of noise on the ECG clinical evaluation. As a first step towards an alternative to classical approaches, this work assesses the ECG quality under the assumption that an ECG has good quality when it is clinically interpretable. Therefore, our hypotheses are that it is possible (a) to create a clinical severity score for the effect of the noise on the ECG, (b) to characterize its consistency in terms of its temporal and statistical distribution, and (c) to use it for signal quality evaluation in LTM scenarios. For this purpose, a database of external event recorder (EER) signals is assembled and labeled from a clinical point of view for its use as the gold standard of noise severity categorization. These devices are assumed to capture those signal segments more prone to be corrupted with noise during long-term periods. Then, the ECG noise is characterized through the comparison of these clinical severity criteria with conventional quantitative metrics taken from traditional noise-removal approaches, and noise maps are proposed as a novel representation tool to achieve this comparison. Our results showed that neither of the benchmarked quantitative noise measurement criteria represent an accurate enough estimation of the clinical severity of the noise. A case study of long-term ECG is reported

[Experience in the use of equipment for ECG system analysis in municipal polyclinics].

Science.gov (United States)

Bondarenko, A A

2006-01-01

Two electrocardiographs, an analog-digital electrocardiograph with preliminary analog filtering of signal and a smart cardiograph implemented as a PC-compatible device without preliminary analog filtering, are considered. Advantages and disadvantages of ECG systems based on artificial intelligence are discussed. ECG interpretation modes provided by the two electrocardiographs are considered. The reliability of automatic ECG interpretation is assessed. Problems of rational use of automated ECG processing systems are discussed.

ECG biometric identification: A compression based approach.

Science.gov (United States)

Bras, Susana; Pinho, Armando J

2015-08-01

Using the electrocardiogram signal (ECG) to identify and/or authenticate persons are problems still lacking satisfactory solutions. Yet, ECG possesses characteristics that are unique or difficult to get from other signals used in biometrics: (1) it requires contact and liveliness for acquisition (2) it changes under stress, rendering it potentially useless if acquired under threatening. Our main objective is to present an innovative and robust solution to the above-mentioned problem. To successfully conduct this goal, we rely on information-theoretic data models for data compression and on similarity metrics related to the approximation of the Kolmogorov complexity. The proposed measure allows the comparison of two (or more) ECG segments, without having to follow traditional approaches that require heartbeat segmentation (described as highly influenced by external or internal interferences). As a first approach, the method was able to cluster the data in three groups: identical record, same participant, different participant, by the stratification of the proposed measure with values near 0 for the same participant and closer to 1 for different participants. A leave-one-out strategy was implemented in order to identify the participant in the database based on his/her ECG. A 1NN classifier was implemented, using as distance measure the method proposed in this work. The classifier was able to identify correctly almost all participants, with an accuracy of 99% in the database used.

Clinical evaluation of the Tl-201 ECG-gated myocardial SPECT

International Nuclear Information System (INIS)

Mochizuki, Teruhito

1989-01-01

In order to evaluate the clinical usefulness of the Tl-201 ECG-gated myocardial single photon emission computed tomography (SPECT), we compared the wall motion and the grade of the Tl-201 uptake of the ECG-gated myocardial SPECT with the wall motion of the ECG-gated blood pool SPECT. Materials were 87 patients of 50 old myocardial infarctions (OMIs), 19 hypertrophic cardiomyopathies (HCMs), 2 dilated cardiomyopathies (DCMs) and 16 others. After intravenous injection of 111-185 MBq (3-5 mCi) of Tl-201 at rest, the projection data were acquired using a rotating gamma-camera through 180deg, from RAO 45deg in 24 directions, each of which consisted of 80-100 beats. For the reconstruction of ED, ES and non-gated images, R-R interval was divided into about 20 (18-22) fractions. In 348 regions of interest (anterior, septal, lateral and inferior wall) in 87 cases, wall motion and the Tl-201 uptake were evaluated to three grades (normal, hypokinesis and akinesis; normal, low and defect, respectively), which were compared with the wall motion of the ECG-gated blood pool SPECT. The wall motion and the grade of the Tl-201 uptake of the ECG-gated myocardial SPECT correlated well with the wall motion of the ECG-gated blood pool SPECT (96.6% and 87.9%, respectively). In conclusion, the ECG-gated myocardial SPECT can provide clear perfusion images and is a very useful diagnostic strategy to evaluate the regional wall motion and perfusion simultaneously. (author)

A comprehensive survey of wearable and wireless ECG monitoring systems for older adults.

Science.gov (United States)

Baig, Mirza Mansoor; Gholamhosseini, Hamid; Connolly, Martin J

2013-05-01

Wearable health monitoring is an emerging technology for continuous monitoring of vital signs including the electrocardiogram (ECG). This signal is widely adopted to diagnose and assess major health risks and chronic cardiac diseases. This paper focuses on reviewing wearable ECG monitoring systems in the form of wireless, mobile and remote technologies related to older adults. Furthermore, the efficiency, user acceptability, strategies and recommendations on improving current ECG monitoring systems with an overview of the design and modelling are presented. In this paper, over 120 ECG monitoring systems were reviewed and classified into smart wearable, wireless, mobile ECG monitoring systems with related signal processing algorithms. The results of the review suggest that most research in wearable ECG monitoring systems focus on the older adults and this technology has been adopted in aged care facilitates. Moreover, it is shown that how mobile telemedicine systems have evolved and how advances in wearable wireless textile-based systems could ensure better quality of healthcare delivery. The main drawbacks of deployed ECG monitoring systems including imposed limitations on patients, short battery life, lack of user acceptability and medical professional's feedback, and lack of security and privacy of essential data have been also discussed.

Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal.

Science.gov (United States)

Wen, Haiguang; Liu, Zhongming

2016-06-01

Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels. This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed

A ECG Signal Gathering and Displaying System Based on AVR

Science.gov (United States)

Ning, Li; Ruilan, Zhang; Jian, Liu; Xiaochen, Wang; Shuying, Chen; Zhuolin, Lang

2017-12-01

This article introduces a kind of system which is based on the AVR to acquire the data of ECG. Such system using the A/D function of ATmega8 chip and the lattice graph LCD to design ECG heart acquisition satisfies the demands above. This design gives a composition of hardware and programming of software about the system in detail which has mainly realized the real-time gathering, the amplifier, the filter, the A/D transformation and the LCD display. Since the AVR includes A/D transformation function and support embedded C language programming, it reduces the peripheral circuit, further more it also decreases the time to design and debug this system.

Signal Sampling for Efficient Sparse Representation of Resting State FMRI Data

Science.gov (United States)

Ge, Bao; Makkie, Milad; Wang, Jin; Zhao, Shijie; Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhang, Shu; Zhang, Wei; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

As the size of brain imaging data such as fMRI grows explosively, it provides us with unprecedented and abundant information about the brain. How to reduce the size of fMRI data but not lose much information becomes a more and more pressing issue. Recent literature studies tried to deal with it by dictionary learning and sparse representation methods, however, their computation complexities are still high, which hampers the wider application of sparse representation method to large scale fMRI datasets. To effectively address this problem, this work proposes to represent resting state fMRI (rs-fMRI) signals of a whole brain via a statistical sampling based sparse representation. First we sampled the whole brain’s signals via different sampling methods, then the sampled signals were aggregate into an input data matrix to learn a dictionary, finally this dictionary was used to sparsely represent the whole brain’s signals and identify the resting state networks. Comparative experiments demonstrate that the proposed signal sampling framework can speed-up by ten times in reconstructing concurrent brain networks without losing much information. The experiments on the 1000 Functional Connectomes Project further demonstrate its effectiveness and superiority. PMID:26646924

Fetal QRS extraction from abdominal recordings via model-based signal processing and intelligent signal merging

International Nuclear Information System (INIS)

Haghpanahi, Masoumeh; Borkholder, David A

2014-01-01

Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother’s abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice. (paper)

IDENTIFIKASI SINYAL ECG IRAMA MYOCARDIAL ISCHEMIA DENGAN PENDEKATAN FUZZY LOGIC

Directory of Open Access Journals (Sweden)

Azhar A N

2009-07-01

Full Text Available The heart is one of vital organs in human body. Incidence of heart disease can be fatal for the patient. Myocardial ischemia, the disease that is often suffered by the human, is a disease due to clogged heart arteries blood vessels. One of the ways to detect this disease is by reading the graph output of electrocardiogram (ECG signal. ECG signal represents the condition and activity of the heart. Specialized knowledge, accuration and expertise are required to read ECG graph. To help expert or doctor, expert system based on artificial intelligent, such as Fuzzy Logic approach, can be applied to improve diagnostic accuracy and thoroughness. Fuzzy logic can be applied because of it flexibility to understand the linguistic variables used in identifying myocardial ischemia disease.

Classification of Multichannel ECG Signals Using a Cross-Distance Analysis

National Research Council Canada - National Science Library

Shahram, Morteza

2001-01-01

This paper presents a multi-stage algorithm for multi-channel ECG beat classification into normal and abnormal categories using a sequential beat clustering and a cross- distance analysis algorithm...

Functional Connectivity of Resting Hemodynamic Signals in Submillimeter Orientation Columns of the Visual Cortex.

Science.gov (United States)

Vasireddi, Anil K; Vazquez, Alberto L; Whitney, David E; Fukuda, Mitsuhiro; Kim, Seong-Gi

2016-09-07

Resting-state functional magnetic resonance imaging has been increasingly used for examining connectivity across brain regions. The spatial scale by which hemodynamic imaging can resolve functional connections at rest remains unknown. To examine this issue, deoxyhemoglobin-weighted intrinsic optical imaging data were acquired from the visual cortex of lightly anesthetized ferrets. The neural activity of orientation domains, which span a distance of 0.7-0.8 mm, has been shown to be correlated during evoked activity and at rest. We performed separate analyses to assess the degree to which the spatial and temporal characteristics of spontaneous hemodynamic signals depend on the known functional organization of orientation columns. As a control, artificial orientation column maps were generated. Spatially, resting hemodynamic patterns showed a higher spatial resemblance to iso-orientation maps than artificially generated maps. Temporally, a correlation analysis was used to establish whether iso-orientation domains are more correlated than orthogonal orientation domains. After accounting for a significant decrease in correlation as a function of distance, a small but significant temporal correlation between iso-orientation domains was found, which decreased with increasing difference in orientation preference. This dependence was abolished when using artificially synthetized orientation maps. Finally, the temporal correlation coefficient as a function of orientation difference at rest showed a correspondence with that calculated during visual stimulation suggesting that the strength of resting connectivity is related to the strength of the visual stimulation response. Our results suggest that temporal coherence of hemodynamic signals measured by optical imaging of intrinsic signals exists at a submillimeter columnar scale in resting state.

2D.03: IMPROVING DIAGNOSTIC STRATEGY IN PATIENTS WITH LONG-STANDING HYPERTENSION, CHEST PAIN AND NORMAL RESTING ECG: VALUE OF THE EXERCISE HIGH-FREQUENCY QRS VERSUS ST-SEGMENT ANALYSIS.

Science.gov (United States)

Conti, A; Bianchi, S; Grifoni, C; Trausi, F; Angeli, E; Paolini, D; Catarzi, S; Perrotta, M E; Covelli, A; Renzi, N; Bertolini, P; Mazzucchelli, M

2015-06-01

The novel exercise computer-assisted high-frequency QRS-analysis (ex-HF/QRS) has demonstrated improved sensitivity and specificity over the conventional exercise-ST/ECG-segment-analysis (ex-ST/ECG) in the detection of myocardial ischemia. The aim of the present study was to test the implementation in diagnostic value of the ex-HF/QRS in patient with hypertension and chest pain (CP) versus the conventional ex-ST/ECG anlysis alone. Patients with long-standing hypertension, CP, normal ECG, troponin and echocardiography were enrolled. All patients underwent the ex-ST/ECG and ex-HF/QRS. A decrease >/=50% of the signal of ex-HF/QRS intensity recorded in two contiguous leads, at least, was considered as index of ischaemia, as ST-segment depression >/=2 mm or >/=1 mm and CP on ex-ST/ECG. Exclusion criteria were QRS duration >/=120 msec and inability to exercise. The end-point was the composite of coronary stenosis >50% or acute coronary syndrome, revascularization, cardiovascular death at 3-month follow-up. Six-hundred thirty-one patients were enrolled (age 61+/-15 y). The percentage of age-adjusted maximal predicted heart rate was 88+/-10 beat-per-minute and the maximal systolic blood pressure was 169+/-22 mmHg. Twenty-seven patients achieved the end-point. On multivariate analysis, both the ex-ST/ECG and ex-HF/QRS were predictors of the end-point. The ex-HF/QRS showed higher sensitivity (88% vs 50%; p = 0.003), lower specificity (77% vs 97%; p = 0.245) and comparable negative predictive value (99% vs 99%; p = NS) when compared to ex-ST/ECG. Receiver operator characteristics (ROC) analysis showed the incremental diagnostic value of the ex-HF/QRS (area: 0.64, 95% Confidence Intervals, CI 0.51-0.77) over conventional ex-ST/ECG (0.60, CI 0.52-0.66) and Chest Pain Score (0.53, CI 0.48-0.59); p = NS on pairwise C-statistic. In patients with long-standing hypertension and CP submitted to risk stratification with exercise tolerance test, the novel ex

An ECG simulator for generating maternal-foetal activity mixtures on abdominal ECG recordings

International Nuclear Information System (INIS)

Behar, Joachim; Andreotti, Fernando; Li, Qiao; Oster, Julien; Clifford, Gari D; Zaunseder, Sebastian

2014-01-01

Accurate foetal electrocardiogram (FECG) morphology extraction from non-invasive sensors remains an open problem. This is partly due to the paucity of available public databases. Even when gold standard information (i.e derived from the scalp electrode) is present, the collection of FECG can be problematic, particularly during stressful or clinically important events. In order to address this problem we have introduced an FECG simulator based on earlier work on foetal and adult ECG modelling. The open source foetal ECG synthetic simulator, fecgsyn, is able to generate maternal-foetal ECG mixtures with realistic amplitudes, morphology, beat-to-beat variability, heart rate changes and noise. Positional (rotation and translation-related) movements in the foetal and maternal heart due to respiration, foetal activity and uterine contractions were also added to the simulator. The simulator was used to generate some of the signals that were part of the 2013 PhysioNet Computing in Cardiology Challenge dataset and has been posted on Physionet.org (together with scripts to generate realistic scenarios) under an open source license. The toolbox enables further research in the field and provides part of a standard for industry and regulatory testing of rare pathological scenarios. (paper)

Labview Based ECG Patient Monitoring System for Cardiovascular Patient Using SMTP Technology.

Science.gov (United States)

Singh, Om Prakash; Mekonnen, Dawit; Malarvili, M B

2015-01-01

This paper leads to developing a Labview based ECG patient monitoring system for cardiovascular patient using Simple Mail Transfer Protocol technology. The designed device has been divided into three parts. First part is ECG amplifier circuit, built using instrumentation amplifier (AD620) followed by signal conditioning circuit with the operation amplifier (lm741). Secondly, the DAQ card is used to convert the analog signal into digital form for the further process. Furthermore, the data has been processed in Labview where the digital filter techniques have been implemented to remove the noise from the acquired signal. After processing, the algorithm was developed to calculate the heart rate and to analyze the arrhythmia condition. Finally, SMTP technology has been added in our work to make device more communicative and much more cost-effective solution in telemedicine technology which has been key-problem to realize the telediagnosis and monitoring of ECG signals. The technology also can be easily implemented over already existing Internet.

Deployment of an Advanced Electrocardiographic Analysis (A-ECG) to Detect Cardiovascular Risk in Career Firefighters

Science.gov (United States)

Dolezal, B. A.; Storer, T. W.; Abrazado, M.; Watne, R.; Schlegel, T. T.; Batalin, M.; Kaiser, W.; Smith, D. L.; Cooper, C. B.

2011-01-01

INTRODUCTION Sudden cardiac death is the leading cause of line of duty death among firefighters, accounting for approximately 45% of fatalities annually. Firefighters perform strenuous muscular work while wearing heavy, encapsulating personal protective equipment in high ambient temperatures, under chaotic and emotionally stressful conditions. These factors can precipitate sudden cardiac events like myocardial infarction, serious dysrhythmias, or cerebrovascular accidents in firefighters with underlying cardiovascular disease. Screening for cardiovascular risk factors is recommended but not always followed in this population. PHASER is a project charged with identifying and prioritizing risk factors in emergency responders. We have deployed an advanced ECG (A-ECG) system developed at NASA for improved sensitivity and specificity in the detection of cardiac risk. METHODS Forty-four professional firefighters were recruited to perform comprehensive baseline assessments including tests of aerobic performance and laboratory tests for fasting lipid profiles and glucose. Heart rate and conventional 12-lead ECG were obtained at rest and during incremental treadmill exercise testing (XT). In addition, a 5-min resting 12-lead A-ECG was obtained in a subset of firefighters (n=18) and transmitted over a secure networked system to a physician collaborator at NASA for advanced-ECG analysis. This A-ECG system has been proven, using myocardial perfusion and other imaging, to accurately identify a number of cardiac pathologies including coronary artery disease (CAD), left ventricular hypertrophy, hypertrophic cardiomyopathy, non-ischemic cardiomyopathy, and ischemic cardiomyopathy. RESULTS Subjects mean (SD) age was 43 (8) years, weight 91 (13) kg, and BMI of 28 (3) kg/square meter. Maximum oxygen uptake (VO2max) was 39 (9) ml/kg/min. This compares with the 45th %ile in healthy reference values and a recommended standard of 42 ml/kg/min for firefighters. The metabolic threshold (VO

Biometric and Emotion Identification: An ECG Compression Based Method.

Science.gov (United States)

Brás, Susana; Ferreira, Jacqueline H T; Soares, Sandra C; Pinho, Armando J

2018-01-01

We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

Science.gov (United States)

Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

2009-02-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

Labview Based ECG Patient Monitoring System for Cardiovascular Patient Using SMTP Technology

OpenAIRE

Singh, Om Prakash; Mekonnen, Dawit; Malarvili, M. B.

2015-01-01

This paper leads to developing a Labview based ECG patient monitoring system for cardiovascular patient using Simple Mail Transfer Protocol technology. The designed device has been divided into three parts. First part is ECG amplifier circuit, built using instrumentation amplifier (AD620) followed by signal conditioning circuit with the operation amplifier (lm741). Secondly, the DAQ card is used to convert the analog signal into digital form for the further process. Furthermore, the data has ...

Challenges of ECG monitoring and ECG interpretation in dialysis units.

Science.gov (United States)

Poulikakos, Dimitrios; Malik, Marek

Patients on hemodialysis (HD) suffer from high cardiovascular morbidity and mortality due to high rates of coronary artery disease and arrhythmias. Electrocardiography (ECG) is often performed in the dialysis units as part of routine clinical assessment. However, fluid and electrolyte changes have been shown to affect all ECG morphologies and intervals. ECG interpretation thus depends on the time of the recording in relation to the HD session. In addition, arrhythmias during HD are common, and dialysis-related ECG artifacts mimicking arrhythmias have been reported. Studies using advanced ECG analyses have examined the impact of the HD procedure on selected repolarization descriptors and heart rate variability indices. Despite the challenges related to the impact of the fluctuant fluid and electrolyte status on conventional and advanced ECG parameters, further research in ECG monitoring during dialysis has the potential to provide clinically meaningful and practically useful information for diagnostic and risk stratification purposes. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Washable and Reliable Textile Electrodes Embedded into Underwear Fabric for Electrocardiography (ECG Monitoring

Directory of Open Access Journals (Sweden)

Amale Ankhili

2018-02-01

Full Text Available A medical quality electrocardiogram (ECG signal is necessary for permanent monitoring, and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The article focuses on textile electrode design and production guaranteeing optimal contact impedance. Therefore, different types of textile fabrics were coated with modified poly(3,4-ethylenedioxythiophene:poly(styrenesulfonate (PEDOT:PSS in order to develop and manufacture reliable and washable textile electrodes assembled to female underwear (bras, by sewing using commercially available conductive yarns. Washability tests of connected underwear containing textile electrodes and conductive threads were carried out up to 50 washing cycles. The influence of standardized washing cycles on the quality of ECG signals and the electrical properties of the textile electrodes were investigated and characterized.

Washable and Reliable Textile Electrodes Embedded into Underwear Fabric for Electrocardiography (ECG) Monitoring.

Science.gov (United States)

Ankhili, Amale; Tao, Xuyuan; Cochrane, Cédric; Coulon, David; Koncar, Vladan

2018-02-07

A medical quality electrocardiogram (ECG) signal is necessary for permanent monitoring, and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The article focuses on textile electrode design and production guaranteeing optimal contact impedance. Therefore, different types of textile fabrics were coated with modified poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) in order to develop and manufacture reliable and washable textile electrodes assembled to female underwear (bras), by sewing using commercially available conductive yarns. Washability tests of connected underwear containing textile electrodes and conductive threads were carried out up to 50 washing cycles. The influence of standardized washing cycles on the quality of ECG signals and the electrical properties of the textile electrodes were investigated and characterized.

A sub-nJ CMOS ECG classifier for wireless smart sensor.

Science.gov (United States)

Chollet, Paul; Pallas, Remi; Lahuec, Cyril; Arzel, Matthieu; Seguin, Fabrice

2017-07-01

Body area sensor networks hold the promise of more efficient and cheaper medical care services through the constant monitoring of physiological markers such as heart beats. Continuously transmitting the electrocardiogram (ECG) signal requires most of the wireless ECG sensor energy budget. This paper presents the analog implantation of a classifier for ECG signals that can be embedded onto a sensor. The classifier is a sparse neural associative memory. It is implemented using the ST 65 nm CMOS technology and requires only 234 pJ per classification while achieving a 93.6% classification accuracy. The energy requirement is 6 orders of magnitude lower than a digital accelerator that performs a similar task. The lifespan of the resulting sensor is 191 times as large as that of a sensor sending all the data.

Heart rhythm analysis using ECG recorded with a novel sternum based patch technology

DEFF Research Database (Denmark)

Saadi, Dorthe Bodholt; Fauerskov, Inge; Osmanagic, Armin

2013-01-01

, reliable long-term ECG recordings. The device is designed for high compliance and low patient burden. This novel patch technology is CE approved for ambulatory ECG recording of two ECG channels on the sternum. This paper describes a clinical pilot study regarding the usefulness of these ECG signals...... for heart rhythm analysis. A clinical technician with experience in ECG interpretation selected 200 noise-free 7 seconds ECG segments from 25 different patients. These 200 ECG segments were evaluated by two medical doctors according to their usefulness for heart rhythm analysis. The first doctor considered...... 98.5% of the segments useful for rhythm analysis, whereas the second doctor considered 99.5% of the segments useful for rhythm analysis. The conclusion of this pilot study indicates that two channel ECG recorded on the sternum is useful for rhythm analysis and could be used as input to diagnosis...

FPGA compression of ECG signals by using modified convolution scheme of the Discrete Wavelet Transform Compresión de señales ECG sobre FPGA utilizando un esquema modificado de convolución de la Transformada Wavelet Discreta

Directory of Open Access Journals (Sweden)

Dora M Ballesteros

2012-04-01

Full Text Available This paper presents FPGA design of ECG compression by using the Discrete Wavelet Transform (DWT and one lossless encoding method. Unlike the classical works based on off-line mode, the current work allows the real-time processing of the ECG signal to reduce the redundant information. A model is developed for a fixed-point convolution scheme which has a good performance in relation to the throughput, the latency, the maximum frequency of operation and the quality of the compressed signal. The quantization of the coefficients of the filters and the selected fixed-threshold give a low error in relation to clinical applications.Este documento presenta el diseño basado en FPGA para la compresión de señales ECG utilizando la Transformada Wavelet Discreta y un método de codificación sin pérdida de información. A diferencia de los trabajos clásicos para modo off-line, el trabajo actual permite la compresión en tiempo real de la señal ECG por medio de la reducción de la información redundante. Se propone un modelo para el esquema de convolución en formato punto fijo, el cual tiene buen desempeño en relación a la tasa de salida, la latencia del sistema, la máxima frecuencia de operación y la calidad de la señal comprimida. La arquitectura propuesta, la cuantización utilizada y el método de codificación proporcionan un PRD que es apto para el análisis clínico.

WaveformECG: A Platform for Visualizing, Annotating, and Analyzing ECG Data.

Science.gov (United States)

Winslow, Raimond L; Granite, Stephen; Jurado, Christian

2016-01-01

The electrocardiogram (ECG) is the most commonly collected data in cardiovascular research because of the ease with which it can be measured and because changes in ECG waveforms reflect underlying aspects of heart disease. Accessed through a browser, WaveformECG is an open source platform supporting interactive analysis, visualization, and annotation of ECGs.

Biometric and Emotion Identification: An ECG Compression Based Method

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Susana Brás

2018-04-01

Full Text Available We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG. The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1 conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2 conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3 identification of the ECG record class, using a 1-NN (nearest neighbor classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.

Biometric and Emotion Identification: An ECG Compression Based Method

Science.gov (United States)

Brás, Susana; Ferreira, Jacqueline H. T.; Soares, Sandra C.; Pinho, Armando J.

2018-01-01

We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model. PMID:29670564

A novel application of deep learning for single-lead ECG classification.

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Mathews, Sherin M; Kambhamettu, Chandra; Barner, Kenneth E

2018-06-04

Detecting and classifying cardiac arrhythmias is critical to the diagnosis of patients with cardiac abnormalities. In this paper, a novel approach based on deep learning methodology is proposed for the classification of single-lead electrocardiogram (ECG) signals. We demonstrate the application of the Restricted Boltzmann Machine (RBM) and deep belief networks (DBN) for ECG classification following detection of ventricular and supraventricular heartbeats using single-lead ECG. The effectiveness of this proposed algorithm is illustrated using real ECG signals from the widely-used MIT-BIH database. Simulation results demonstrate that with a suitable choice of parameters, RBM and DBN can achieve high average recognition accuracies of ventricular ectopic beats (93.63%) and of supraventricular ectopic beats (95.57%) at a low sampling rate of 114 Hz. Experimental results indicate that classifiers built into this deep learning-based framework achieved state-of-the art performance models at lower sampling rates and simple features when compared to traditional methods. Further, employing features extracted at a sampling rate of 114 Hz when combined with deep learning provided enough discriminatory power for the classification task. This performance is comparable to that of traditional methods and uses a much lower sampling rate and simpler features. Thus, our proposed deep neural network algorithm demonstrates that deep learning-based methods offer accurate ECG classification and could potentially be extended to other physiological signal classifications, such as those in arterial blood pressure (ABP), nerve conduction (EMG), and heart rate variability (HRV) studies. Copyright © 2018. Published by Elsevier Ltd.

Closed-Loop Control of Humidification for Artifact Reduction in Capacitive ECG Measurements.

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Leicht, Lennart; Eilebrecht, Benjamin; Weyer, Soren; Leonhardt, Steffen; Teichmann, Daniel

2017-04-01

Recording biosignals without the need for direct skin contact offers new opportunities for ubiquitous health monitoring. Electrodes with capacitive coupling have been shown to be suitable for the monitoring of electrical potentials on the body surface, in particular ECG. However, due to triboelectric charge generation and motion artifacts, signal and thus diagnostic quality is inferior to galvanic coupling. Active closed-loop humidification of capacitive electrodes is proposed in this work as a new concept to improve signal quality. A capacitive ECG recording system integrated into a common car seat is presented. It can regulate the micro climate at the interface of electrode and patient by actively dispensing water vapour and monitoring humidity in a closed-loop approach. As a regenerative water reservoir, silica gel is used. The system was evaluated with respect to subjective and objective ECG signal quality. Active humidification was found to have a significant positive effect in case of previously poor quality. Also, it had no diminishing effect in case of already good signal quality.

A 58 nW ECG ASIC With Motion-Tolerant Heartbeat Timing Extraction for Wearable Cardiovascular Monitoring.

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Da He, David; Sodini, Charles G

2015-06-01

An ASIC for wearable cardiovascular monitoring is implemented using a topology that takes advantage of the electrocardiogram's (ECG) waveform to replace the traditional ECG instrumentation amplifier, ADC, and signal processor with a single chip solution. The ASIC can extract heartbeat timings in the presence of baseline drift, muscle artifact, and signal clipping. The circuit can operate with ECGs ranging from the chest location to remote locations where the ECG magnitude is as low as 30 μV. Besides heartbeat detection, a midpoint estimation method can accurately extract the ECG R-wave timing, enabling the calculations of heart rate variability. With 58 nW of power consumption at 0.8 V supply voltage and 0.76 mm (2) of active die area in standard 0.18 μm CMOS technology, the ECG ASIC is sufficiently low power and compact to be suitable for long term and wearable cardiovascular monitoring applications under stringent battery and size constraints.

Prevalence and prognostic significance of ECG abnormalities in HIV-infected patients: results from the Strategies for Management of Antiretroviral Therapy study

DEFF Research Database (Denmark)

Soliman, Elsayed Z; Prineas, Ronald J; Roediger, Mollie P

2011-01-01

BACKGROUND: It remains debated whether to include resting electrocardiogram (ECG) in the routine care of human immunodeficiency virus (HIV)-infected patients. METHODS: This analysis included 4518 HIV-infected patients (28% women and 29% blacks) from the Strategies for Management of Antiretroviral...... Therapy study, a clinical trial aimed to compare 2 HIV treatment strategies. ECG abnormalities were classified using the Minnesota Code. Cox proportional hazards analysis was used to examine the association between baseline ECG abnormalities and incident cardiovascular disease (CVD). RESULTS: More than...... half of the participants (n = 2325, or 51.5%) had either minor or major ECG abnormalities. Minor ECG abnormalities (48.6%) were more common than major ECG abnormalities (7.7%). During a median follow-up of 28.7 months, 155 participants (3.4%) developed incident CVD. After adjusting for the study...

Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI.

Science.gov (United States)

Wong, Chi Wah; Olafsson, Valur; Tal, Omer; Liu, Thomas T

2012-10-15

Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state. Copyright © 2012 Elsevier Inc. All rights reserved.

Heartbeat Classification Using Abstract Features From the Abductive Interpretation of the ECG.

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Teijeiro, Tomas; Felix, Paulo; Presedo, Jesus; Castro, Daniel

2018-03-01

This paper aims to prove that automatic beat classification on ECG signals can be effectively solved with a pure knowledge-based approach, using an appropriate set of abstract features obtained from the interpretation of the physiological processes underlying the signal. A set of qualitative morphological and rhythm features are obtained for each heartbeat as a result of the abductive interpretation of the ECG. Then, a QRS clustering algorithm is applied in order to reduce the effect of possible errors in the interpretation. Finally, a rule-based classifier assigns a tag to each cluster. The method has been tested with the MIT-BIH Arrhythmia Database records, showing a significantly better performance than any other automatic approach in the state-of-the-art, and even improving most of the assisted approaches that require the intervention of an expert in the process. The most relevant issues in ECG classification, related to a large extent to the variability of the signal patterns between different subjects and even in the same subject over time, will be overcome by changing the reasoning paradigm. This paper demonstrates the power of an abductive framework for time-series interpretation to make a qualitative leap in the significance of the information extracted from the ECG by automatic methods.

Fetal ECG extraction via Type-2 adaptive neuro-fuzzy inference systems.

Science.gov (United States)

Ahmadieh, Hajar; Asl, Babak Mohammadzadeh

2017-04-01

We proposed a noninvasive method for separating the fetal ECG (FECG) from maternal ECG (MECG) by using Type-2 adaptive neuro-fuzzy inference systems. The method can extract FECG components from abdominal signal by using one abdominal channel, including maternal and fetal cardiac signals and other environmental noise signals, and one chest channel. The proposed algorithm detects the nonlinear dynamics of the mother's body. So, the components of the MECG are estimated from the abdominal signal. By subtracting estimated mother cardiac signal from abdominal signal, fetal cardiac signal can be extracted. This algorithm was applied on synthetic ECG signals generated based on the models developed by McSharry et al. and Behar et al. and also on DaISy real database. In environments with high uncertainty, our method performs better than the Type-1 fuzzy method. Specifically, in evaluation of the algorithm with the synthetic data based on McSharry model, for input signals with SNR of -5dB, the SNR of the extracted FECG was improved by 38.38% in comparison with the Type-1 fuzzy method. Also, the results show that increasing the uncertainty or decreasing the input SNR leads to increasing the percentage of the improvement in SNR of the extracted FECG. For instance, when the SNR of the input signal decreases to -30dB, our proposed algorithm improves the SNR of the extracted FECG by 71.06% with respect to the Type-1 fuzzy method. The same results were obtained on synthetic data based on Behar model. Our results on real database reflect the success of the proposed method to separate the maternal and fetal heart signals even if their waves overlap in time. Moreover, the proposed algorithm was applied to the simulated fetal ECG with ectopic beats and achieved good results in separating FECG from MECG. The results show the superiority of the proposed Type-2 neuro-fuzzy inference method over the Type-1 neuro-fuzzy inference and the polynomial networks methods, which is due to its

An Interoperable System toward Cardiac Risk Stratification from ECG Monitoring

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Cristina Soguero-Ruiz

2018-03-01

Full Text Available Many indices have been proposed for cardiovascular risk stratification from electrocardiogram signal processing, still with limited use in clinical practice. We created a system integrating the clinical definition of cardiac risk subdomains from ECGs and the use of diverse signal processing techniques. Three subdomains were defined from the joint analysis of the technical and clinical viewpoints. One subdomain was devoted to demographic and clinical data. The other two subdomains were intended to obtain widely defined risk indices from ECG monitoring: a simple-domain (heart rate turbulence (HRT, and a complex-domain (heart rate variability (HRV. Data provided by the three subdomains allowed for the generation of alerts with different intensity and nature, as well as for the grouping and scrutinization of patients according to the established processing and risk-thresholding criteria. The implemented system was tested by connecting data from real-world in-hospital electronic health records and ECG monitoring by considering standards for syntactic (HL7 messages and semantic interoperability (archetypes based on CEN/ISO EN13606 and SNOMED-CT. The system was able to provide risk indices and to generate alerts in the health records to support decision-making. Overall, the system allows for the agile interaction of research and clinical practice in the Holter-ECG-based cardiac risk domain.

An Interoperable System toward Cardiac Risk Stratification from ECG Monitoring

Science.gov (United States)

Mora-Jiménez, Inmaculada; Ramos-López, Javier; Quintanilla Fernández, Teresa; García-García, Antonio; Díez-Mazuela, Daniel; García-Alberola, Arcadi

2018-01-01

Many indices have been proposed for cardiovascular risk stratification from electrocardiogram signal processing, still with limited use in clinical practice. We created a system integrating the clinical definition of cardiac risk subdomains from ECGs and the use of diverse signal processing techniques. Three subdomains were defined from the joint analysis of the technical and clinical viewpoints. One subdomain was devoted to demographic and clinical data. The other two subdomains were intended to obtain widely defined risk indices from ECG monitoring: a simple-domain (heart rate turbulence (HRT)), and a complex-domain (heart rate variability (HRV)). Data provided by the three subdomains allowed for the generation of alerts with different intensity and nature, as well as for the grouping and scrutinization of patients according to the established processing and risk-thresholding criteria. The implemented system was tested by connecting data from real-world in-hospital electronic health records and ECG monitoring by considering standards for syntactic (HL7 messages) and semantic interoperability (archetypes based on CEN/ISO EN13606 and SNOMED-CT). The system was able to provide risk indices and to generate alerts in the health records to support decision-making. Overall, the system allows for the agile interaction of research and clinical practice in the Holter-ECG-based cardiac risk domain. PMID:29494497

A Digital Compressed Sensing-Based Energy-Efficient Single-Spot Bluetooth ECG Node

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Kan Luo

2018-01-01

Full Text Available Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing- (CS- based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic sleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power analog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the node’s specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of lay, sit, stand, walk, and run. Under using sparse binary matrix (SBM, block sparse Bayesian learning (BSBL method, and discrete cosine transform (DCT basis, all ECG signals were essentially undistorted recovered with root-mean-square differences (PRDs which are less than 6%. The proposed sleep/wake-up scheme and data compression can reduce the airtime over energy-hungry wireless links, the energy consumption of proposed node is 6.53 mJ, and the energy consumption of radio decreases 77.37%. Moreover, the energy consumption increase caused by CS code execution is negligible, which is 1.3% of the total energy consumption.

A Digital Compressed Sensing-Based Energy-Efficient Single-Spot Bluetooth ECG Node.

Science.gov (United States)

Luo, Kan; Cai, Zhipeng; Du, Keqin; Zou, Fumin; Zhang, Xiangyu; Li, Jianqing

2018-01-01

Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing- (CS-) based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic sleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power analog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the node's specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of lay, sit, stand, walk, and run. Under using sparse binary matrix (SBM), block sparse Bayesian learning (BSBL) method, and discrete cosine transform (DCT) basis, all ECG signals were essentially undistorted recovered with root-mean-square differences (PRDs) which are less than 6%. The proposed sleep/wake-up scheme and data compression can reduce the airtime over energy-hungry wireless links, the energy consumption of proposed node is 6.53 mJ, and the energy consumption of radio decreases 77.37%. Moreover, the energy consumption increase caused by CS code execution is negligible, which is 1.3% of the total energy consumption.

Revisiting QRS Detection Methodologies for Portable, Wearable, Battery-Operated, and Wireless ECG Systems

Science.gov (United States)

Elgendi, Mohamed; Eskofier, Björn; Dokos, Socrates; Abbott, Derek

2014-01-01

Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices. PMID:24409290

Electrocardiogram signal denoising based on empirical mode decomposition technique: an overview

International Nuclear Information System (INIS)

Han, G.; Lin, B.; Xu, Z.

2017-01-01

Electrocardiogram (ECG) signal is nonlinear and non-stationary weak signal which reflects whether the heart is functioning normally or abnormally. ECG signal is susceptible to various kinds of noises such as high/low frequency noises, powerline interference and baseline wander. Hence, the removal of noises from ECG signal becomes a vital link in the ECG signal processing and plays a significant role in the detection and diagnosis of heart diseases. The review will describe the recent developments of ECG signal denoising based on Empirical Mode Decomposition (EMD) technique including high frequency noise removal, powerline interference separation, baseline wander correction, the combining of EMD and Other Methods, EEMD technique. EMD technique is a quite potential and prospective but not perfect method in the application of processing nonlinear and non-stationary signal like ECG signal. The EMD combined with other algorithms is a good solution to improve the performance of noise cancellation. The pros and cons of EMD technique in ECG signal denoising are discussed in detail. Finally, the future work and challenges in ECG signal denoising based on EMD technique are clarified.

Electrocardiogram signal denoising based on empirical mode decomposition technique: an overview

Science.gov (United States)

Han, G.; Lin, B.; Xu, Z.

2017-03-01

Electrocardiogram (ECG) signal is nonlinear and non-stationary weak signal which reflects whether the heart is functioning normally or abnormally. ECG signal is susceptible to various kinds of noises such as high/low frequency noises, powerline interference and baseline wander. Hence, the removal of noises from ECG signal becomes a vital link in the ECG signal processing and plays a significant role in the detection and diagnosis of heart diseases. The review will describe the recent developments of ECG signal denoising based on Empirical Mode Decomposition (EMD) technique including high frequency noise removal, powerline interference separation, baseline wander correction, the combining of EMD and Other Methods, EEMD technique. EMD technique is a quite potential and prospective but not perfect method in the application of processing nonlinear and non-stationary signal like ECG signal. The EMD combined with other algorithms is a good solution to improve the performance of noise cancellation. The pros and cons of EMD technique in ECG signal denoising are discussed in detail. Finally, the future work and challenges in ECG signal denoising based on EMD technique are clarified.

New approach for T-wave peak detection and T-wave end location in 12-lead paced ECG signals based on a mathematical model.

Science.gov (United States)

Madeiro, João P V; Nicolson, William B; Cortez, Paulo C; Marques, João A L; Vázquez-Seisdedos, Carlos R; Elangovan, Narmadha; Ng, G Andre; Schlindwein, Fernando S

2013-08-01

This paper presents an innovative approach for T-wave peak detection and subsequent T-wave end location in 12-lead paced ECG signals based on a mathematical model of a skewed Gaussian function. Following the stage of QRS segmentation, we establish search windows using a number of the earliest intervals between each QRS offset and subsequent QRS onset. Then, we compute a template based on a Gaussian-function, modified by a mathematical procedure to insert asymmetry, which models the T-wave. Cross-correlation and an approach based on the computation of Trapezium's area are used to locate, respectively, the peak and end point of each T-wave throughout the whole raw ECG signal. For evaluating purposes, we used a database of high resolution 12-lead paced ECG signals, recorded from patients with ischaemic cardiomyopathy (ICM) in the University Hospitals of Leicester NHS Trust, UK, and the well-known QT database. The average T-wave detection rates, sensitivity and positive predictivity, were both equal to 99.12%, for the first database, and, respectively, equal to 99.32% and 99.47%, for QT database. The average time errors computed for T-wave peak and T-wave end locations were, respectively, -0.38±7.12 ms and -3.70±15.46 ms, for the first database, and 1.40±8.99 ms and 2.83±15.27 ms, for QT database. The results demonstrate the accuracy, consistency and robustness of the proposed method for a wide variety of T-wave morphologies studied. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

Myocardial scintigraphy (thallium-201) and electrocardiography at rest and during exercise in angina pectoris

International Nuclear Information System (INIS)

Minning, E.; Scharf-Bornhofen, E.; Brueggeman, Th.; Chen, T.; Barthel, W.; Bluemchen, G.; Sankt-Josef-Hospital, Oberhausen

1980-01-01

Ecg (at rest and during exercise) was compared to Thallium-201 myocardial perfusion imaging (at rest and after exercise) in 65 patients with coronary heart disease (myocardial infarction in 53 patients) and angina pectoris. These results were compared to coronary angiography and left ventricular angiography. (orig./AJ) [de

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System

Directory of Open Access Journals (Sweden)

Hongqiang Li

2016-10-01

Full Text Available Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.

Weak correlations between hemodynamic signals and ongoing neural activity during the resting state

Science.gov (United States)

Winder, Aaron T.; Echagarruga, Christina; Zhang, Qingguang; Drew, Patrick J.

2017-01-01

Spontaneous fluctuations in hemodynamic signals in the absence of a task or overt stimulation are used to infer neural activity. We tested this coupling by simultaneously measuring neural activity and changes in cerebral blood volume (CBV) in the somatosensory cortex of awake, head-fixed mice during periods of true rest, and during whisker stimulation and volitional whisking. Here we show that neurovascular coupling was similar across states, and large spontaneous CBV changes in the absence of sensory input were driven by volitional whisker and body movements. Hemodynamic signals during periods of rest were weakly correlated with neural activity. Spontaneous fluctuations in CBV and vessel diameter persisted when local neural spiking and glutamatergic input was blocked, and during blockade of noradrenergic receptors, suggesting a non-neuronal origin for spontaneous CBV fluctuations. Spontaneous hemodynamic signals reflect a combination of behavior, local neural activity, and putatively non-neural processes. PMID:29184204

Dynamic segmentation and linear prediction for maternal ECG removal in antenatal abdominal recordings

International Nuclear Information System (INIS)

Vullings, R; Sluijter, R J; Mischi, M; Bergmans, J W M; Peters, C H L; Oei, S G

2009-01-01

Monitoring the fetal heart rate (fHR) and fetal electrocardiogram (fECG) during pregnancy is important to support medical decision making. Before labor, the fHR is usually monitored using Doppler ultrasound. This method is inaccurate and therefore of limited clinical value. During labor, the fHR can be monitored more accurately using an invasive electrode; this method also enables monitoring of the fECG. Antenatally, the fECG and fHR can also be monitored using electrodes on the maternal abdomen. The signal-to-noise ratio of these recordings is, however, low, the maternal electrocardiogram (mECG) being the main interference. Existing techniques to remove the mECG from these non-invasive recordings are insufficiently accurate or do not provide all spatial information of the fECG. In this paper a new technique for mECG removal in antenatal abdominal recordings is presented. This technique operates by the linear prediction of each separate wave in the mECG. Its performance in mECG removal and fHR detection is evaluated by comparison with spatial filtering, adaptive filtering, template subtraction and independent component analysis techniques. The new technique outperforms the other techniques in both mECG removal and fHR detection (by more than 3%)

Continuous and Cuffless Blood Pressure Monitoring Based on ECG and SpO2 Signals ByUsing Microsoft Visual C Sharp.

Science.gov (United States)

Younessi Heravi, M A; Khalilzadeh, M A; Joharinia, S

2014-03-01

One of the main problems especially in operating room and monitoring devices is measurement of Blood Pressure (BP) by sphygmomanometer cuff. Objective :In this study we designed a new method to measure BP changes continuously for detecting information between cuff inflation times by using vital signals in monitoring devices. This will be achieved by extraction of the time difference between each cardiac cycle and a relative pulse wave. Finger pulse and ECG signals in lead I were recorded by a monitoring device. The output of monitoring device wasinserted in a computer by serial network communication. A software interface (Microsoft Visual C#.NET ) was used to display and process the signals in the computer. Time difference between each cardiac cycle and pulse signal was calculated throughout R wave detection in ECG and peak of pulse signal by the software. The relation between time difference in two waves and BP was determined then the coefficients of equation were obtained in different physical situations. The results of estimating BP were compared with the results of sphygmomanometer method and the error rate was calculated. In this study, 25 subjects participated among them 15 were male and 10 were female. The results showed that BP was linearly related to time difference. Average of coefficient correlation was 0.9±0.03 for systolic and 0.82±0.04 for diastolic blood pressure. The highest error percentage was calculated 8% for male and 11% for female group. Significant difference was observed between the different physical situation and arm movement changes. The relationship between time difference and age was estimated in a linear relationship with a correlation coefficient of 0.76. By determining linear relation values with high accuracy, BP can be measured with insignificant error. Therefore it can be suggested as a new method to measure the blood pressure continuously.

Electrocardiogram signal denoising based on a new improved wavelet thresholding

Science.gov (United States)

Han, Guoqiang; Xu, Zhijun

2016-08-01

Good quality electrocardiogram (ECG) is utilized by physicians for the interpretation and identification of physiological and pathological phenomena. In general, ECG signals may mix various noises such as baseline wander, power line interference, and electromagnetic interference in gathering and recording process. As ECG signals are non-stationary physiological signals, wavelet transform is investigated to be an effective tool to discard noises from corrupted signals. A new compromising threshold function called sigmoid function-based thresholding scheme is adopted in processing ECG signals. Compared with other methods such as hard/soft thresholding or other existing thresholding functions, the new algorithm has many advantages in the noise reduction of ECG signals. It perfectly overcomes the discontinuity at ±T of hard thresholding and reduces the fixed deviation of soft thresholding. The improved wavelet thresholding denoising can be proved to be more efficient than existing algorithms in ECG signal denoising. The signal to noise ratio, mean square error, and percent root mean square difference are calculated to verify the denoising performance as quantitative tools. The experimental results reveal that the waves including P, Q, R, and S waves of ECG signals after denoising coincide with the original ECG signals by employing the new proposed method.

Implementation of a wireless ECG acquisition SoC for IEEE 802.15.4 (ZigBee) applications.

Science.gov (United States)

Wang, Liang-Hung; Chen, Tsung-Yen; Lin, Kuang-Hao; Fang, Qiang; Lee, Shuenn-Yuh

2015-01-01

This paper presents a wireless biosignal acquisition system-on-a-chip (WBSA-SoC) specialized for electrocardiogram (ECG) monitoring. The proposed system consists of three subsystems, namely, 1) the ECG acquisition node, 2) the protocol for standard IEEE 802.15.4 ZigBee system, and 3) the RF transmitter circuits. The ZigBee protocol is adopted for wireless communication to achieve high integration, applicability, and portability. A fully integrated CMOS RF front end containing a quadrature voltage-controlled oscillator and a 2.4-GHz low-IF (i.e., zero-IF) transmitter is employed to transmit ECG signals through wireless communication. The low-power WBSA-SoC is implemented by the TSMC 0.18-μm standard CMOS process. An ARM-based displayer with FPGA demodulation and an RF receiver with analog-to-digital mixed-mode circuits are constructed as verification platform to demonstrate the wireless ECG acquisition system. Measurement results on the human body show that the proposed SoC can effectively acquire ECG signals.

Non-invasive Drosophila ECG recording by using eutectic gallium-indium alloy electrode: a feasible tool for future research on the molecular mechanisms involved in cardiac arrhythmia.

Directory of Open Access Journals (Sweden)

Po-Hung Kuo

Full Text Available BACKGROUND: Drosophila heart tube is a feasible model for cardiac physiological research. However, obtaining Drosophila electrocardiograms (ECGs is difficult, due to the weak signals and limited contact area to apply electrodes. This paper presents a non-invasive Gallium-Indium (GaIn based recording system for Drosophila ECG measurement, providing the heart rate and heartbeat features to be observed. This novel, high-signal-quality system prolongs the recording time of insect ECGs, and provides a feasible platform for research on the molecular mechanisms involved in cardiovascular diseases. METHODS: In this study, two types of electrode, tungsten needle probes and GaIn electrodes, were used respectively to noiselessly conduct invasive and noninvasive ECG recordings of Drosophila. To further analyze electrode properties, circuit models were established and simulated. By using electromagnetic shielded heart signal acquiring system, consisted of analog amplification and digital filtering, the ECG signals of three phenotypes that have different heart functions were recorded without dissection. RESULTS AND DISCUSSION: The ECG waveforms of different phenotypes of Drosophila recorded invasively and repeatedly with n value (n>5 performed obvious difference in heart rate. In long period ECG recordings, non-invasive method implemented by GaIn electrodes acts relatively stable in both amplitude and period. To analyze GaIn electrode, the correctness of GaIn electrode model established by this paper was validated, presenting accuracy, stability, and reliability. CONCLUSIONS: Noninvasive ECG recording by GaIn electrodes was presented for recording Drosophila pupae ECG signals within a limited contact area and signal strength. Thus, the observation of ECG changes in normal and SERCA-depleted Drosophila over an extended period is feasible. This method prolongs insect survival time while conserving major ECG features, and provides a platform for

Biosignal integrated circuit with simultaneous acquisition of ECG and PPG for wearable healthcare applications.

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Kim, Hyungseup; Park, Yunjong; Ko, Youngwoon; Mun, Yeongjin; Lee, Sangmin; Ko, Hyoungho

2018-01-01

Wearable healthcare systems require measurements from electrocardiograms (ECGs) and photoplethysmograms (PPGs), and the blood pressure of the user. The pulse transit time (PTT) can be calculated by measuring the ECG and PPG simultaneously. Continuous-time blood pressure without using an air cuff can be estimated by using the PTT. This paper presents a biosignal acquisition integrated circuit (IC) that can simultaneously measure the ECG and PPG for wearable healthcare applications. Included in this biosignal acquisition circuit are a voltage mode instrumentation amplifier (IA) for ECG acquisition and a current mode transimpedance amplifier for PPG acquisition. The analog outputs from the ECG and PPG channels are muxed and converted to digital signals using 12-bit successive approximation register (SAR) analog-to-digital converter (ADC). The proposed IC is fabricated by using a standard 0.18 μm CMOS process with an active area of 14.44 mm2. The total current consumption for the multichannel IC is 327 μA with a 3.3 V supply. The measured input referred noise of ECG readout channel is 1.3 μVRMS with a bandwidth of 0.5 Hz to 100 Hz. And the measured input referred current noise of the PPG readout channel is 0.122 nA/√Hz with a bandwidth of 0.5 Hz to 100 Hz. The proposed IC, which is implemented using various circuit techniques, can measure ECG and PPG signals simultaneously to calculate the PTT for wearable healthcare applications.

ECG-derived respiration methods: adapted ICA and PCA.

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Tiinanen, Suvi; Noponen, Kai; Tulppo, Mikko; Kiviniemi, Antti; Seppänen, Tapio

2015-05-01

Respiration is an important signal in early diagnostics, prediction, and treatment of several diseases. Moreover, a growing trend toward ambulatory measurements outside laboratory environments encourages developing indirect measurement methods such as ECG derived respiration (EDR). Recently, decomposition techniques like principal component analysis (PCA), and its nonlinear version, kernel PCA (KPCA), have been used to derive a surrogate respiration signal from single-channel ECG. In this paper, we propose an adapted independent component analysis (AICA) algorithm to obtain EDR signal, and extend the normal linear PCA technique based on the best principal component (PC) selection (APCA, adapted PCA) to improve its performance further. We also demonstrate that the usage of smoothing spline resampling and bandpass-filtering improve the performance of all EDR methods. Compared with other recent EDR methods using correlation coefficient and magnitude squared coherence, the proposed AICA and APCA yield a statistically significant improvement with correlations 0.84, 0.82, 0.76 and coherences 0.90, 0.91, 0.85 between reference respiration and AICA, APCA and KPCA, respectively. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Improving ECG Services at a Children’s Hospital: Implementation of a Digital ECG System

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Frank A. Osei

2015-01-01

Full Text Available Background. The use of digital ECG software and services is becoming common. We hypothesized that the introduction of a completely digital ECG system would increase the volume of ECGs interpreted at our children’s hospital. Methods. As part of a hospital wide quality improvement initiative, a digital ECG service (MUSE, GE was implemented at the Children’s Hospital at Montefiore in June 2012. The total volume of ECGs performed in the first 6 months of the digital ECG era was compared to 18 months of the predigital era. Predigital and postdigital data were compared via t-tests. Results. The mean ECGs interpreted per month were 53 ± 16 in the predigital era and 216 ± 37 in the postdigital era (p<0.001, a fourfold increase in ECG volume after introduction of the digital system. There was no significant change in inpatient or outpatient service volume during that time. The mean billing time decreased from 21 ± 27 days in the postdigital era to 12 ± 5 days in the postdigital era (p<0.001. Conclusion. Implementation of a digital ECG system increased the volume of ECGs officially interpreted and reported.

MYBPC3 hypertrophic cardiomyopathy can be detected by using advanced ECG in children and young adults.

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Fernlund, E; Liuba, P; Carlson, J; Platonov, P G; Schlegel, T T

2016-01-01

The conventional ECG is commonly used to screen for hypertrophic cardiomyopathy (HCM), but up to 25% of adults and possibly larger percentages of children with HCM have no distinctive abnormalities on the conventional ECG, whereas 5 to 15% of healthy young athletes do. Recently, a 5-min resting advanced 12-lead ECG test ("A-ECG score") showed superiority to pooled criteria from the strictly conventional ECG in correctly identifying adult HCM. The purpose of this study was to evaluate whether in children and young adults, A-ECG scoring could detect echocardiographic HCM associated with the MYBPC3 genetic mutation with greater sensitivity than conventional ECG criteria and distinguish healthy young controls and athletes from persons with MYBPC3 HCM with greater specificity. Five-minute 12-lead ECGs were obtained from 15 young patients (mean age 13.2years, range 0-30years) with MYBPC3 mutation and phenotypic HCM. The conventional and A-ECG results of these patients were compared to those of 198 healthy children and young adults (mean age 13.2, range 1month-30years) with unremarkable echocardiograms, and to those of 36 young endurance-trained athletes, 20 of whom had athletic (physiologic) left ventricular hypertrophy. Compared with commonly used, age-specific pooled criteria from the conventional ECG, a retrospectively generated A-ECG score incorporating results from just 2 derived vectorcardiographic parameters (spatial QRS-T angle and the change in the vectorcardiographic QRS azimuth angle from the second to the third eighth of the QRS interval) increased the sensitivity of ECG for identifying MYBPC3 HCM from 46% to 87% (pyoung endurance-trained athletes (100% vs. 69% for conventional ECG criteria, pyoung adults, a 2-parameter 12-lead A-ECG score is retrospectively significantly more sensitive and specific than pooled, age-specific conventional ECG criteria for detecting MYBPC3-HCM and in distinguishing such patients from healthy controls, including endurance

An Advanced Bio-Inspired PhotoPlethysmoGraphy (PPG) and ECG Pattern Recognition System for Medical Assessment.

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Rundo, Francesco; Conoci, Sabrina; Ortis, Alessandro; Battiato, Sebastiano

2018-01-30

Physiological signals are widely used to perform medical assessment for monitoring an extensive range of pathologies, usually related to cardio-vascular diseases. Among these, both PhotoPlethysmoGraphy (PPG) and Electrocardiography (ECG) signals are those more employed. PPG signals are an emerging non-invasive measurement technique used to study blood volume pulsations through the detection and analysis of the back-scattered optical radiation coming from the skin. ECG is the process of recording the electrical activity of the heart over a period of time using electrodes placed on the skin. In the present paper we propose a physiological ECG/PPG "combo" pipeline using an innovative bio-inspired nonlinear system based on a reaction-diffusion mathematical model, implemented by means of the Cellular Neural Network (CNN) methodology, to filter PPG signal by assigning a recognition score to the waveforms in the time series. The resulting "clean" PPG signal exempts from distortion and artifacts is used to validate for diagnostic purpose an EGC signal simultaneously detected for a same patient. The multisite combo PPG-ECG system proposed in this work overpasses the limitations of the state of the art in this field providing a reliable system for assessing the above-mentioned physiological parameters and their monitoring over time for robust medical assessment. The proposed system has been validated and the results confirmed the robustness of the proposed approach.

An optimized compression algorithm for real-time ECG data transmission in wireless network of medical information systems.

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Cho, Gyoun-Yon; Lee, Seo-Joon; Lee, Tae-Ro

2015-01-01

Recent medical information systems are striving towards real-time monitoring models to care patients anytime and anywhere through ECG signals. However, there are several limitations such as data distortion and limited bandwidth in wireless communications. In order to overcome such limitations, this research focuses on compression. Few researches have been made to develop a specialized compression algorithm for ECG data transmission in real-time monitoring wireless network. Not only that, recent researches' algorithm is not appropriate for ECG signals. Therefore this paper presents a more developed algorithm EDLZW for efficient ECG data transmission. Results actually showed that the EDLZW compression ratio was 8.66, which was a performance that was 4 times better than any other recent compression method widely used today.

REST/NRSF Knockdown Alters Survival, Lineage Differentiation and Signaling in Human Embryonic Stem Cells.

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Kaushali Thakore-Shah

Full Text Available REST (RE1 silencing transcription factor, also known as NRSF (neuron-restrictive silencer factor, is a well-known transcriptional repressor of neural genes in non-neural tissues and stem cells. Dysregulation of REST activity is thought to play a role in diverse diseases including epilepsy, cancer, Down's syndrome and Huntington's disease. The role of REST/NRSF in control of human embryonic stem cell (hESC fate has never been examined. To evaluate the role of REST in hESCs we developed an inducible REST knockdown system and examined both growth and differentiation over short and long term culture. Interestingly, we have found that altering REST levels in multiple hESC lines does not result in loss of self-renewal but instead leads to increased survival. During differentiation, REST knockdown resulted in increased MAPK/ERK and WNT signaling and increased expression of mesendoderm differentiation markers. Therefore we have uncovered a new role for REST in regulation of growth and early differentiation decisions in human embryonic stem cells.

ECG-cryptography and authentication in body area networks.

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Zhang, Zhaoyang; Wang, Honggang; Vasilakos, Athanasios V; Fang, Hua

2012-11-01

Wireless body area networks (BANs) have drawn much attention from research community and industry in recent years. Multimedia healthcare services provided by BANs can be available to anyone, anywhere, and anytime seamlessly. A critical issue in BANs is how to preserve the integrity and privacy of a person's medical data over wireless environments in a resource efficient manner. This paper presents a novel key agreement scheme that allows neighboring nodes in BANs to share a common key generated by electrocardiogram (ECG) signals. The improved Jules Sudan (IJS) algorithm is proposed to set up the key agreement for the message authentication. The proposed ECG-IJS key agreement can secure data communications over BANs in a plug-n-play manner without any key distribution overheads. Both the simulation and experimental results are presented, which demonstrate that the proposed ECG-IJS scheme can achieve better security performance in terms of serval performance metrics such as false acceptance rate (FAR) and false rejection rate (FRR) than other existing approaches. In addition, the power consumption analysis also shows that the proposed ECG-IJS scheme can achieve energy efficiency for BANs.

A robust physiology-based source separation method for QRS detection in low amplitude fetal ECG recordings

International Nuclear Information System (INIS)

Vullings, R; Bergmans, J W M; Peters, C H L; Hermans, M J M; Wijn, P F F; Oei, S G

2010-01-01

The use of the non-invasively obtained fetal electrocardiogram (ECG) in fetal monitoring is complicated by the low signal-to-noise ratio (SNR) of ECG signals. Even after removal of the predominant interference (i.e. the maternal ECG), the SNR is generally too low for medical diagnostics, and hence additional signal processing is still required. To this end, several methods for exploiting the spatial correlation of multi-channel fetal ECG recordings from the maternal abdomen have been proposed in the literature, of which principal component analysis (PCA) and independent component analysis (ICA) are the most prominent. Both PCA and ICA, however, suffer from the drawback that they are blind source separation (BSS) techniques and as such suboptimum in that they do not consider a priori knowledge on the abdominal electrode configuration and fetal heart activity. In this paper we propose a source separation technique that is based on the physiology of the fetal heart and on the knowledge of the electrode configuration. This technique operates by calculating the spatial fetal vectorcardiogram (VCG) and approximating the VCG for several overlayed heartbeats by an ellipse. By subsequently projecting the VCG onto the long axis of this ellipse, a source signal of the fetal ECG can be obtained. To evaluate the developed technique, its performance is compared to that of both PCA and ICA and to that of augmented versions of these techniques (aPCA and aICA; PCA and ICA applied on preprocessed signals) in generating a fetal ECG source signal with enhanced SNR that can be used to detect fetal QRS complexes. The evaluation shows that the developed source separation technique performs slightly better than aPCA and aICA and outperforms PCA and ICA and has the main advantage that, with respect to aPCA/PCA and aICA/ICA, it performs more robustly. This advantage renders it favorable for employment in automated, real-time fetal monitoring applications

Wireless and Non-contact ECG Measurement System – the “Aachen SmartChair”

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A. Aleksandrowicz

2007-01-01

Full Text Available This publication describes a measurement system that obtains an electrocardiogram (ECG by capacitively coupled electrodes. Fordemonstration purposes, this measurement system was integrated into an off-the-shelf office chair (so-called “Aachen SmartChair”.Whereas in usual clinical applications adhesive, conductively-coupled electrodes have to be attached to the skin, the described system is able to measure an ECG without direct skin contact through the cloth. A wireless communication module was integrated for transmitting theECG data to a PC or to an ICU patient monitor. For system validation, a classical ECG with conductive electrodes and an oxygensaturation signal (SpO2 were obtained simultaneously. Finally, system-specific problems of the presented device are discussed.

Advanced ECG in 2016: is there more than just a tracing?

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Reichlin, Tobias; Abächerli, Roger; Twerenbold, Raphael; Kühne, Michael; Schaer, Beat; Müller, Christian; Sticherling, Christian; Osswald, Stefan

2016-01-01

The 12-lead electrocardiogram (ECG) is the most frequently used technology in clinical cardiology. It is critical for evidence-based management of patients with most cardiovascular conditions, including patients with acute myocardial infarction, suspected chronic cardiac ischaemia, cardiac arrhythmias, heart failure and implantable cardiac devices. In contrast to many other techniques in cardiology, the ECG is simple, small, mobile, universally available and cheap, and therefore particularly attractive. Standard ECG interpretation mainly relies on direct visual assessment. The progress in biomedical computing and signal processing, and the available computational power offer fascinating new options for ECG analysis relevant to all fields of cardiology. Several digital ECG markers and advanced ECG technologies have shown promise in preliminary studies. This article reviews promising novel surface ECG technologies in three different fields. (1) For the detection of myocardial ischaemia and infarction, QRS morphology feature analysis, the analysis of high frequency QRS components (HF-QRS) and methods using vectorcardiography as well as ECG imaging are discussed. (2) For the identification and management of patients with cardiac arrhythmias, methods of advanced P-wave analysis are discussed and the concept of ECG imaging for noninvasive localisation of cardiac arrhythmias is presented. (3) For risk stratification of sudden cardiac death and the selection of patients for medical device therapy, several novel markers including an automated QRS-score for scar quantification, the QRS-T angle or the T-wave peak-to-end-interval are discussed. Despite the existing preliminary data, none of the advanced ECG markers and technologies has yet accomplished the transition into clinical practice. Further refinement of these technologies and broader validation in large unselected patient cohorts are the critical next step needed to facilitate translation of advanced ECG technologies

Simultaneous ECG-gated PET imaging of multiple mice

International Nuclear Information System (INIS)

Seidel, Jurgen; Bernardo, Marcelino L.; Wong, Karen J.; Xu, Biying; Williams, Mark R.; Kuo, Frank; Jagoda, Elaine M.; Basuli, Falguni; Li, Changhui; Griffiths, Gary L.

2014-01-01

Introduction: We describe and illustrate a method for creating ECG-gated PET images of the heart for each of several mice imaged at the same time. The method is intended to increase “throughput” in PET research studies of cardiac dynamics or to obtain information derived from such studies, e.g. tracer concentration in end-diastolic left ventricular blood. Methods: An imaging bed with provisions for warming, anesthetic delivery, etc., was fabricated by 3D printing to allow simultaneous PET imaging of two side-by-side mice. After electrode attachment, tracer injection and placement of the animals in the scanner field of view, ECG signals from each animal were continuously analyzed and independent trigger markers generated whenever an R-wave was detected in each signal. PET image data were acquired in “list” mode and these trigger markers were inserted into this list along with the image data. Since each mouse is in a different spatial location in the FOV, sorting of these data using trigger markers first from one animal and then the other yields two independent and correctly formed ECG-gated image sequences that reflect the dynamical properties of the heart during an “average” cardiac cycle. Results: The described method yields two independent ECG-gated image sequences that exhibit the expected properties in each animal, e.g. variation of the ventricular cavity volumes from maximum to minimum and back during the cardiac cycle in the processed animal with little or no variation in these volumes during the cardiac cycle in the unprocessed animal. Conclusion: ECG-gated image sequences for each of several animals can be created from a single list mode data collection using the described method. In principle, this method can be extended to more than two mice (or other animals) and to other forms of physiological gating, e.g. respiratory gating, when several subjects are imaged at the same time

Ultra-Low Voltage Sixth-Order Low Pass Filter for Sensing the T-Wave Signal in ECGs

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Panagiotis Bertsias

2014-11-01

Full Text Available An ultra-low voltage sixth-order low pass filter topology, suitable for sensing the T-wave signal in an electrocardiogram (ECG, is presented in this paper. This is realized using a cascade connection of second-order building blocks constructed from a sinh-domain two-integrator loop. The performance of the filter has been evaluated using the Cadence Analog Design Environment and the design kit provided by the Austria Mikro Systeme (AMS 0.35-µm CMOS process. The power consumption of filters was 7.21 nW, while a total harmonic distortion (THD level of 4% was observed for an input signal of 220 pA. The RMS value of the input referred noise was 0.43 pA, and the simulated value of the dynamic range (DR was 51.1 dB. A comparison with already published counterparts shows that the proposed topology offers the benefits of 0.5-V supply voltage operation and significantly improved power efficiency.

ECG Electrocardiogram (For Parents)

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... Staying Safe Videos for Educators Search English Español ECG (Electrocardiogram) KidsHealth / For Parents / ECG (Electrocardiogram) Print en ... whether there is any damage. How Is an ECG Done? There is nothing painful about getting an ...

Evaluation of Digital Compressed Sensing for Real-Time Wireless ECG System with Bluetooth low Energy.

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Wang, Yishan; Doleschel, Sammy; Wunderlich, Ralf; Heinen, Stefan

2016-07-01

In this paper, a wearable and wireless ECG system is firstly designed with Bluetooth Low Energy (BLE). It can detect 3-lead ECG signals and is completely wireless. Secondly the digital Compressed Sensing (CS) is implemented to increase the energy efficiency of wireless ECG sensor. Different sparsifying basis, various compression ratio (CR) and several reconstruction algorithms are simulated and discussed. Finally the reconstruction is done by the android application (App) on smartphone to display the signal in real time. The power efficiency is measured and compared with the system without CS. The optimum satisfying basis built by 3-level decomposed db4 wavelet coefficients, 1-bit Bernoulli random matrix and the most suitable reconstruction algorithm are selected by the simulations and applied on the sensor node and App. The signal is successfully reconstructed and displayed on the App of smartphone. Battery life of sensor node is extended from 55 h to 67 h. The presented wireless ECG system with CS can significantly extend the battery life by 22 %. With the compact characteristic and long term working time, the system provides a feasible solution for the long term homecare utilization.

Sustained Attention in Auditory and Visual Monitoring Tasks: Evaluation of the Administration of a Rest Break or Exogenous Vibrotactile Signals.

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Arrabito, G Robert; Ho, Geoffrey; Aghaei, Behzad; Burns, Catherine; Hou, Ming

2015-12-01

Performance and mental workload were observed for the administration of a rest break or exogenous vibrotactile signals in auditory and visual monitoring tasks. Sustained attention is mentally demanding. Techniques are required to improve observer performance in vigilance tasks. Participants (N = 150) monitored an auditory or a visual display for changes in signal duration in a 40-min watch. During the watch, participants were administered a rest break or exogenous vibrotactile signals. Detection accuracy was significantly greater in the auditory than in the visual modality. A short rest break restored detection accuracy in both sensory modalities following deterioration in performance. Participants experienced significantly lower mental workload when monitoring auditory than visual signals, and a rest break significantly reduced mental workload in both sensory modalities. Exogenous vibrotactile signals had no beneficial effects on performance, or mental workload. A rest break can restore performance in auditory and visual vigilance tasks. Although sensory differences in vigilance tasks have been studied, this study is the initial effort to investigate the effects of a rest break countermeasure in both auditory and visual vigilance tasks, and it is also the initial effort to explore the effects of the intervention of a rest break on the perceived mental workload of auditory and visual vigilance tasks. Further research is warranted to determine exact characteristics of effective exogenous vibrotactile signals in vigilance tasks. Potential applications of this research include procedures for decreasing the temporal decline in observer performance and the high mental workload imposed by vigilance tasks. © 2015, Her Majesty the Queen in Right of Canada, as represented by the Minister of National Defence.

Threshold-based system for noise detection in multilead ECG recordings

International Nuclear Information System (INIS)

Jekova, Irena; Krasteva, Vessela; Christov, Ivaylo; Abächerli, Roger

2012-01-01

This paper presents a system for detection of the most common noise types seen on the electrocardiogram (ECG) in order to evaluate whether an episode from 12-lead ECG is reliable for diagnosis. It implements criteria for estimation of the noise corruption level in specific frequency bands, aiming to identify the main sources of ECG quality disruption, such as missing signal or limited dynamics of the QRS components above 4 Hz; presence of high amplitude and steep artifacts seen above 1 Hz; baseline drift estimated at frequencies below 1 Hz; power–line interference in a band ±2 Hz around its central frequency; high-frequency and electromyographic noises above 20 Hz. All noise tests are designed to process the ECG series in the time domain, including 13 adjustable thresholds for amplitude and slope criteria which are evaluated in adjustable time intervals, as well as number of leads. The system allows flexible extension toward application-specific requirements for the noise levels in acceptable quality ECGs. Training of different thresholds’ settings to determine different positive noise detection rates is performed with the annotated set of 1000 ECGs from the PhysioNet database created for the Computing in Cardiology Challenge 2011. Two implementations are highlighted on the receiver operating characteristic (area 0.968) to fit to different applications. The implementation with high sensitivity (Se = 98.7%, Sp = 80.9%) appears as a reliable alarm when there are any incidental problems with the ECG acquisition, while the implementation with high specificity (Sp = 97.8%, Se = 81.8%) is less susceptible to transient problems but rather validates noisy ECGs with acceptable quality during a small portion of the recording. (paper)

Mobile Cloud-Computing-Based Healthcare Service by Noncontact ECG Monitoring

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Ee-May Fong

2013-12-01

Full Text Available Noncontact electrocardiogram (ECG measurement technique has gained popularity these days owing to its noninvasive features and convenience in daily life use. This paper presents mobile cloud computing for a healthcare system where a noncontact ECG measurement method is employed to capture biomedical signals from users. Healthcare service is provided to continuously collect biomedical signals from multiple locations. To observe and analyze the ECG signals in real time, a mobile device is used as a mobile monitoring terminal. In addition, a personalized healthcare assistant is installed on the mobile device; several healthcare features such as health status summaries, medication QR code scanning, and reminders are integrated into the mobile application. Health data are being synchronized into the healthcare cloud computing service (Web server system and Web server dataset to ensure a seamless healthcare monitoring system and anytime and anywhere coverage of network connection is available. Together with a Web page application, medical data are easily accessed by medical professionals or family members. Web page performance evaluation was conducted to ensure minimal Web server latency. The system demonstrates better availability of off-site and up-to-the-minute patient data, which can help detect health problems early and keep elderly patients out of the emergency room, thus providing a better and more comprehensive healthcare cloud computing service.

Wireless ECG and PCG Portable Telemedicine Kit for Rural Areas of Colombia

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Miguel Jimeno

2014-07-01

Full Text Available Telemedicine is always a popular topic thanks to the constants advancements of technology. The focus on development of new devices has been mainly on decreasing size to increase portability. Our research focused on improving functionality but not giving up on portability and cost. In this paper we are presenting the first prototype device that measures 4-leads electrocardiogram (ECG and phonocardiogram (PCG signals with low cost, high portability and wireless connectivity features in mind. We designed and developed a prototype that measures ECG using a standard ECG cable; we designed and developed a digital stethoscope prototype and also the necessary hardware for both medical signals to be transmitted through Bluetooth to a computer. We present here the hardware design, a new communication protocol for transmission of both signals from the device to the computer, and the software system to enable remote consultations. We designed the prototype with the main purpose of using low cost parts without sacrificing functionality, with the purpose of using it in remote zones of the Caribbean coast of Colombia. We show open issues and prepare a field implementation of the kit in the target zone.

A wavelet-based ECG delineation algorithm for 32-bit integer online processing.

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Di Marco, Luigi Y; Chiari, Lorenzo

2011-04-03

Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra.

Continuous and Cuffless Blood Pressure Monitoring Based on ECG and SpO2 Signals By Using Microsoft Visual C Sharp

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Younessi Heravi M. A.

2014-03-01

Full Text Available Background: One of the main problems especially in operating room and monitoring devices is measurement of Blood Pressure (BP by sphygmomanometer cuff. Objective: In this study we designed a new method to measure BP changes continuously for detecting information between cuff inflation times by using vital signals in monitoring devices. This will be achieved by extraction of the time difference between each cardiac cycle and a relative pulse wave. Methods: Finger pulse and ECG signals in lead I were recorded by a monitoring device. The output of monitoring device was inserted in a computer by serial network communication. A software interface (Microsoft Visual C#.NET was used to display and process the signals in the computer. Time difference between each cardiac cycle and pulse signal was calculated throughout R wave detection in ECG and peak of pulse signal by the software. The relation between time difference in two waves and BP was determined then the coefficients of equation were obtained in different physical situations. The results of estimating BP were compared with the results of sphygmomanometer method and the error rate was calculated. Results: In this study, 25 subjects participated among them 15 were male and 10 were female. The results showed that BP was linearly related to time difference. Average of coefficient correlation was 0.9±0.03 for systolic and 0.82±0.04 for diastolic blood pressure. The highest error percentage was calculated 8% for male and 11% for female group. Significant difference was observed between the different physical situation and arm movement changes. The relationship between time difference and age was estimated in a linear relationship with a correlation coefficient of 0.76. Conclusion: By determining linear relation values with high accuracy, BP can be measured with insignificant error. Therefore it can be suggested as a new method to measure the blood pressure continuously.

In hypertrophic cardiomyopathy reduction of relative resting myocardial blood flow is related to late enhancement, T2-signal and LV wall thickness.

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Katja Hueper

Full Text Available To quantify resting myocardial blood flow (MBF in the left ventricular (LV wall of HCM patients and to determine the relationship to important parameters of disease: LV wall thickness, late gadolinium enhancement (LGE, T2-signal abnormalities (dark and bright signal, LV outflow tract obstruction and age.Seventy patients with proven HCM underwent cardiac MRI. Absolute and relative resting MBF were calculated from cardiac perfusion MRI by using the Fermi function model. The relationship between relative MBF and LV wall thickness, T2-signal abnormalities (T2 dark and T2 bright signal, LGE, age and LV outflow gradient as determined by echocardiography was determined using simple and multiple linear regression analysis. Categories of reduced and elevated perfusion in relation to non- or mildly affected reference segments were defined, and T2-signal characteristics and extent as well as pattern of LGE were examined. Statistical testing included linear and logistic regression analysis, unpaired t-test, odds ratios, and Fisher's exact test.804 segments in 70 patients were included in the analysis. In a simple linear regression model LV wall thickness (p<0.001, extent of LGE (p<0.001, presence of edema, defined as focal T2 bright signal (p<0.001, T2 dark signal (p<0.001 and age (p = 0.032 correlated inversely with relative resting MBF. The LV outflow gradient did not show any effect on resting perfusion (p = 0.901. Multiple linear regression analysis revealed that LGE (p<0.001, edema (p = 0.026 and T2 dark signal (p = 0.019 were independent predictors of relative resting MBF. Segments with reduced resting perfusion demonstrated different LGE patterns compared to segments with elevated resting perfusion.In HCM resting MBF is significantly reduced depending on LV wall thickness, extent of LGE, focal T2 signal abnormalities and age. Furthermore, different patterns of perfusion in HCM patients have been defined, which may represent different stages of

Prognostic value of an electrocardiogram at rest and exercise test in patients admitted with suspected acute myocardial infarction, in whom the diagnosis is not confirmed

DEFF Research Database (Denmark)

Madsen, J K; Hommel, E; Hansen, J F

1987-01-01

. Impaired prognosis was found in patients with negative T waves or ST depression at rest or with ST--T abnormalities or angina pectoris during exercise. Patients with ST depression or elevation, Q wave or intraventricular block at rest. ST abnormalities during exercise or both constituted a high-risk group......The prognosis following discharge in 217 patients admitted with suspected acute myocardial infarction (AMI) due to chest pain, but in whom AMI was not confirmed, was related to the electrocardiogram (ECG) at rest and a symptom-limited exercise test. The patients were followed for 12 to 24 months...... in the ECG at rest and during exercise can be used to identify high and low risk patients....

201Th chloride scintiscanning in myocardial infarction - correlation with ECG findings - diagnostic potential

International Nuclear Information System (INIS)

Kostka, I.

1980-01-01

The author intended to find out in how far myocardial scintiscanning with 201 Th chloride is a necessary auxiliary investigation in diagnosing acute myocardial infarction and whether there are correlations between ECG, increase of enzyme levels, and pressure measured in the lesser circulatory system. The scintiscans were evaluated by a new method: Defect sizes were determined using a transparent template and recorded in angular degrees. Also the reduced activity was considered. Especially posterior myocardial infarctions can be localized more easily and clearly by means of myocardial scintiscanning at rest, and also infarction sizes can be judged more easily. For a diagnosis of small myocardial infarctions or in patients with a block in their ECG picture, scintiscanning is a necessary part of the diagnostic spectrum. The findings of myocardial scintiscanning correspond well with those of other methods. As for the pressure increase in the lesser circulatory system, it is well correlated with the defect size shown by the scintiscan. 201 Th scintiscanning offers a good diagnostic possibility in those myocardial infarctions where ECG findings are ambiguous. (orig./MG) [de

NInFEA: an embedded framework for the real-time evaluation of fetal ECG extraction algorithms.

Science.gov (United States)

Pani, Danilo; Barabino, Gianluca; Raffo, Luigi

2013-02-01

Fetal electrocardiogram (ECG) extraction from non-invasive biopotential recordings is a long-standing research topic. Despite the significant number of algorithms presented in the scientific literature, it is difficult to find information about embedded hardware implementations able to provide real-time support for the required features, bridging the gap between theory and practice. This article presents the NInFEA (non-invasive fetal ECG analysis) tool, an embedded hardware/software framework based on the hybrid dual-core OMAP-L137 low-power processor for the real-time evaluation of fetal ECG extraction algorithms. The hybrid platform, including a digital signal processor (DSP) and a general-purpose processor (GPP), allows achieving the best performance compared with single-core architectures. The GPP provides a portable graphical user interface, whereas the DSP is extensively used for advanced signal processing tasks. As a case study, three state-of-the-art fetal ECG extraction algorithms have been ported onto NInFEA, along with some support routines needed to provide the additional information required by the clinicians and supported by the user interface. NInFEA can be regarded both as a reference design for similar applications and as a common embedded low-power testbed for real-time fetal ECG extraction algorithms.

Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography

Directory of Open Access Journals (Sweden)

Thomas Penzel

2016-10-01

Full Text Available The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG and cardio-respiratory couplings in a chronological (historical sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave.

Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography.

Science.gov (United States)

Penzel, Thomas; Kantelhardt, Jan W; Bartsch, Ronny P; Riedl, Maik; Kraemer, Jan F; Wessel, Niels; Garcia, Carmen; Glos, Martin; Fietze, Ingo; Schöbel, Christoph

2016-01-01

The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However, their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG, and cardio-respiratory couplings in a chronological (historical) sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability (HRV) analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave).

The Telemetric and Holter ECG Warehouse Initiative (THEW): a Data Repository for the Design, Implementation and Validation of ECG-related Technologies

Science.gov (United States)

Couderc, Jean-Philippe

2011-01-01

We present an initiative supported by the National Heart Lung, and Blood Institute and the Food and Drug Administration for the development of a repository containing continuous electrocardiographic information to be shared with the worldwide scientific community. We believe that sharing data reinforces open scientific inquiry. It encourages diversity of analysis and opinion while promoting new research and facilitating the education of new researchers. In this paper, we present the resources available in this initiative for the scientific community. We describe the set of ECG signals currently hosted and we briefly discuss the associated clinical information (medical history. Disease and study-specific endpoints) and software tools we propose. Currently, the repository contains more than 250GB of data from eight clinical studies including healthy individuals and cardiac patients. This data is available for the development, implementation and validation of technologies related to body-surface ECGs. To conclude, the Telemetric and Holter ECG Warehouse (THEW) is an initiative developed to benefit the scientific community and to advance the field of quantitative electrocardiography and cardiac safety. PMID:21097349

Matrix-Inversion-Free Compressed Sensing With Variable Orthogonal Multi-Matching Pursuit Based on Prior Information for ECG Signals.

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Cheng, Yih-Chun; Tsai, Pei-Yun; Huang, Ming-Hao

2016-05-19

Low-complexity compressed sensing (CS) techniques for monitoring electrocardiogram (ECG) signals in wireless body sensor network (WBSN) are presented. The prior probability of ECG sparsity in the wavelet domain is first exploited. Then, variable orthogonal multi-matching pursuit (vOMMP) algorithm that consists of two phases is proposed. In the first phase, orthogonal matching pursuit (OMP) algorithm is adopted to effectively augment the support set with reliable indices and in the second phase, the orthogonal multi-matching pursuit (OMMP) is employed to rescue the missing indices. The reconstruction performance is thus enhanced with the prior information and the vOMMP algorithm. Furthermore, the computation-intensive pseudo-inverse operation is simplified by the matrix-inversion-free (MIF) technique based on QR decomposition. The vOMMP-MIF CS decoder is then implemented in 90 nm CMOS technology. The QR decomposition is accomplished by two systolic arrays working in parallel. The implementation supports three settings for obtaining 40, 44, and 48 coefficients in the sparse vector. From the measurement result, the power consumption is 11.7 mW at 0.9 V and 12 MHz. Compared to prior chip implementations, our design shows good hardware efficiency and is suitable for low-energy applications.

Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

Science.gov (United States)

Sharifahmadian, Ershad

2006-01-01

The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

An optimized cosine-modulated nonuniform filter bank design for subband coding of ECG signal

Directory of Open Access Journals (Sweden)

A. Kumar

2015-07-01

Full Text Available A simple iterative technique for the design of nonuniform cosine modulated filter banks (CMFBS is presented in this paper. The proposed technique employs a single parameter for optimization. The nonuniform cosine modulated filter banks are derived by merging the adjacent filters of uniform cosine modulated filter banks. The prototype filter is designed with the aid of different adjustable window functions such as Kaiser, Cosh and Exponential, and by using the constrained equiripple finite impulse response (FIR digital filter design technique. In this method, either cut off frequency or passband edge frequency is varied in order to adjust the filter coefficients so that reconstruction error could be optimized/minimized to zero. Performance and effectiveness of the proposed method in terms of peak reconstruction error (PRE, aliasing distortion (AD, computational (CPU time, and number of iteration (NOI have been shown through the numerical examples and comparative studies. Finally, the technique is exploited for the subband coding of electrocardiogram (ECG and speech signals.

Detection of Acute Myocardial Infarction in a Pig Model Using the SAN-Atrial-AVN-His (SAAH) Electrocardiogram (ECG), Model PHS-A10, an Automated and Integrated Signals Recognition System.

Science.gov (United States)

Zhao, Wenjiao; Lu, Guihua; Liu, Li; Sun, Zhishan; Wu, Mingxin; Yi, Wenyan; Chen, Haiyan; Li, Yanhui; Tang, Lilong; Zeng, Jianping

2018-03-04

BACKGROUND The aim of this study was to compare the use of the standard 12-lead electrocardiogram (ECG) with the SAN-Atrial-AVN-His (SAAH) ECG (Model PHS-A10), a new automated and integrated signals recognition system that detects micro-waveforms within the P, QRS, and T-wave, in a pig model of acute myocardial infarction (MI). MATERIAL AND METHODS Six medium-sized domestic Chinese pigs underwent general anesthesia, and an angioplasty balloon was placed and dilated for 120 minutes in the first diagonal coronary artery arising from the left anterior descending (LAD) coronary artery. A standard ECG and a SAAH ECG (Model PHS-A10) were used to evaluate: 1) the number of wavelets in ST-T segment in lead V5; 2) the duration of the repolarization initial (Ri), or duration of the wavelets starting from the J-point to the endpoint of the wavelets in the ST interval; 3) the duration of the repolarization terminal (Rt), of the wavelets, starting from the endpoint of the wavelets in the ST interval to the cross-point of the T-wave and baseline; 4) the ratio Ri: Rt. RESULTS Following coronary artery occlusion, duration of Ri and Ri/Rt increased, and Rt decreased, which was detected by the SAAH ECG (Model PHS-A10) within 12 seconds, compared with standard ECG that detected ST segment depression at 24 seconds following coronary artery occlusion. CONCLUSIONS The findings from this preliminary study in a pig model of acute MI support the need for clinical studies to evaluate the SAAH ECG (Model PHS-A10) for the early detection of acute MI.

A Wearable Healthcare System With a 13.7 μA Noise Tolerant ECG Processor.

Science.gov (United States)

Izumi, Shintaro; Yamashita, Ken; Nakano, Masanao; Kawaguchi, Hiroshi; Kimura, Hiromitsu; Marumoto, Kyoji; Fuchikami, Takaaki; Fujimori, Yoshikazu; Nakajima, Hiroshi; Shiga, Toshikazu; Yoshimoto, Masahiko

2015-10-01

To prevent lifestyle diseases, wearable bio-signal monitoring systems for daily life monitoring have attracted attention. Wearable systems have strict size and weight constraints, which impose significant limitations of the battery capacity and the signal-to-noise ratio of bio-signals. This report describes an electrocardiograph (ECG) processor for use with a wearable healthcare system. It comprises an analog front end, a 12-bit ADC, a robust Instantaneous Heart Rate (IHR) monitor, a 32-bit Cortex-M0 core, and 64 Kbyte Ferroelectric Random Access Memory (FeRAM). The IHR monitor uses a short-term autocorrelation (STAC) algorithm to improve the heart-rate detection accuracy despite its use in noisy conditions. The ECG processor chip consumes 13.7 μA for heart rate logging application.

Metabolic, respiratory, and cardiological measurements during exercise and rest

Science.gov (United States)

1971-01-01

Low concentration effects of CO2 on metabolic respiration and circulation were measured during work and at rest. The relationship between heart rate and metabolic rate is examined, as well as calibration procedures, and rate measurement during submaximal and standard exercise tests. Alterations in acid base and electrolytes were found during exhaustive exercise, including changes in ECG and metabolic alkalosis effects.

Comparison between retrospective gating and ECG triggering in magnetic resonance velocity mapping

DEFF Research Database (Denmark)

Søndergaard, L; Ståhlberg, F; Thomsen, C

1993-01-01

ECG-triggered cinematographic studies of the cardiovascular system are hampered by several technical restrictions such as the inability to image end-diastole, ghosting, varying signal intensity, and phase contributions from eddy currents. Retrospective gating may solve these problems, but involves...... of flow pulses. However, by reducing the time window retrospectively gated flow measurements were in good agreement with those that are ECG triggered. When fulfilling the demand of a narrow time window for interpolation, retrospective gating offers several advantages in MR velocity mapping....

The acquisition and retention of ECG interpretation skills after a standardized web-based ECG tutorial

DEFF Research Database (Denmark)

Rolskov Bojsen, Signe; Räder, Sune Bernd Emil Werner; Holst, Anders Gaardsdal

2015-01-01

BACKGROUND: Electrocardiogram (ECG) interpretation is of great importance for patient management. However, medical students frequently lack proficiency in ECG interpretation and rate their ECG training as inadequate. Our aim was to examine the effect of a standalone web-based ECG tutorial...... and to assess the retention of skills using multiple follow-up intervals. METHODS: 203 medical students were included in the study. All participants completed a pre-test, an ECG tutorial, and a post-test. The participants were also randomised to complete a retention-test after short (2-4 weeks), medium (10.......6), respectively). When comparing the pre-test to retention-test delta scores, junior students had learned significantly more than senior students (junior students improved 10.7 points and senior students improved 4.7 points, p = 0.003). CONCLUSION: A standalone web-based ECG tutorial can be an effective means...

Specificity of elevated intercostal space ECG recording for the type 1 Brugada ECG pattern

DEFF Research Database (Denmark)

Holst, Anders G; Tangø, Mogens; Batchvarov, Velislav

2012-01-01

Right precordial (V1-3) elevated electrode placement ECG (EEP-ECG) is often used in the diagnosis of Brugada syndrome (BrS). However, the specificity of this has only been studied in smaller studies in Asian populations. We aimed to study this in a larger European population.......Right precordial (V1-3) elevated electrode placement ECG (EEP-ECG) is often used in the diagnosis of Brugada syndrome (BrS). However, the specificity of this has only been studied in smaller studies in Asian populations. We aimed to study this in a larger European population....

An Adaptive Particle Weighting Strategy for ECG Denoising Using Marginalized Particle Extended Kalman Filter: An Evaluation in Arrhythmia Contexts.

Science.gov (United States)

Hesar, Hamed Danandeh; Mohebbi, Maryam

2017-11-01

Model-based Bayesian frameworks have a common problem in processing electrocardiogram (ECG) signals with sudden morphological changes. This situation often happens in the case of arrhythmias where ECGs do not obey the predefined state models. To solve this problem, in this paper, a model-based Bayesian denoising framework is proposed using marginalized particle-extended Kalman filter (MP-EKF), variational mode decomposition, and a novel fuzzy-based adaptive particle weighting strategy. This strategy helps MP-EKF to perform well even when the morphology of signal does not comply with the predefined dynamic model. In addition, this strategy adapts MP-EKF's behavior to the acquired measurements in different input signal to noise ratios (SNRs). At low input SNRs, this strategy decreases the particles' trust level to the measurements while increasing their trust level to a synthetic ECG constructed with the feature parameters of ECG dynamic model. At high input SNRs, the particles' trust level to the measurements is increased and the trust level to synthetic ECG is decreased. The proposed method was evaluated on MIT-BIH normal sinus rhythm database and compared with EKF/EKS frameworks and previously proposed MP-EKF. It was also evaluated on ECG segments extracted from MIT-BIH arrhythmia database, which contained ventricular and atrial arrhythmia. The results showed that the proposed algorithm had a noticeable superiority over benchmark methods from both SNR improvement and multiscale entropy based weighted distortion (MSEWPRD) viewpoints at low input SNRs.

A 1.0 V 78 mircoW reconfigurable ASIC embedded in an intelligent electrode for continuous remote ECG applications.

Science.gov (United States)

Yang, Geng; Chen, Jian; Jonsson, Fredrik; Tenhunen, Hannu; Zheng, Li-Rong

2009-01-01

In this paper, a reconfigurable, low-power Application Specific Integrated Circuit (ASIC) that extracts and transmits electrocardiograph (ECG) signals is presented. An Intelligent Electrode is introduced which consists of the proposed ASIC and a micro spike array, permitting onsite ECG signal acquisition, processing and transmission. Fabricated in a standard 0.18 microm CMOS process, the ASIC consumes 78 microW with 1.0 V core voltage at 6 MHz operating frequency and only occupies 2.25 mm(2). The tiny silicon size makes it possible and suitable to embed the proposed ASIC into an Intelligent Electrode, and the low power consumption makes it feasible for long term continuous ECG monitoring.

Spatial–temporal signature of resting-state BOLD signals in classic trigeminal neuralgia

Directory of Open Access Journals (Sweden)

Wang Y

2017-12-01

Full Text Available Yanping Wang,1 Congying Xu,1 Liping Zhai,1 Xudong Lu,1 Xiaoqiang Wu,1 Yahui Yi,2 Ziyun Liu,1 Qiaobing Guan,1 Xiaoling Zhang1 1Department of Neurology, the Second Hospital of Jiaxing City, Jiaxing, Zhejiang, 2Department of Radiology, the Second Hospital of Jiaxing City, Jiaxing, Zhejiang, China Abstract: Resting-state functional magnetic resonance imaging (R-fMRI signals are spatiotemporally organized. R-fMRI studies in patients with classic trigeminal neuralgia (CTN have suggested alterations in functional connectivity. However, far less attention has been given to investigations of the local oscillations and their frequency-specific changes in these patients. The objective of this study was to address this issue in patients with CTN. R-fMRI data from 17 patients with CTN and 19 age- and gender-matched healthy controls (HCs were analyzed using amplitude of low-frequency fluctuation (ALFF. The ALFF was computed across different frequencies (slow-4: 0.027–0.073 Hz; slow-5: 0.01–0.027 Hz; and typical band: 0.01–0.08 Hz in patients with CTN compared to HCs. In the typical band, patients with CTN showed increases of ALFF in bilateral temporal, occipital, and left middle frontal regions and in the left middle cingulate gyrus, as well as decreases of ALFF in the right inferior temporal region and in regions (medial prefrontal regions of default mode network. These significant group differences were identified in different sub-bands, with greater brainstem findings in higher frequencies (slow-4 and extensive default mode network and right postparietal results in lower frequencies (slow-5. Furthermore, significant relationships were found between subjective pain ratings and both amplitudes of higher frequency (slow-4 blood oxygen level-dependent (BOLD signals in pain localization brain regions and lower frequencies (slow-5 in pain signaling/modulating brain regions in the patients, and decreased ALFF within the prefrontal regions was significantly

Spectral analysis of 87-lead body surface signal-averaged ECGs in patients with previous anterior myocardial infarction as a marker of ventricular tachycardia.

Science.gov (United States)

Hosoya, Y; Kubota, I; Shibata, T; Yamaki, M; Ikeda, K; Tomoike, H

1992-06-01

There were few studies on the relation between the body surface distribution of high- and low-frequency components within the QRS complex and ventricular tachycardia (VT). Eighty-seven signal-averaged ECGs were obtained from 30 normal subjects (N group) and 30 patients with previous anterior myocardial infarction (MI) with VT (MI-VT[+] group, n = 10) or without VT (MI-VT[-] group, n = 20). The onset and offset of the QRS complex were determined from 87-lead root mean square values computed from the averaged (but not filtered) ECG waveforms. Fast Fourier transform analysis was performed on signal-averaged ECG. The resulting Fourier coefficients were attenuated by use of the transfer function, and then inverse transform was done with five frequency ranges (0-25, 25-40, 40-80, 80-150, and 150-250 Hz). From the QRS onset to the QRS offset, the time integration of the absolute value of reconstructed waveforms was calculated for each of the five frequency ranges. The body surface distributions of these areas were expressed as QRS area maps. The maximal values of QRS area maps were compared among the three groups. In the frequency ranges of 0-25 and 150-250 Hz, there were no significant differences in the maximal values among these three groups. Both MI groups had significantly smaller maximal values of QRS area maps in the frequency ranges of 25-40 and 40-80 Hz compared with the N group. The MI-VT(+) group had significantly smaller maximal values in the frequency ranges of 40-80 and 80-150 Hz than the MI-VT(-) group. These three groups were clearly differentiated by the maximal values of the 40-80-Hz QRS area map. It was suggested that the maximal value of the 40-80-Hz QRS area map was a new marker for VT after anterior MI.

Novel technical solutions for wireless ECG transmission & analysis in the age of the internet cloud.

Science.gov (United States)

Al-Zaiti, Salah S; Shusterman, Vladimir; Carey, Mary G

2013-01-01

Current guidelines recommend early reperfusion therapy for ST-elevation myocardial infarction (STEMI) within 90 min of first medical encounter. Telecardiology entails the use of advanced communication technologies to transmit the prehospital 12-lead electrocardiogram (ECG) to offsite cardiologists for early triage to the cath lab; which has been shown to dramatically reduce door-to-balloon time and total mortality. However, hospitals often find adopting ECG transmission technologies very challenging. The current review identifies seven major technical challenges of prehospital ECG transmission, including: paramedics inconvenience and transport delay; signal noise and interpretation errors; equipment malfunction and transmission failure; reliability of mobile phone networks; lack of compliance with the standards of digital ECG formats; poor integration with electronic medical records; and costly hardware and software pre-requisite installation. Current and potential solutions to address each of these technical challenges are discussed in details and include: automated ECG transmission protocols; annotatable waveform-based ECGs; optimal routing solutions; and the use of cloud computing systems rather than vendor-specific processing stations. Nevertheless, strategies to monitor transmission effectiveness and patient outcomes are essential to sustain initial gains of implementing ECG transmission technologies. © 2013.

Check your biosignals here: a new dataset for off-the-person ECG biometrics.

Science.gov (United States)

da Silva, Hugo Plácido; Lourenço, André; Fred, Ana; Raposo, Nuno; Aires-de-Sousa, Marta

2014-02-01

The Check Your Biosignals Here initiative (CYBHi) was developed as a way of creating a dataset and consistently repeatable acquisition framework, to further extend research in electrocardiographic (ECG) biometrics. In particular, our work targets the novel trend towards off-the-person data acquisition, which opens a broad new set of challenges and opportunities both for research and industry. While datasets with ECG signals collected using medical grade equipment at the chest can be easily found, for off-the-person ECG data the solution is generally for each team to collect their own corpus at considerable expense of resources. In this paper we describe the context, experimental considerations, methods, and preliminary findings of two public datasets created by our team, one for short-term and another for long-term assessment, with ECG data collected at the hand palms and fingers. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Comparison of JADE and canonical correlation analysis for ECG de-noising.

Science.gov (United States)

Kuzilek, Jakub; Kremen, Vaclav; Lhotska, Lenka

2014-01-01

This paper explores differences between two methods for blind source separation within frame of ECG de-noising. First method is joint approximate diagonalization of eigenmatrices, which is based on estimation of fourth order cross-cummulant tensor and its diagonalization. Second one is the statistical method known as canonical correlation analysis, which is based on estimation of correlation matrices between two multidimensional variables. Both methods were used within method, which combines the blind source separation algorithm with decision tree. The evaluation was made on large database of 382 long-term ECG signals and the results were examined. Biggest difference was found in results of 50 Hz power line interference where the CCA algorithm completely failed. Thus main power of CCA lies in estimation of unstructured noise within ECG. JADE algorithm has larger computational complexity thus the CCA perfomed faster when estimating the components.

Biometric security based on ECG

NARCIS (Netherlands)

Ma, L.; Groot, de J.A.; Linnartz, J.P.M.G.

2011-01-01

Recently the electrocardiogram (ECG) has been proposed as a novel biometric. This paper aims to construct a reliable ECG verification system, in terms of privacy protection. To this end, an improved expression to estimate the capacity in the autocorrelation (AC) of the ECG is derived, which not only

Competency in ECG Interpretation Among Medical Students

Science.gov (United States)

Kopeć, Grzegorz; Magoń, Wojciech; Hołda, Mateusz; Podolec, Piotr

2015-01-01

Background Electrocardiogram (ECG) is commonly used in diagnosis of heart diseases, including many life-threatening disorders. We aimed to assess skills in ECG interpretation among Polish medical students and to analyze the determinants of these skills. Material/Methods Undergraduates from all Polish medical schools were asked to complete a web-based survey containing 18 ECG strips. Questions concerned primary ECG parameters (rate, rhythm, and axis), emergencies, and common ECG abnormalities. Analysis was restricted to students in their clinical years (4th–6th), and students in their preclinical years (1st–3rd) were used as controls. Results We enrolled 536 medical students (females: n=299; 55.8%), aged 19 to 31 (23±1.6) years from all Polish medical schools. Most (72%) were in their clinical years. The overall rate of good response was better in students in years 4th–5th than those in years 1st–3rd (66% vs. 56%; pECG interpretation was higher in students who reported ECG self-learning (69% vs. 62%; pECG classes (66% vs. 66%; p=0.99). On multivariable analysis (pECG interpretation. Conclusions Polish medical students in their clinical years have a good level of competency in interpreting the primary ECG parameters, but their ability to recognize ECG signs of emergencies and common heart abnormalities is low. ECG interpretation skills are determined by self-education but not by attendance at regular ECG classes. Our results indicate qualitative and quantitative deficiencies in teaching ECG interpretation at medical schools. PMID:26541993

Quality assessment of digital annotated ECG data from clinical trials by the FDA ECG Warehouse.

Science.gov (United States)

Sarapa, Nenad

2007-09-01

The FDA mandates that digital electrocardiograms (ECGs) from 'thorough' QTc trials be submitted into the ECG Warehouse in Health Level 7 extended markup language format with annotated onset and offset points of waveforms. The FDA did not disclose the exact Warehouse metrics and minimal acceptable quality standards. The author describes the Warehouse scoring algorithms and metrics used by FDA, points out ways to improve FDA review and suggests Warehouse benefits for pharmaceutical sponsors. The Warehouse ranks individual ECGs according to their score for each quality metric and produces histogram distributions with Warehouse-specific thresholds that identify ECGs of questionable quality. Automatic Warehouse algorithms assess the quality of QT annotation and duration of manual QT measurement by the central ECG laboratory.

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal.

Science.gov (United States)

Nayak, Suraj K; Bit, Arindam; Dey, Anilesh; Mohapatra, Biswajit; Pal, Kunal

2018-01-01

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis.

Prospective ECG-triggered axial CT at 140-kV tube voltage improves coronary in-stent restenosis visibility at a lower radiation dose compared with conventional retrospective ECG-gated helical CT

Energy Technology Data Exchange (ETDEWEB)

Horiguchi, Jun; Fujioka, Chikako; Kiguchi, Masao; Kohno, Shingo [Hiroshima University Hospital, Department of Clinical Radiology, Hiroshima (Japan); Yamamoto, Hideya; Kitagawa, Toshiro [Hiroshima University, Department of Molecular and Internal Medicine, Division of Clinical Medical Science, Programs for Applied Biomedicine, Graduate School of Biomedical Sciences, Hiroshima (Japan); Ito, Katsuhide [Hiroshima University, Department of Radiology, Division of Medical Intelligence and Informatics, Programs for Applied Biomedicine, Graduate School of Biomedical Sciences, Hiroshima (Japan)

2009-10-15

The purpose of this study was to compare coronary 64-slice CT angiography (CTA) protocols, specifically prospective electrocardiograph (ECG)-triggered and retrospective ECG-gated CT acquisition performed using a tube voltage of 140 kV and 120 kV, regarding intracoronary stent imaging. Coronary artery stents (n=12) with artificial in-stent restenosis (50% luminal reduction, 40 HU) on a cardiac phantom were examined by CT at heart rates of 50-75 beats per minute (bpm). The subjective visibility of in-stent restenosis was evaluated with a three-point scale (1 clearly visible, 2 visible, and 3 not visible), and artificial lumen narrowing [(inner stent diameter - measured lumen diameter)/inner stent diameter], lumen attenuation increase ratio [(in-stent attenuation - coronary lumen attenuation)/coronary lumen attenuation], and signal-to-noise ratio of in-stent lumen were determined. The effective dose was estimated. The artificial lumen narrowing (mean 43%), the increase of lumen attenuation (mean 46%), and signal-to-noise ratio (mean 7.8) were not different between CT acquisitions (p=0.12-0.91). However, the visibility scores of in-stent restenosis were different (p<0.05) between ECG-gated CTA techniques: (a) 140-kV prospective (effective dose 4.6 mSv), 1.6; (b) 120-kV prospective (3.3 mSv), 1.8; (c) 140-kV retrospective (16.4-18.8 mSv), 1.9; and (d) 120-kV retrospective (11.0-13.4 mSv), 1.9. Thus, 140-kV prospective ECG-triggered CTA improves coronary in-stent restenosis visibility at a lower radiation dose compared with retrospective ECG-gated CTA. (orig.)

Resting heart rate and risk of adverse cardiovascular outcomes in asymptomatic aortic stenosis

DEFF Research Database (Denmark)

Greve, Anders M; Bang, Casper N; Berg, Ronan M G

2015-01-01

BACKGROUND: An elevated resting heart rate (RHR) may be an early sign of cardiac failure, but its prognostic value during watchful waiting in asymptomatic aortic stenosis (AS) is largely unknown. METHODS: RHR was determined by annual ECGs in the Simvastatin and Ezetimibe in Aortic Stenosis (SEAS)...

Ecg manifestations in dengue infection

International Nuclear Information System (INIS)

Tarique, S.; Murtaza, G.; Asif, S.; Qureshi, I.H.

2013-01-01

To determine the frequency of ECG changes in patients with dengue fever and dengue hemorrhagic fever. Place of study: Department of Medicine, Mayo Hospital Lahore Duration of study: September to November 201 Study design: Cross sectional analytical study Patient and methods: 116 patients with dengue infection were enrolled in the study. Their clinical presentation and examination was duly noted. Each patient had baseline and then regular monitoring of blood counts, metabolic profile and fluid status. Patients with Dengue Hemorrhagic fever underwent radiological examination in form of chest radiograph and ultrasound abdomen. ECG was carried out in all patients. Results: Out of 116 patients, 61(52.6%) suffered from Dengue Fever and 55(47.4%) had Dengue Hemorrhagic Fever. Overall 78 patients had normal ECG. Abnormal ECG findings like tachycardia, bradycardia, supraventricular tachycardia, left bundle branch block, ST depression, poor progression of R wave were noted. There was no significant relationship of ECG findings with the disease. Conclusion: ECG changes can occur in dengue infection with or without cardiac symptoms. Commonly noted findings were ST depression and bradycardia. (author)

Utility of the CORD ECG Database in Evaluating ECG Interpretation by Emergency Medicine Residents

Directory of Open Access Journals (Sweden)

Wong, Hubert E

2002-10-01

Full Text Available OBJECTIVES: Electrocardiograph (ECG interpretation is a vital component of Emergency Medicine (EM resident education, but few studies have formally examined ECG teaching methods used in residency training. Recently, the Council of EM Residency Directors (CORD developed an Internet database of 395 ECGs that have been extensively peer-reviewed to incorporate all findings and abnormalities. We examined the efficacy of this database in assessing EM residents' skills in ECG interpretation. METHODS: We used the CORD ECG database to evaluate residents at our academic three-year EM residency. Thirteen residents participated, including four first-year, four second-year, and five third-year residents. Twenty ECGs were selected using 14 search criteria representing a broad range of abnormalities, including infarction, rhythm, and conduction abnormalities. Exams were scored based on all abnormalities and findings listed in the teaching points accompanying each ECG. We assigned points to each abnormal finding based on clinical relevance. RESULTS: Out of a total of 183 points in our clinically weighted scoring system, first-year residents scored an average of 99 points (54.1% [9 1- 1191, second-year residents 11 1 points (60.4% [97-1261, and third-year residents 130 points (7 1.0% [94- 1501, p = 0.12. Clinically relevant abnormalities, including anterior and inferior myocardial infarctions, were most frequently diagnosed correctly, while posterior infarction was more frequently missed. Rhythm abnormalities including ventricular and supraventricular tachycardias were most frequently diagnosed correctly, while conduction abnormalities including left bundle branch block and atrioventricular (AV block were more frequently missed. CONCLUSION: The CORD database represents a valuable resource in the assessment and teaching of ECG skills, allowing more precise identification of areas upon which instruction should be further focused or individually tailored. Our

Evaluation of a novel portable capacitive ECG system in the clinical practice for a fast and simple ECG assessment in patients presenting with chest pain: FIDET (Fast Infarction Diagnosis ECG Trial)

OpenAIRE

Rasenack, Eva C. L.; Oehler, Martin; Els?sser, Albrecht; Schilling, Meinhard; Maier, Lars S.

2012-01-01

Background Electrocardiogram (ECG) assessment plays a crucial role in patients presenting with chest pain and suspected acute coronary syndrome (ACS). In a pilot study, we previously evaluated a capacitive ECG system (cECG) as a novel ECG technique for a fast and simple ECG assessment in patients with ST-elevation myocardial infarction (STEMI). In a next step, the sensitivity and specificity of this novel ECG technique have to be assessed in patients with ACS. Hypothesis The Fast Infarction D...

Reduction of Motion Artifacts and Improvement of R Peak Detecting Accuracy Using Adjacent Non-Intrusive ECG Sensors

Directory of Open Access Journals (Sweden)

Minho Choi

2016-05-01

Full Text Available Non-intrusive electrocardiogram (ECG monitoring has many advantages: easy to measure and apply in daily life. However, motion noise in the measured signal is the major problem of non-intrusive measurement. This paper proposes a method to reduce the noise and to detect the R peaks of ECG in a stable manner in a sitting arrangement using non-intrusive sensors. The method utilizes two capacitive ECG sensors (cECGs to measure ECG, and another two cECGs located adjacent to the sensors for ECG are added to obtain the information on motion. Then, active noise cancellation technique and the motion information are used to reduce motion noise. To verify the proposed method, ECG was measured indoors and during driving, and the accuracy of the detected R peaks was compared. After applying the method, the sum of sensitivity and positive predictivity increased 8.39% on average and 26.26% maximally in the data. Based on the results, it was confirmed that the motion noise was reduced and that more reliable R peak positions could be obtained by the proposed method. The robustness of the new ECG measurement method will elicit benefits to various health care systems that require noninvasive heart rate or heart rate variability measurements.

Compressed ECG biometric: a fast, secured and efficient method for identification of CVD patient.

Science.gov (United States)

Sufi, Fahim; Khalil, Ibrahim; Mahmood, Abdun

2011-12-01

Adoption of compression technology is often required for wireless cardiovascular monitoring, due to the enormous size of Electrocardiography (ECG) signal and limited bandwidth of Internet. However, compressed ECG must be decompressed before performing human identification using present research on ECG based biometric techniques. This additional step of decompression creates a significant processing delay for identification task. This becomes an obvious burden on a system, if this needs to be done for a trillion of compressed ECG per hour by the hospital. Even though the hospital might be able to come up with an expensive infrastructure to tame the exuberant processing, for small intermediate nodes in a multihop network identification preceded by decompression is confronting. In this paper, we report a technique by which a person can be identified directly from his / her compressed ECG. This technique completely obviates the step of decompression and therefore upholds biometric identification less intimidating for the smaller nodes in a multihop network. The biometric template created by this new technique is lower in size compared to the existing ECG based biometrics as well as other forms of biometrics like face, finger, retina etc. (up to 8302 times lower than face template and 9 times lower than existing ECG based biometric template). Lower size of the template substantially reduces the one-to-many matching time for biometric recognition, resulting in a faster biometric authentication mechanism.

A novel method for the detection of R-peaks in ECG based on K-Nearest Neighbors and Particle Swarm Optimization

Science.gov (United States)

He, Runnan; Wang, Kuanquan; Li, Qince; Yuan, Yongfeng; Zhao, Na; Liu, Yang; Zhang, Henggui

2017-12-01

Cardiovascular diseases are associated with high morbidity and mortality. However, it is still a challenge to diagnose them accurately and efficiently. Electrocardiogram (ECG), a bioelectrical signal of the heart, provides crucial information about the dynamical functions of the heart, playing an important role in cardiac diagnosis. As the QRS complex in ECG is associated with ventricular depolarization, therefore, accurate QRS detection is vital for interpreting ECG features. In this paper, we proposed a real-time, accurate, and effective algorithm for QRS detection. In the algorithm, a proposed preprocessor with a band-pass filter was first applied to remove baseline wander and power-line interference from the signal. After denoising, a method combining K-Nearest Neighbor (KNN) and Particle Swarm Optimization (PSO) was used for accurate QRS detection in ECGs with different morphologies. The proposed algorithm was tested and validated using 48 ECG records from MIT-BIH arrhythmia database (MITDB), achieved a high averaged detection accuracy, sensitivity and positive predictivity of 99.43, 99.69, and 99.72%, respectively, indicating a notable improvement to extant algorithms as reported in literatures.

Cardiorespiratory phase synchronization during normal rest and inward-attention meditation.

Science.gov (United States)

Wu, Shr-Da; Lo, Pei-Chen

2010-06-11

The cardiac and respiratory systems can be viewed as two self-sustained oscillators with various interactions between them. In this study, the cardiorespiratory phase synchronization (CRPS) quantified by synchrogram was investigated to explore the phase synchronization between these two systems. The synchrogram scheme was applied to electrocardiogram (ECG) and respiration signals. Particular focus was the distinct cardiac-respiratory regulation phenomena intervened by inward-attention meditation and normal relaxation. Four synchronization parameters were measured: frequency ratio, lasting length, number of epochs, and total length. The results showed that normal rest resulted in much weaker CRPS. Statistical analysis reveals that the number of synchronous epochs and the total synchronization length significantly increase (p=0.024 and 0.034 respectively) during meditation. Furthermore, a predominance of 4:1 and 5:1 rhythm-ratio synchronizations was observed during meditation. Consequently, this study concludes that CRPS can be enhanced during meditation, compared with normal relaxation, and reveals a predominance of specific frequency ratios. Copyright (c) 2008 Elsevier Ireland Ltd. All rights reserved.

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal

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Mohapatra, Biswajit

2018-01-01

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis. PMID:29854361

Correcting for Blood Arrival Time in Global Mean Regression Enhances Functional Connectivity Analysis of Resting State fMRI-BOLD Signals.

Science.gov (United States)

Erdoğan, Sinem B; Tong, Yunjie; Hocke, Lia M; Lindsey, Kimberly P; deB Frederick, Blaise

2016-01-01

Resting state functional connectivity analysis is a widely used method for mapping intrinsic functional organization of the brain. Global signal regression (GSR) is commonly employed for removing systemic global variance from resting state BOLD-fMRI data; however, recent studies have demonstrated that GSR may introduce spurious negative correlations within and between functional networks, calling into question the meaning of anticorrelations reported between some networks. In the present study, we propose that global signal from resting state fMRI is composed primarily of systemic low frequency oscillations (sLFOs) that propagate with cerebral blood circulation throughout the brain. We introduce a novel systemic noise removal strategy for resting state fMRI data, "dynamic global signal regression" (dGSR), which applies a voxel-specific optimal time delay to the global signal prior to regression from voxel-wise time series. We test our hypothesis on two functional systems that are suggested to be intrinsically organized into anticorrelated networks: the default mode network (DMN) and task positive network (TPN). We evaluate the efficacy of dGSR and compare its performance with the conventional "static" global regression (sGSR) method in terms of (i) explaining systemic variance in the data and (ii) enhancing specificity and sensitivity of functional connectivity measures. dGSR increases the amount of BOLD signal variance being modeled and removed relative to sGSR while reducing spurious negative correlations introduced in reference regions by sGSR, and attenuating inflated positive connectivity measures. We conclude that incorporating time delay information for sLFOs into global noise removal strategies is of crucial importance for optimal noise removal from resting state functional connectivity maps.

Position difference regularity of corresponding R-wave peaks for maternal ECG components from different abdominal points

International Nuclear Information System (INIS)

Zhang Jie-Min; Liu Hong-Xing; Huang Xiao-Lin; Si Jun-Feng; Guan Qun; Tang Li-Ming; Liu Tie-Bing

2014-01-01

We collected 343 groups of abdominal electrocardiogram (ECG) data from 78 pregnant women and deleted the channels unable for experts to determine R-wave peaks from them; then, based on these filtered data, the statistics of position difference of corresponding R-wave peaks for different maternal ECG components from different points were studied. The resultant statistics showed the regularity that the position difference of corresponding maternal R-wave peaks between different abdominal points does not exceed the range of 30 ms. The regularity was also proved using the fECG data from MIT—BIH PhysioBank. Additionally, the paper applied the obtained regularity, the range of position differences of the corresponding maternal R-wave peaks, to accomplish the automatic detection of maternal R-wave peaks in the recorded all initial 343 groups of abdominal signals, including the ones with the largest fetal ECG components, and all 55 groups of ECG data from MIT—BIH PhysioBank, achieving the successful separation of the maternal ECGs. (interdisciplinary physics and related areas of science and technology)

Deep Learning for ECG Classification

Science.gov (United States)

Pyakillya, B.; Kazachenko, N.; Mikhailovsky, N.

2017-10-01

The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG data. However, the main disadvantages of these ML results is use of heuristic hand-crafted or engineered features with shallow feature learning architectures. The problem relies in the possibility not to find most appropriate features which will give high classification accuracy in this ECG problem. One of the proposing solution is to use deep learning architectures where first layers of convolutional neurons behave as feature extractors and in the end some fully-connected (FCN) layers are used for making final decision about ECG classes. In this work the deep learning architecture with 1D convolutional layers and FCN layers for ECG classification is presented and some classification results are showed.

Measuring vascular reactivity with resting-state blood oxygenation level-dependent (BOLD) signal fluctuations: A potential alternative to the breath-holding challenge?

Science.gov (United States)

Jahanian, Hesamoddin; Christen, Thomas; Moseley, Michael E; Pajewski, Nicholas M; Wright, Clinton B; Tamura, Manjula K; Zaharchuk, Greg

2017-07-01

Measurement of the ability of blood vessels to dilate and constrict, known as vascular reactivity, is often performed with breath-holding tasks that transiently raise arterial blood carbon dioxide (P a CO 2 ) levels. However, following the proper commands for a breath-holding experiment may be difficult or impossible for many patients. In this study, we evaluated two approaches for obtaining vascular reactivity information using blood oxygenation level-dependent signal fluctuations obtained from resting-state functional magnetic resonance imaging data: physiological fluctuation regression and coefficient of variation of the resting-state functional magnetic resonance imaging signal. We studied a cohort of 28 older adults (69 ± 7 years) and found that six of them (21%) could not perform the breath-holding protocol, based on an objective comparison with an idealized respiratory waveform. In the subjects that could comply, we found a strong linear correlation between data extracted from spontaneous resting-state functional magnetic resonance imaging signal fluctuations and the blood oxygenation level-dependent percentage signal change during breath-holding challenge ( R 2  = 0.57 and 0.61 for resting-state physiological fluctuation regression and resting-state coefficient of variation methods, respectively). This technique may eliminate the need for subject cooperation, thus allowing the evaluation of vascular reactivity in a wider range of clinical and research conditions in which it may otherwise be impractical.

Investigations of sensitivity and resolution of ECG and MCG in a realistically shaped thorax model

International Nuclear Information System (INIS)

Mäntynen, Ville; Konttila, Teijo; Stenroos, Matti

2014-01-01

Solving the inverse problem of electrocardiography (ECG) and magnetocardiography (MCG) is often referred to as cardiac source imaging. Spatial properties of ECG and MCG as imaging systems are, however, not well known. In this modelling study, we investigate the sensitivity and point-spread function (PSF) of ECG, MCG, and combined ECG+MCG as a function of source position and orientation, globally around the ventricles: signal topographies are modelled using a realistically-shaped volume conductor model, and the inverse problem is solved using a distributed source model and linear source estimation with minimal use of prior information. The results show that the sensitivity depends not only on the modality but also on the location and orientation of the source and that the sensitivity distribution is clearly reflected in the PSF. MCG can better characterize tangential anterior sources (with respect to the heart surface), while ECG excels with normally-oriented and posterior sources. Compared to either modality used alone, the sensitivity of combined ECG+MCG is less dependent on source orientation per source location, leading to better source estimates. Thus, for maximal sensitivity and optimal source estimation, the electric and magnetic measurements should be combined. (paper)

The electrocardiogram signal of Seba's short-tailed bat, Carollia perspicillata.

Science.gov (United States)

Mihova, Diana; Hechavarría, Julio C

2016-07-01

A number of studies have successfully used electrocardiogram (ECG) signals to characterize complex physiological phenomena such as associative learning in bats. However, at present, no thorough characterization of the structure of ECG signals is available for these animals. The aim of the present study was to quantitatively characterize features of the ECG signals in the bat species Carollia perspicillata, a species that is commonly used in neuroethology studies. Our results show that the ECG signals of C. perspicillata follow the typical mammalian pattern, in that they are composed by a P wave, QRS complex and a T wave. Peak-to-peak amplitudes in the bats' ECG signals were larger in measuring configurations in which one of the electrodes was attached to the right thumb. In addition, large differences in the instantaneous heart rate (HR) distributions were observed between ketamine/xylazine anesthetized and awake bats. Ketamine/xylazine might target the neural circuits that control HR, therefore, instantaneous HR measurements should only be used as physiological marker in awake animals.

Influence of ER leak on resting cytoplasmic Ca2+ and receptor-mediated Ca2+ signalling in human macrophage.

Science.gov (United States)

Layhadi, Janice A; Fountain, Samuel J

2017-06-03

Mechanisms controlling endoplasmic reticulum (ER) Ca 2+ homeostasis are important regulators of resting cytoplasmic Ca 2+ concentration ([Ca 2+ ] cyto ) and receptor-mediated Ca 2+ signalling. Here we investigate channels responsible for ER Ca 2+ leak in THP-1 macrophage and human primary macrophage. In the absence of extracellular Ca 2+ we employ ionomycin action at the plasma membrane to stimulate ER Ca 2+ leak. Under these conditions ionomycin elevates [Ca 2+ ] cyto revealing a Ca 2+ leak response which is abolished by thapsigargin. IP 3 receptors (Xestospongin C, 2-APB), ryanodine receptors (dantrolene), and translocon (anisomycin) inhibition facilitated ER Ca 2+ leak in model macrophage, with translocon inhibition also reducing resting [Ca 2+ ] cyto . In primary macrophage, translocon inhibition blocks Ca 2+ leak but does not influence resting [Ca 2+ ] cyto . We identify a role for translocon-mediated ER Ca 2+ leak in receptor-mediated Ca 2+ signalling in both model and primary human macrophage, whereby the Ca 2+ response to ADP (P2Y receptor agonist) is augmented following anisomycin treatment. In conclusion, we demonstrate a role of ER Ca 2+ leak via the translocon in controlling resting cytoplasmic Ca 2+ in model macrophage and receptor-mediated Ca 2+ signalling in model macrophage and primary macrophage. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of heart rate variability between resting state and external-cuff-inflation-and-deflation state: a pilot study.

Science.gov (United States)

Ji, Lizhen; Liu, Chengyu; Li, Peng; Wang, Xinpei; Yan, Chang; Liu, Changchun

2015-10-01

Heart rate variability (HRV) has been widely used in clinical research to provide an insight into the autonomic control of the cardiovascular system. Measurement of HRV is generally performed under a relaxed resting state. The effects of other conditions on HRV measurement, such as running, mountaineering, head-up tilt, etc, have also been investigated. This study aimed to explore whether an inflation-and-deflation process applied to a unilateral upper arm cuff would influence the HRV measurement. Fifty healthy young volunteers aged between 21 and 30 were enrolled in this study. Electrocardiogram (ECG) signals were recorded for each subject over a five minute resting state followed by a five minute external-cuff-inflation-and-deflation state (ECID state). A one minute gap was scheduled between the two measurements. Consecutive RR intervals in the ECG were extracted automatically to form the HRV data for each of the two states. Time domain (SDNN, RMSSD and PNN50), frequency domain (LFn, HFn and LF/HF) and nonlinear (VLI, VAI and SampEn) HRV indices were analyzed and compared between the two states. In addition, the effects of mean artery pressure (MAP) and heart rate (HR) on the aforementioned HRV indices were assessed for the two states, respectively, by Pearson correlation analysis. The results showed no significant difference in all aforementioned HRV indices between the resting and the ECID states (all p  >  0.05). The corresponding HRV indices had significant positive correlation (all p    0.05) for either state. Besides, none of the indices showed HR-related change (all p  >  0.05) for either state except the index of VLI in the resting state. To conclude, this pilot study suggested that the applied ECID process hardly influenced those commonly used HRV indices. It would thus be applicable to simultaneously measure both blood pressure and HRV indices in clinical practice.

Experimental evaluations of wearable ECG monitor.

Science.gov (United States)

Ha, Kiryong; Kim, Youngsung; Jung, Junyoung; Lee, Jeunwoo

2008-01-01

Healthcare industry is changing with ubiquitous computing environment and wearable ECG measurement is one of the most popular approaches in this healthcare industry. Reliability and performance of healthcare device is fundamental issue for widespread adoptions, and interdisciplinary perspectives of wearable ECG monitor make this more difficult. In this paper, we propose evaluation criteria considering characteristic of both ECG measurement and ubiquitous computing. With our wearable ECG monitors, various levels of experimental analysis are performed based on evaluation strategy.

Subcutaneous ICD screening with the Boston Scientific ZOOM programmer versus a 12-lead ECG machine.

Science.gov (United States)

Chang, Shu C; Patton, Kristen K; Robinson, Melissa R; Poole, Jeanne E; Prutkin, Jordan M

2018-02-24

The subcutaneous implantable cardioverter-defibrillator (S-ICD) requires preimplant screening to ensure appropriate sensing and reduce risk of inappropriate shocks. Screening can be performed using either an ICD programmer or a 12-lead electrocardiogram (ECG) machine. It is unclear whether differences in signal filtering and digital sampling change the screening success rate. Subjects were recruited if they had a transvenous single-lead ICD without pacing requirements or were candidates for a new ICD. Screening was performed using both a Boston Scientific ZOOM programmer (Marlborough, MA, USA) and General Electric MAC 5000 ECG machine (Fairfield, CT, USA). A pass was defined as having at least one lead that fit within the screening template in both supine and sitting positions. A total of 69 subjects were included and 27 sets of ECG leads had differing screening results between the two machines (7%). Of these sets, 22 (81%) passed using the ECG machine but failed using the programmer and five (19%) passed using the ECG machine but failed using the programmer (P machine but failed using the programmer. No subject passed screening with the programmer but failed with the ECG machine. There can be occasional disagreement in S-ICD patient screening between an ICD programmer and ECG machine, all of whom passed with the ECG machine but failed using the programmer. On a per lead basis, the ECG machine passes more subjects. It is unknown what the inappropriate shock rate would be if an S-ICD was implanted. Clinical judgment should be used in borderline cases. © 2018 Wiley Periodicals, Inc.

Dose modulated retrospective ECG-gated versus non-gated 64-row CT angiography of the aorta at the same radiation dose: Comparison of motion artifacts, diagnostic confidence and signal-to-noise-ratios

International Nuclear Information System (INIS)

Schernthaner, Ruediger E.; Stadler, Alfred; Beitzke, Dietrich; Homolka, Peter; Weber, Michael; Lammer, Johannes; Czerny, Martin; Loewe, Christian

2012-01-01

Purpose: To compare ECG-gated and non-gated CT angiography of the aorta at the same radiation dose, with regard to motion artifacts (MA), diagnostic confidence (DC) and signal-to-noise-ratios (SNRs). Materials and methods: Sixty consecutive patients prospectively randomized into two groups underwent 64-row CT angiography, with or without dose-modulated ECG-gating, of the entire aorta, due to several pathologies of the ascending aorta. MA and DC were both assessed using a four-point scale. SNRs were calculated by dividing the mean enhancement by the standard deviation. The dose-length-product (DLP) of each examination was recorded and the effective dose was estimated. Results: Dose-modulated ECG-gating showed statistically significant advantages over non-gated CT angiography, with regard to MA (p < 0.001) and DC (p < 0.001), at the aortic valve, at the origin of the coronary arteries, and at the dissection membrane, with a significant correlation (p < 0.001) between MA and DC. At the aortic wall, however, ECG-gated CT angiography showed statistically significant fewer MA (p < 0.001), but not a statistically significant higher DC (p = 0.137) compared to non-gated CT angiography. At the supra-aortic vessels and the descending aorta, the ECG-triggering showed no statistically significant differences with regard to MA (p = 0.861 and 0.526, respectively) and DC (p = 1.88 and 0.728, respectively). The effective dose of ECG-gated CT angiography (23.24 mSv; range, 18.43–25.94 mSv) did not differ significantly (p = 0.051) from that of non-gated CT angiography (24.28 mSv; range, 19.37–29.27 mSv). Conclusion: ECG-gated CT angiography of the entire aorta reduces MA and results in a higher DC with the same SNR, compared to non-gated CT angiography at the same radiation dose.

Design, fabrication and skin-electrode contact analysis of polymer microneedle-based ECG electrodes

Science.gov (United States)

O'Mahony, Conor; Grygoryev, Konstantin; Ciarlone, Antonio; Giannoni, Giuseppe; Kenthao, Anan; Galvin, Paul

2016-08-01

Microneedle-based ‘dry’ electrodes have immense potential for use in diagnostic procedures such as electrocardiography (ECG) analysis, as they eliminate several of the drawbacks associated with the conventional ‘wet’ electrodes currently used for physiological signal recording. To be commercially successful in such a competitive market, it is essential that dry electrodes are manufacturable in high volumes and at low cost. In addition, the topographical nature of these emerging devices means that electrode performance is likely to be highly dependent on the quality of the skin-electrode contact. This paper presents a low-cost, wafer-level micromoulding technology for the fabrication of polymeric ECG electrodes that use microneedle structures to make a direct electrical contact to the body. The double-sided moulding process can be used to eliminate post-process via creation and wafer dicing steps. In addition, measurement techniques have been developed to characterize the skin-electrode contact force. We perform the first analysis of signal-to-noise ratio dependency on contact force, and show that although microneedle-based electrodes can outperform conventional gel electrodes, the quality of ECG recordings is significantly dependent on temporal and mechanical aspects of the skin-electrode interface.

Design, fabrication and skin-electrode contact analysis of polymer microneedle-based ECG electrodes

International Nuclear Information System (INIS)

O’Mahony, Conor; Grygoryev, Konstantin; Ciarlone, Antonio; Giannoni, Giuseppe; Kenthao, Anan; Galvin, Paul

2016-01-01

Microneedle-based ‘dry’ electrodes have immense potential for use in diagnostic procedures such as electrocardiography (ECG) analysis, as they eliminate several of the drawbacks associated with the conventional ‘wet’ electrodes currently used for physiological signal recording. To be commercially successful in such a competitive market, it is essential that dry electrodes are manufacturable in high volumes and at low cost. In addition, the topographical nature of these emerging devices means that electrode performance is likely to be highly dependent on the quality of the skin-electrode contact.This paper presents a low-cost, wafer-level micromoulding technology for the fabrication of polymeric ECG electrodes that use microneedle structures to make a direct electrical contact to the body. The double-sided moulding process can be used to eliminate post-process via creation and wafer dicing steps. In addition, measurement techniques have been developed to characterize the skin-electrode contact force. We perform the first analysis of signal-to-noise ratio dependency on contact force, and show that although microneedle-based electrodes can outperform conventional gel electrodes, the quality of ECG recordings is significantly dependent on temporal and mechanical aspects of the skin-electrode interface. (paper)

A cancelable biometric scheme based on multi-lead ECGs.

Science.gov (United States)

Peng-Tzu Chen; Shun-Chi Wu; Jui-Hsuan Hsieh

2017-07-01

Biometric technologies offer great advantages over other recognition methods, but there are concerns that they may compromise the privacy of individuals. In this paper, an electrocardiogram (ECG)-based cancelable biometric scheme is proposed to relieve such concerns. In this scheme, distinct biometric templates for a given beat bundle are constructed via "subspace collapsing." To determine the identity of any unknown beat bundle, the multiple signal classification (MUSIC) algorithm, incorporating a "suppression and poll" strategy, is adopted. Unlike the existing cancelable biometric schemes, knowledge of the distortion transform is not required for recognition. Experiments with real ECGs from 285 subjects are presented to illustrate the efficacy of the proposed scheme. The best recognition rate of 97.58 % was achieved under the test condition N train = 10 and N test = 10.

Design of Secure ECG-Based Biometric Authentication in Body Area Sensor Networks.

Science.gov (United States)

Peter, Steffen; Reddy, Bhanu Pratap; Momtaz, Farshad; Givargis, Tony

2016-04-22

Body area sensor networks (BANs) utilize wireless communicating sensor nodes attached to a human body for convenience, safety, and health applications. Physiological characteristics of the body, such as the heart rate or Electrocardiogram (ECG) signals, are promising means to simplify the setup process and to improve security of BANs. This paper describes the design and implementation steps required to realize an ECG-based authentication protocol to identify sensor nodes attached to the same human body. Therefore, the first part of the paper addresses the design of a body-area sensor system, including the hardware setup, analogue and digital signal processing, and required ECG feature detection techniques. A model-based design flow is applied, and strengths and limitations of each design step are discussed. Real-world measured data originating from the implemented sensor system are then used to set up and parametrize a novel physiological authentication protocol for BANs. The authentication protocol utilizes statistical properties of expected and detected deviations to limit the number of false positive and false negative authentication attempts. The result of the described holistic design effort is the first practical implementation of biometric authentication in BANs that reflects timing and data uncertainties in the physical and cyber parts of the system.

Design of Secure ECG-Based Biometric Authentication in Body Area Sensor Networks

Science.gov (United States)

Peter, Steffen; Pratap Reddy, Bhanu; Momtaz, Farshad; Givargis, Tony

2016-01-01

Body area sensor networks (BANs) utilize wireless communicating sensor nodes attached to a human body for convenience, safety, and health applications. Physiological characteristics of the body, such as the heart rate or Electrocardiogram (ECG) signals, are promising means to simplify the setup process and to improve security of BANs. This paper describes the design and implementation steps required to realize an ECG-based authentication protocol to identify sensor nodes attached to the same human body. Therefore, the first part of the paper addresses the design of a body-area sensor system, including the hardware setup, analogue and digital signal processing, and required ECG feature detection techniques. A model-based design flow is applied, and strengths and limitations of each design step are discussed. Real-world measured data originating from the implemented sensor system are then used to set up and parametrize a novel physiological authentication protocol for BANs. The authentication protocol utilizes statistical properties of expected and detected deviations to limit the number of false positive and false negative authentication attempts. The result of the described holistic design effort is the first practical implementation of biometric authentication in BANs that reflects timing and data uncertainties in the physical and cyber parts of the system. PMID:27110785

Design of Secure ECG-Based Biometric Authentication in Body Area Sensor Networks

Directory of Open Access Journals (Sweden)

Steffen Peter

2016-04-01

Full Text Available Body area sensor networks (BANs utilize wireless communicating sensor nodes attached to a human body for convenience, safety, and health applications. Physiological characteristics of the body, such as the heart rate or Electrocardiogram (ECG signals, are promising means to simplify the setup process and to improve security of BANs. This paper describes the design and implementation steps required to realize an ECG-based authentication protocol to identify sensor nodes attached to the same human body. Therefore, the first part of the paper addresses the design of a body-area sensor system, including the hardware setup, analogue and digital signal processing, and required ECG feature detection techniques. A model-based design flow is applied, and strengths and limitations of each design step are discussed. Real-world measured data originating from the implemented sensor system are then used to set up and parametrize a novel physiological authentication protocol for BANs. The authentication protocol utilizes statistical properties of expected and detected deviations to limit the number of false positive and false negative authentication attempts. The result of the described holistic design effort is the first practical implementation of biometric authentication in BANs that reflects timing and data uncertainties in the physical and cyber parts of the system.

Singularity detection by wavelet approach: application to electrocardiogram signal

Science.gov (United States)

Jalil, Bushra; Beya, Ouadi; Fauvet, Eric; Laligant, Olivier

2010-01-01

In signal processing, the region of abrupt changes contains the most of the useful information about the nature of the signal. The region or the points where these changes occurred are often termed as singular point or singular region. The singularity is considered to be an important character of the signal, as it refers to the discontinuity and interruption present in the signal and the main purpose of the detection of such singular point is to identify the existence, location and size of those singularities. Electrocardiogram (ECG) signal is used to analyze the cardiovascular activity in the human body. However the presence of noise due to several reasons limits the doctor's decision and prevents accurate identification of different pathologies. In this work we attempt to analyze the ECG signal with energy based approach and some heuristic methods to segment and identify different signatures inside the signal. ECG signal has been initially denoised by empirical wavelet shrinkage approach based on Steins Unbiased Risk Estimate (SURE). At the second stage, the ECG signal has been analyzed by Mallat approach based on modulus maximas and Lipschitz exponent computation. The results from both approaches has been discussed and important aspects has been highlighted. In order to evaluate the algorithm, the analysis has been done on MIT-BIH Arrhythmia database; a set of ECG data records sampled at a rate of 360 Hz with 11 bit resolution over a 10mv range. The results have been examined and approved by medical doctors.

Systolic blood pressure estimation using PPG and ECG during physical exercise

NARCIS (Netherlands)

Sun, S.; Bezemer, R.; Long, X.; Muehlsteff, J.; Aarts, R.M.

2016-01-01

In this work, a model to estimate systolic blood pressure (SBP) using photoplethysmography (PPG) and electrocardiography (ECG) is proposed. Data from 19 subjects doing a 40 min exercise was analyzed. Reference SBP was measured at the finger based on the volume-clamp principle. PPG signals were

Combining and benchmarking methods of foetal ECG extraction without maternal or scalp electrode data

International Nuclear Information System (INIS)

Behar, Joachim; Oster, Julien; Clifford, Gari D

2014-01-01

Despite significant advances in adult clinical electrocardiography (ECG) signal processing techniques and the power of digital processors, the analysis of non-invasive foetal ECG (NI-FECG) is still in its infancy. The Physionet/Computing in Cardiology Challenge 2013 addresses some of these limitations by making a set of FECG data publicly available to the scientific community for evaluation of signal processing techniques. The abdominal ECG signals were first preprocessed with a band-pass filter in order to remove higher frequencies and baseline wander. A notch filter to remove power interferences at 50 Hz or 60 Hz was applied if required. The signals were then normalized before applying various source separation techniques to cancel the maternal ECG. These techniques included: template subtraction, principal/independent component analysis, extended Kalman filter and a combination of a subset of these methods (FUSE method). Foetal QRS detection was performed on all residuals using a Pan and Tompkins QRS detector and the residual channel with the smoothest foetal heart rate time series was selected. The FUSE algorithm performed better than all the individual methods on the training data set. On the validation and test sets, the best Challenge scores obtained were E1 = 179.44, E2 = 20.79, E3 = 153.07, E4 = 29.62 and E5 = 4.67 for events 1–5 respectively using the FUSE method. These were the best Challenge scores for E1 and E2 and third and second best Challenge scores for E3, E4 and E5 out of the 53 international teams that entered the Challenge. The results demonstrated that existing standard approaches for foetal heart rate estimation can be improved by fusing estimators together. We provide open source code to enable benchmarking for each of the standard approaches described. (paper)

New system for digital to analog transformation and reconstruction of 12-lead ECGs.

Science.gov (United States)

Kothadia, Roshni; Kulecz, Walter B; Kofman, Igor S; Black, Adam J; Grier, James W; Schlegel, Todd T

2013-01-01

We describe initial validation of a new system for digital to analog conversion (DAC) and reconstruction of 12-lead ECGs. The system utilizes an open and optimized software format with a commensurately optimized DAC hardware configuration to accurately reproduce, from digital files, the original analog electrocardiographic signals of previously instrumented patients. By doing so, the system also ultimately allows for transmission of data collected on one manufacturer's 12-lead ECG hardware/software into that of any other. To initially validate the system, we compared original and post-DAC re-digitized 12-lead ECG data files (∼5-minutes long) in two types of validation studies in 10 patients. The first type quantitatively compared the total waveform voltage differences between the original and re-digitized data while the second type qualitatively compared the automated electrocardiographic diagnostic statements generated by the original versus re-digitized data. The grand-averaged difference in root mean squared voltage between the original and re-digitized data was 20.8 µV per channel when re-digitization involved the same manufacturer's analog to digital converter (ADC) as the original digitization, and 28.4 µV per channel when it involved a different manufacturer's ADC. Automated diagnostic statements generated by the original versus reconstructed data did not differ when using the diagnostic algorithm from the same manufacturer on whose device the original data were collected, and differed only slightly for just 1 of 10 patients when using a third-party diagnostic algorithm throughout. Original analog 12-lead ECG signals can be reconstructed from digital data files with accuracy sufficient for clinical use. Such reconstructions can readily enable automated second opinions for difficult-to-interpret 12-lead ECGs, either locally or remotely through the use of dedicated or cloud-based servers.

New system for digital to analog transformation and reconstruction of 12-lead ECGs.

Directory of Open Access Journals (Sweden)

Roshni Kothadia

Full Text Available INTRODUCTION: We describe initial validation of a new system for digital to analog conversion (DAC and reconstruction of 12-lead ECGs. The system utilizes an open and optimized software format with a commensurately optimized DAC hardware configuration to accurately reproduce, from digital files, the original analog electrocardiographic signals of previously instrumented patients. By doing so, the system also ultimately allows for transmission of data collected on one manufacturer's 12-lead ECG hardware/software into that of any other. MATERIALS AND METHODS: To initially validate the system, we compared original and post-DAC re-digitized 12-lead ECG data files (∼5-minutes long in two types of validation studies in 10 patients. The first type quantitatively compared the total waveform voltage differences between the original and re-digitized data while the second type qualitatively compared the automated electrocardiographic diagnostic statements generated by the original versus re-digitized data. RESULTS: The grand-averaged difference in root mean squared voltage between the original and re-digitized data was 20.8 µV per channel when re-digitization involved the same manufacturer's analog to digital converter (ADC as the original digitization, and 28.4 µV per channel when it involved a different manufacturer's ADC. Automated diagnostic statements generated by the original versus reconstructed data did not differ when using the diagnostic algorithm from the same manufacturer on whose device the original data were collected, and differed only slightly for just 1 of 10 patients when using a third-party diagnostic algorithm throughout. CONCLUSION: Original analog 12-lead ECG signals can be reconstructed from digital data files with accuracy sufficient for clinical use. Such reconstructions can readily enable automated second opinions for difficult-to-interpret 12-lead ECGs, either locally or remotely through the use of dedicated or cloud

Respiratory Information Extraction from Electrocardiogram Signals

KAUST Repository

Amin, Gamal El Din Fathy

2010-12-01

The Electrocardiogram (ECG) is a tool measuring the electrical activity of the heart, and it is extensively used for diagnosis and monitoring of heart diseases. The ECG signal reflects not only the heart activity but also many other physiological processes. The respiratory activity is a prominent process that affects the ECG signal due to the close proximity of the heart and the lungs. In this thesis, several methods for the extraction of respiratory process information from the ECG signal are presented. These methods allow an estimation of the lung volume and the lung pressure from the ECG signal. The potential benefit of this is to eliminate the corresponding sensors used to measure the respiration activity. A reduction of the number of sensors connected to patients will increase patients’ comfort and reduce the costs associated with healthcare. As a further result, the efficiency of diagnosing respirational disorders will increase since the respiration activity can be monitored with a common, widely available method. The developed methods can also improve the detection of respirational disorders that occur while patients are sleeping. Such disorders are commonly diagnosed in sleeping laboratories where the patients are connected to a number of different sensors. Any reduction of these sensors will result in a more natural sleeping environment for the patients and hence a higher sensitivity of the diagnosis.

Effects of cuff inflation and deflation on pulse transit time measured from ECG and multi-wavelength PPG.

Science.gov (United States)

Liu, Jing; Li, Yao; Ding, Xiao-Rong; Dai, Wen-Xuan; Zhang, Yuan-Ting

2015-01-01

Pulse transit time (PTT), which refers to the time it takes a pulse wave to travel between two arterial sites is a promising index for cuff-less blood pressure (BP) estimation, as well as non-invasive assessment of arterial functions. However, it has not been investigated whether PTTs measured from ECG and different wavelength PPG are equally affected by the arterial status. Furthermore, comparison between the changes of different PTTs can provide enlightenment on the hardware implementation of the PTT-based BP estimation method. This work mainly studied the changes of PTTs calculated from electrocardiogram (ECG) and multi-wavelength photoplethysmogram (PPG) after exerting cuff pressure on the upper arm. A four-channel PPG acquisition system was developed to collect the multi-wavelength PPG signals of red, yellow, green and blue light at the fingertip simultaneously. Ten subjects participated in the experiment and their PTTs measured from different PPG and ECG signals before and after exerting cuff pressure were compared. This study found that within one minute after the four-minute cuff inflation and deflation process, the PTT measured from ECG and yellow PPG experienced a significant increase (p0.9) compared with that before exerting cuff pressure. This indicates that PTTs calculated from different wavelength PPG have different recoverability from smooth muscle relaxation. Another interesting finding is that the PTT calculated from ECG and yellow PPG had a strong correlation (|r|>0.7) with the time difference between yellow PPG and other PPG signals, which implies the potential of the time difference between yellow PPG and other PPGs as a complementary to PTT-based model for blood pressure estimation.

Correlation of BOLD Signal with Linear and Nonlinear Patterns of EEG in Resting State EEG-Informed fMRI

Directory of Open Access Journals (Sweden)

Galina V. Portnova

2018-01-01

Full Text Available Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data on how changes in the complexity of brain dynamics derived from EEG reflect variations in the BOLD signal. The purpose of our study was to correlate both spectral patterns, as linear features of EEG rhythms, and nonlinear EEG dynamic complexity with neuronal activity obtained by fMRI. We examined the relationships between EEG patterns and brain activation obtained by simultaneous EEG-fMRI during the resting state condition in 25 healthy right-handed adult volunteers. Using EEG-derived regressors, we demonstrated a substantial correlation of BOLD signal changes with linear and nonlinear features of EEG. We found the most significant positive correlation of fMRI signal with delta spectral power. Beta and alpha spectral features had no reliable effect on BOLD fluctuation. However, dynamic changes of alpha peak frequency exhibited a significant association with BOLD signal increase in right-hemisphere areas. Additionally, EEG dynamic complexity as measured by the HFD of the 2–20 Hz EEG frequency range significantly correlated with the activation of cortical and subcortical limbic system areas. Our results indicate that both spectral features of EEG frequency bands and nonlinear dynamic properties of spontaneous EEG are strongly associated with fluctuations of the BOLD signal during the resting state condition.

Predictive value of casual ECG-based resting heart rate compared with resting heart rate obtained from Holter recording

DEFF Research Database (Denmark)

Carlson, Nicholas; Dixen, Ulrik; Marott, Jacob L

2014-01-01

BACKGROUND: Elevated resting heart rate (RHR) is associated with cardiovascular mortality and morbidity. Assessment of heart rate (HR) from Holter recording may afford a more precise estimate of the effect of RHR on cardiovascular risk, as compared to casual RHR. Comparative analysis was carried ...

A new algorithm for ECG interference removal from single channel EMG recording.

Science.gov (United States)

Yazdani, Shayan; Azghani, Mahmood Reza; Sedaaghi, Mohammad Hossein

2017-09-01

This paper presents a new method to remove electrocardiogram (ECG) interference from electromyogram (EMG). This interference occurs during the EMG acquisition from trunk muscles. The proposed algorithm employs progressive image denoising (PID) algorithm and ensembles empirical mode decomposition (EEMD) to remove this type of interference. PID is a very recent method that is being used for denoising digital images mixed with white Gaussian noise. It detects white Gaussian noise by deterministic annealing. To the best of our knowledge, PID has never been used before, in the case of EMG and ECG separation or in other 1D signal denoising applications. We have used it according to this fact that amplitude of the EMG signal can be modeled as white Gaussian noise using a filter with time-variant properties. The proposed algorithm has been compared to the other well-known methods such as HPF, EEMD-ICA, Wavelet-ICA and PID. The results show that the proposed algorithm outperforms the others, on the basis of three evaluation criteria used in this paper: Normalized mean square error, Signal to noise ratio and Pearson correlation.

ECG-gated myocardial tomo-scintigraphy by rotating bilateral collimator. Clinical application and artificial defect

Energy Technology Data Exchange (ETDEWEB)

Komatani, Akio; Takahashi, Kazuei; Takanashi, Toshiyasu; Yamaguchi, Koichi [Yamagata Univ. (Japan)

1985-01-01

Tomo-scintigraphy of /sup 201/Tl-myocardium by rotating bilateral collimator was performed in synchronization with cardiac cycle. Ten frames per R-R interval were acquired with ECG pulse signal during 16 min and tomographic reconstruction of end-diastolic and end-systolic image was done. This method was very useful to estimate not only three dimensional distribution of Tl-201, but also wall motion and change of wall thickness during cardiac cycle. However, through its clinical application, artificial defect was frequently noticed at inferior-apical portion of the myocardium. In order to elucidate the cause of the artifact, influence of tilted projection and cardiac motion due to respiratory was also investigated. During inspiratory phase of patients in rest, increment of volume up to 40% and 15 mm of caudal deviation of the left ventricle were observed. Furthermore, periodic motion of the diaphragm interrupted emission of gamma ray from the myocardium. It is proved that main cause of the artifact was not tilting projection, but these influence of respiratory motion.

Accuracy of ECG indices for diagnosis of left ventricular hypertrophy in people >65 years: results from the ActiFE study.

Science.gov (United States)

Laszlo, Roman; Kunz, Katia; Dallmeier, Dhayana; Klenk, Jochen; Denkinger, Michael; Koenig, Wolfgang; Rothenbacher, Dietrich; Steinacker, Juergen Michael

2017-10-01

The detection of left ventricular hypertrophy (LVH) is still a common objective of electrocardiography (ECG) in clinical practice. The aim of our study was to evaluate the accuracy of LVH ECG indices in people older than 65 recruited from a population-based cohort (ActiFE-Ulm study). In 432 subjects (mean age 76.2 ± 5.5 years, 51% male), left ventricular mass was echocardiographically determined (Devereux formula) and indexed (LVMI) to body surface area. Several LVH ECG indices (Lewis voltage, Gubner-Ungerleider voltage, Sokolow-Lyon voltage/product, Cornell voltage/product) were calculated with the help of resting ECG data and compared with the echocardiographic assessment. Despite echocardiographic signs of LVH [LVMI > 115 (♂) or >95 g/m 2 (♀)] in 47.5% of all subjects, diagnostic performance of all ECG indices was generally low. Magnitude of all LVH-indices was mainly predicted by frontal QRS axis in multivariate linear regression analysis. In comparison with the literature data from younger subjects, average frontal QRS axis turned counterclockwise. Most probably, age-related counterclockwise turn of frontal QRS axis is mainly explanatory for the decreased magnitude of LVH ECG indices and consecutive worse diagnostic performance of these indices in the elderly. ECG indices for detection of LVH have insufficient predictive values in geriatric subjects and should therefore not be used clinically for this purpose. Nevertheless, due to its established relevancy in cardiac risk stratification in this age group, usage of some established ECG indices might keep its significance even in the age of modern cardiac imaging.

'Brugada ECG' elicited by imipramine overdose

NARCIS (Netherlands)

van den Berg, M. P.; Tulleken, J. E.; Wilde, A. A. M.

2004-01-01

The ECG hallmark of the Brugada syndrome is ST-segment elevation in the right precordial leads. However, a 'Brugada ECG' may also occasionally be caused by other conditions. We report a case of a Brugada ECG due to an overdose of imipramine, a tricyclic antidepressant. The patient, a 66-year-old

Downregulation of the Repressor Element 1-Silencing Transcription Factor (REST Is Associated with Akt-mTOR and Wnt-β-Catenin Signaling in Prion Diseases Models

Directory of Open Access Journals (Sweden)

Zhiqi Song

2017-05-01

Full Text Available Prion diseases are a group of infectious diseases characterized by multiple neuropathological changes, yet the mechanisms that preserve function and protect against prion-associated neurodegeneration are still unclear. We previously reported that the repressor element 1-silencing transcription factor (REST alleviates neurotoxic prion peptide (PrP106-126-induced toxicity in primary neurons. Here we confirmed the findings of the in vitro model in 263K infected hamsters, an in vivo model of prion diseases and further showed the relationships between REST and related signaling pathways. REST was depleted from the nucleus in prion infected brains and taken up by autophagosomes in the cytoplasm, co-localizing with LC3-II. Importantly, downregulation of the Akt–mTOR and at least partially inactivation of LRP6-Wnt-β-catenin signaling pathways correlated with the decreased levels of REST in vivo in the brain of 263K-infected hamsters and in vitro in PrP106-126-treated primary neurons. Overexpression of REST in primary cortical neurons alleviated PrP106-126 peptide-induced neuronal oxidative stress, mitochondrial damage and partly inhibition of the LRP6-Wnt-β-catenin and Akt–mTOR signaling. Based on our findings, a model of REST-mediated neuroprotection in prion infected animals is proposed, with Akt–mTOR and Wnt-β-catenin signaling as the key pathways. REST-mediated neuronal survival signaling could be explored as a viable therapeutic target for prion diseases and related neurodegenerative diseases.

A Mobile Device System for Early Warning of ECG Anomalies

Directory of Open Access Journals (Sweden)

Adam Szczepański

2014-06-01

Full Text Available With the rapid increase in computational power of mobile devices the amount of ambient intelligence-based smart environment systems has increased greatly in recent years. A proposition of such a solution is described in this paper, namely real time monitoring of an electrocardiogram (ECG signal during everyday activities for identification of life threatening situations. The paper, being both research and review, describes previous work of the authors, current state of the art in the context of the authors’ work and the proposed aforementioned system. Although parts of the solution were described in earlier publications of the authors, the whole concept is presented completely for the first time along with the prototype implementation on mobile device—a Windows 8 tablet with Modern UI. The system has three main purposes. The first goal is the detection of sudden rapid cardiac malfunctions and informing the people in the patient’s surroundings, family and friends and the nearest emergency station about the deteriorating health of the monitored person. The second goal is a monitoring of ECG signals under non-clinical conditions to detect anomalies that are typically not found during diagnostic tests. The third goal is to register and analyze repeatable, long-term disturbances in the regular signal and finding their patterns.

e-SCP-ECG+ Protocol: An Expansion on SCP-ECG Protocol for Health Telemonitoring—Pilot Implementation

Directory of Open Access Journals (Sweden)

George J. Mandellos

2010-01-01

Full Text Available Standard Communication Protocol for Computer-assisted Electrocardiography (SCP-ECG provides standardized communication among different ECG devices and medical information systems. This paper extends the use of this protocol in order to be included in health monitoring systems. It introduces new sections into SCP-ECG structure for transferring data for positioning, allergies, and five additional biosignals: noninvasive blood pressure (NiBP, body temperature (Temp, Carbon dioxide (CO2, blood oxygen saturation (SPO2, and pulse rate. It also introduces new tags in existing sections for transferring comprehensive demographic data. The proposed enhanced version is referred to as e-SCP-ECG+ protocol. This paper also considers the pilot implementation of the new protocol as a software component in a Health Telemonitoring System.

Beat-to-beat ECG restitution: A review and proposal for a new biomarker to assess cardiac stress and ventricular tachyarrhythmia vulnerability.

Science.gov (United States)

Fossa, Anthony A

2017-09-01

Cardiac restitution is the ability of the heart to recover from one beat to the next. Ventricular arrhythmia vulnerability can occur when the heart does not properly adjust to sudden changes in rate or in hemodynamics leading to excessive temporal and/or spatial heterogeneity in conduction or repolarization. Restitution has historically been used to study, by invasive means, the dynamics of the relationship between action potential duration (APD) and diastolic interval (DI) in sedated subjects using various pacing protocols. Even though the analogous measures of APD and DI can be obtained using the surface ECG to acquire the respective QT and TQ intervals for ECG restitution, this methodology has not been widely adopted for a number of reasons. Recent development of more advanced software algorithms enables ECG intervals to be measured accurately, on a continuous beat-to-beat basis, in an automated manner, and under highly dynamic conditions (i.e., ambulatory or exercise) providing information beyond that available in the typical resting state. Current breakthroughs in ECG technology will allow ECG restitution measures to become a practical approach for providing quantitative measures of the risks for ventricular arrhythmias as well as cardiac stress in general. In addition to a review of the underlying principles and caveats of ECG restitution, a new approach toward an advancement of more integrated restitution biomarkers is proposed. © 2017 Wiley Periodicals, Inc.

An intelligent telecardiology system using a wearable and wireless ECG to detect atrial fibrillation.

Science.gov (United States)

Lin, Chin-Teng; Chang, Kuan-Cheng; Lin, Chun-Ling; Chiang, Chia-Cheng; Lu, Shao-Wei; Chang, Shih-Sheng; Lin, Bor-Shyh; Liang, Hsin-Yueh; Chen, Ray-Jade; Lee, Yuan-Teh; Ko, Li-Wei

2010-05-01

This study presents a novel wireless, ambulatory, real-time, and autoalarm intelligent telecardiology system to improve healthcare for cardiovascular disease, which is one of the most prevalent and costly health problems in the world. This system consists of a lightweight and power-saving wireless ECG device equipped with a built-in automatic warning expert system. This device is connected to a mobile and ubiquitous real-time display platform. The acquired ECG signals are instantaneously transmitted to mobile devices, such as netbooks or mobile phones through Bluetooth, and then, processed by the expert system. An alert signal is sent to the remote database server, which can be accessed by an Internet browser, once an abnormal ECG is detected. The current version of the expert system can identify five types of abnormal cardiac rhythms in real-time, including sinus tachycardia, sinus bradycardia, wide QRS complex, atrial fibrillation (AF), and cardiac asystole, which is very important for both the subjects who are being monitored and the healthcare personnel tracking cardiac-rhythm disorders. The proposed system also activates an emergency medical alarm system when problems occur. Clinical testing reveals that the proposed system is approximately 94% accurate, with high sensitivity, specificity, and positive prediction rates for ten normal subjects and 20 AF patients. We believe that in the future a business-card-like ECG device, accompanied with a mobile phone, can make universal cardiac protection service possible.

Radiotelemetry recording of electroencephalogram in piglets during rest.

Science.gov (United States)

Saito, Toshiyuki; Watanabe, Yasuko; Nemoto, Tetsu; Kasuya, Etsuko; Sakumoto, Ryosuke

2005-04-13

A wireless recording system was developed to study the electroencephalogram (EEG) in unrestrained, male Landrace piglets. Under general anesthesia, ball-tipped silver/silver chloride electrodes for EEG recording were implanted onto the dura matter of the parietal and frontal cortex of the piglets. A pair of miniature preamplifiers and transmitters was then mounted on the surface of the skull. To examine whether other bioelectrical activities interfere with the EEG measurements, an electrocardiogram (ECG) or electromyogram (EMG) of the neck was simultaneously recorded with the EEG. Next, wire electrodes for recording movement of the eyelid were implanted with EEG electrodes, and EEG and eyelid movements were simultaneously measured. Power spectral analysis using a Fast Fourier Transformation (FFT) algorithm indicates that EEG was successfully recorded in unrestrained piglets, at rest, during the daytime in the absence of interference from ECG, EMG or eyelid movements. These data indicate the feasibility of using our radiotelemetry system for measurement of EEG under these conditions.

Reliability and Reproducibility of Advanced ECG Parameters in Month-to-Month and Year-to-Year Recordings in Healthy Subjects

Science.gov (United States)

Starc, Vito; Abughazaleh, Ahmed S.; Schlegel, Todd T.

2014-01-01

Advanced resting ECG parameters such the spatial mean QRS-T angle and the QT variability index (QTVI) have important diagnostic and prognostic utility, but their reliability and reproducibility (R&R) are not well characterized. We hypothesized that the spatial QRS-T angle would have relatively higher R&R than parameters such as QTVI that are more responsive to transient changes in the autonomic nervous system. The R&R of several conventional and advanced ECG para-meters were studied via intraclass correlation coefficients (ICCs) and coefficients of variation (CVs) in: (1) 15 supine healthy subjects from month-to-month; (2) 27 supine healthy subjects from year-to-year; and (3) 25 subjects after transition from the supine to the seated posture. As hypothesized, for the spatial mean QRS-T angle and many conventional ECG parameters, ICCs we-re higher, and CVs lower than QTVI, suggesting that the former parameters are more reliable and reproducible.

[Analysis of pacemaker ECGs].

Science.gov (United States)

Israel, Carsten W; Ekosso-Ejangue, Lucy; Sheta, Mohamed-Karim

2015-09-01

The key to a successful analysis of a pacemaker electrocardiogram (ECG) is the application of the systematic approach used for any other ECG without a pacemaker: analysis of (1) basic rhythm and rate, (2) QRS axis, (3) PQ, QRS and QT intervals, (4) morphology of P waves, QRS, ST segments and T(U) waves and (5) the presence of arrhythmias. If only the most obvious abnormality of a pacemaker ECG is considered, wrong conclusions can easily be drawn. If a systematic approach is skipped it may be overlooked that e.g. atrial pacing is ineffective, the left ventricle is paced instead of the right ventricle, pacing competes with intrinsic conduction or that the atrioventricular (AV) conduction time is programmed too long. Apart from this analysis, a pacemaker ECG which is not clear should be checked for the presence of arrhythmias (e.g. atrial fibrillation, atrial flutter, junctional escape rhythm and endless loop tachycardia), pacemaker malfunction (e.g. atrial or ventricular undersensing or oversensing, atrial or ventricular loss of capture) and activity of specific pacing algorithms, such as automatic mode switching, rate adaptation, AV delay modifying algorithms, reaction to premature ventricular contractions (PVC), safety window pacing, hysteresis and noise mode. A systematic analysis of the pacemaker ECG almost always allows a probable diagnosis of arrhythmias and malfunctions to be made, which can be confirmed by pacemaker control and can often be corrected at the touch of the right button to the patient's benefit.

Respiratory Information Extraction from Electrocardiogram Signals

KAUST Repository

Amin, Gamal El Din Fathy

2010-01-01

The Electrocardiogram (ECG) is a tool measuring the electrical activity of the heart, and it is extensively used for diagnosis and monitoring of heart diseases. The ECG signal reflects not only the heart activity but also many other physiological

Local Wavelet-Based Filtering of Electromyographic Signals to Eliminate the Electrocardiographic-Induced Artifacts in Patients with Spinal Cord Injury.

Science.gov (United States)

Nitzken, Matthew; Bajaj, Nihit; Aslan, Sevda; Gimel'farb, Georgy; El-Baz, Ayman; Ovechkin, Alexander

2013-07-18

Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorders associated with motor control deficits. However, EMG potentials recorded from these muscles are often contaminated with heart-induced electrocardiographic (ECG) signals. Elimination of these artifacts plays a critical role in the precise measure of the respiratory muscle electrical activity. This study was undertaken to find an optimal approach to eliminate the ECG artifacts from EMG recordings. Conventional global filtering can be used to decrease the ECG-induced artifact. However, this method can alter the EMG signal and changes physiologically relevant information. We hypothesize that, unlike global filtering, localized removal of ECG artifacts will not change the original EMG signals. We develop an approach to remove the ECG artifacts without altering the amplitude and frequency components of the EMG signal by using an externally recorded ECG signal as a mask to locate areas of the ECG spikes within EMG data. These segments containing ECG spikes were decomposed into 128 sub-wavelets by a custom-scaled Morlet Wavelet Transform. The ECG-related sub-wavelets at the ECG spike location were removed and a de-noised EMG signal was reconstructed. Validity of the proposed method was proven using mathematical simulated synthetic signals and EMG obtained from SCI patients. We compare the Root-mean Square Error and the Relative Change in Variance between this method, global, notch and adaptive filters. The results show that the localized wavelet-based filtering has the benefit of not introducing error in the native EMG signal and accurately removing ECG artifacts from EMG signals.

Robust electrocardiogram (ECG) beat classification using discrete wavelet transform

International Nuclear Information System (INIS)

Minhas, Fayyaz-ul-Amir Afsar; Arif, Muhammad

2008-01-01

This paper presents a robust technique for the classification of six types of heartbeats through an electrocardiogram (ECG). Features extracted from the QRS complex of the ECG using a wavelet transform along with the instantaneous RR-interval are used for beat classification. The wavelet transform utilized for feature extraction in this paper can also be employed for QRS delineation, leading to reduction in overall system complexity as no separate feature extraction stage would be required in the practical implementation of the system. Only 11 features are used for beat classification with the classification accuracy of ∼99.5% through a KNN classifier. Another main advantage of this method is its robustness to noise, which is illustrated in this paper through experimental results. Furthermore, principal component analysis (PCA) has been used for feature reduction, which reduces the number of features from 11 to 6 while retaining the high beat classification accuracy. Due to reduction in computational complexity (using six features, the time required is ∼4 ms per beat), a simple classifier and noise robustness (at 10 dB signal-to-noise ratio, accuracy is 95%), this method offers substantial advantages over previous techniques for implementation in a practical ECG analyzer

Study on a Biometric Authentication Model based on ECG using a Fuzzy Neural Network

Science.gov (United States)

Kim, Ho J.; Lim, Joon S.

2018-03-01

Traditional authentication methods use numbers or graphic passwords and thus involve the risk of loss or theft. Various studies are underway regarding biometric authentication because it uses the unique biometric data of a human being. Biometric authentication technology using ECG from biometric data involves signals that record electrical stimuli from the heart. It is difficult to manipulate and is advantageous in that it enables unrestrained measurements from sensors that are attached to the skin. This study is on biometric authentication methods using the neural network with weighted fuzzy membership functions (NEWFM). In the biometric authentication process, normalization and the ensemble average is applied during preprocessing, characteristics are extracted using Haar-wavelets, and a registration process called “training” is performed in the fuzzy neural network. In the experiment, biometric authentication was performed on 73 subjects in the Physionet Database. 10-40 ECG waveforms were tested for use in the registration process, and 15 ECG waveforms were deemed the appropriate number for registering ECG waveforms. 1 ECG waveforms were used during the authentication stage to conduct the biometric authentication test. Upon testing the proposed biometric authentication method based on 73 subjects from the Physionet Database, the TAR was 98.32% and FAR was 5.84%.

Cost-effectiveness of pre-participation screening of athletes with ECG in Europe and Algeria.

Science.gov (United States)

Assanelli, Deodato; Levaggi, Rosella; Carré, François; Sharma, Sanjay; Deligiannis, Asterios; Mellwig, Klaus Peter; Tahmi, Mohamed; Vinetti, Giovanni; Aliverti, Paola

2015-03-01

The aim of this study is to evaluate the cost-effectiveness of ECG in combination with family and personal history and physical examination in order to detect cardiovascular diseases that might cause sudden death in athletes. The study was conducted on a cohort of 6,634, mainly young professional and recreational athletes, 1,071 from Algeria and 5,563 from Europe (France, Germany and Greece). Each athlete underwent medical history, physical examination, and resting 12-lead ECG. 293 athletes (4.4 %), 149 in Europe (2.7 %) and 144 in Algeria (13.4 %) required further tests, and 56 were diagnosed with cardiovascular disease and thus disqualified. The cost-effectiveness ratio (CER) was calculated as the ratio between the cost of screening and the number of statistical life-years saved by the intervention. The estimated reduced risk of death deriving from treatment or disqualification resulted in the saving of 79.1 statistical life-years in Europe and 136.3 in Algeria. CER of screening was 4,071 purchasing-power-parity-adjusted US dollars ($PPP) in Europe and 582 $PPP in Algeria. The results of this study strongly support the utilisation of 12-lead ECG in the pre-participation screening of young athletes, especially in countries where secondary preventive care is not highly developed.

Multi detector computed tomography (MDCT) of the aortic root; ECG-gated verses non-ECG-gated examinations

International Nuclear Information System (INIS)

Kristiansen, Joanna; Guenther, Anne; Aalokken, Trond Mogens; Andersen, Rune

2011-01-01

Purpose: Motion artifacts may degrade a conventional CT examination of the ascending aorta and hinder accurate diagnosis. We quantitatively compared retrospectively electrocardiographic (ECG) -gated multi detector computed tomography (MDCT) with non-ECG-gated MDCT in order to demonstrate whether or not one of the methods should be preferred. Method: The study included seventeen patients with surgically reconstructed aortic root and reimplanted coronary arteries. All patients had undergone both non-gated MDCT and retrospectively ECG-gated MDCT employing a stringently modulated tube current with single phase image reconstruction. The incidence of motion artifacts in the left main coronary artery (LM), proximal right coronary artery (RCA), and aortic root and ascending aorta were rated using a four point scale. The effective dose for each scan was calculated and normalized to a 15 cm scan length. Statistical analysis of motion artifacts and radiation dose was performed using Wilcoxon matched pairs signed rank sum test. Results: A significant reduction in motion artifacts was found in all three vessels in images from the retrospectively ECG-gated scans (LM: P = 0.005, RCA: P = 0.015, aorta: P = 0.003). The mean normalized effective radiation dose was 3.69 mSv (±1.03) for the non-ECG-gated scans and 16.37 mSv (±2.53) for the ECG-gated scans. Conclusion: Retrospective ECG-gating with single phase reconstruction significantly reduces the incidence of motion artifacts in the aortic root and the proximal portion of the coronary arteries but at the expense of a fourfold increase in radiation dose.

Sequential Markov chain Monte Carlo filter with simultaneous model selection for electrocardiogram signal modeling.

Science.gov (United States)

Edla, Shwetha; Kovvali, Narayan; Papandreou-Suppappola, Antonia

2012-01-01

Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can be used for automated disease classification, is of great importance in precluding manual annotation and providing prompt diagnosis of cardiac diseases. ECG signals consist of several segments with different morphologies (namely the P wave, QRS complex and the T wave) in a single heart beat, which can vary across individuals and diseases. Also, existing statistical ECG models exhibit a reliance upon obtaining a priori information from the ECG data by using preprocessing algorithms to initialize the filter parameters, or to define the user-specified model parameters. In this paper, we propose an ECG modeling technique using the sequential Markov chain Monte Carlo (SMCMC) filter that can perform simultaneous model selection, by adaptively choosing from different representations depending upon the nature of the data. Our results demonstrate the ability of the algorithm to track various types of ECG morphologies, including intermittently occurring ECG beats. In addition, we use the estimated model parameters as the feature set to classify between ECG signals with normal sinus rhythm and four different types of arrhythmia.

A novel LabVIEW-based multi-channel non-invasive abdominal maternal-fetal electrocardiogram signal generator.

Science.gov (United States)

Martinek, Radek; Kelnar, Michal; Koudelka, Petr; Vanus, Jan; Bilik, Petr; Janku, Petr; Nazeran, Homer; Zidek, Jan

2016-02-01

This paper describes the design, construction, and testing of a multi-channel fetal electrocardiogram (fECG) signal generator based on LabVIEW. Special attention is paid to the fetal heart development in relation to the fetus' anatomy, physiology, and pathology. The non-invasive signal generator enables many parameters to be set, including fetal heart rate (FHR), maternal heart rate (MHR), gestational age (GA), fECG interferences (biological and technical artifacts), as well as other fECG signal characteristics. Furthermore, based on the change in the FHR and in the T wave-to-QRS complex ratio (T/QRS), the generator enables manifestations of hypoxic states (hypoxemia, hypoxia, and asphyxia) to be monitored while complying with clinical recommendations for classifications in cardiotocography (CTG) and fECG ST segment analysis (STAN). The generator can also produce synthetic signals with defined properties for 6 input leads (4 abdominal and 2 thoracic). Such signals are well suited to the testing of new and existing methods of fECG processing and are effective in suppressing maternal ECG while non-invasively monitoring abdominal fECG. They may also contribute to the development of a new diagnostic method, which may be referred to as non-invasive trans-abdominal CTG +  STAN. The functional prototype is based on virtual instrumentation using the LabVIEW developmental environment and its associated data acquisition measurement cards (DAQmx). The generator also makes it possible to create synthetic signals and measure actual fetal and maternal ECGs by means of bioelectrodes.

On the resolution of ECG acquisition systems for the reliable analysis of the P-wave

International Nuclear Information System (INIS)

Censi, Federica; Calcagnini, Giovanni; Mattei, Eugenio; Triventi, Michele; Bartolini, Pietro; Corazza, Ivan; Boriani, Giuseppe

2012-01-01

The analysis of the P-wave on surface ECG is widely used to assess the risk of atrial arrhythmias. In order to provide reliable results, the automatic analysis of the P-wave must be precise and reliable and must take into account technical aspects, one of those being the resolution of the acquisition system. The aim of this note is to investigate the effects of the amplitude resolution of ECG acquisition systems on the P-wave analysis. Starting from ECG recorded by an acquisition system with a less significant bit (LSB) of 31 nV (24 bit on an input range of 524 mVpp), we reproduced an ECG signal as acquired by systems with lower resolution (16, 15, 14, 13 and 12 bit). We found that, when the LSB is of the order of 128 µV (12 bit), a single P-wave is not recognizable on ECG. However, when averaging is applied, a P-wave template can be extracted, apparently suitable for the P-wave analysis. Results obtained in terms of P-wave duration and morphology revealed that the analysis of ECG at lowest resolutions (from 12 to 14 bit, LSB higher than 30 µV) could lead to misleading results. However, the resolution used nowadays in modern electrocardiographs (15 and 16 bit, LSB <10 µV) is sufficient for the reliable analysis of the P-wave. (note)

Clinical applications of resting state functional connectivity

Directory of Open Access Journals (Sweden)

Michael D Fox

2010-06-01

Full Text Available During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level dependent (BOLD signal of fMRI. The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI and has the potential to greatly increase the translation of fMRI into clinical care. In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations. We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm.

Evaluation of cardiac signals using discrete wavelet transform with MATLAB graphical user interface.

Science.gov (United States)

John, Agnes Aruna; Subramanian, Aruna Priyadharshni; Jaganathan, Saravana Kumar; Sethuraman, Balasubramanian

2015-01-01

To process the electrocardiogram (ECG) signals using MATLAB-based graphical user interface (GUI) and to classify the signals based on heart rate. The subject condition was identified using R-peak detection based on discrete wavelet transform followed by a Bayes classifier that classifies the ECG signals. The GUI was designed to display the ECG signal plot. Obtained from MIT database 18 patients had normal heart rate and 9 patients had abnormal heart rate; 14.81% of the patients suffered from tachycardia and 18.52% of the patients have bradycardia. The proposed GUI display was found useful to analyze the digitized ECG signal by a non-technical user and may help in diagnostics. Further improvement can be done by employing field programmable gate array for the real time processing of cardiac signals. Copyright © 2015 Cardiological Society of India. Published by Elsevier B.V. All rights reserved.

Wearable Current-Based ECG Monitoring System with Non-Insulated Electrodes for Underwater Application

Directory of Open Access Journals (Sweden)

Stefan Gradl

2017-12-01

Full Text Available The second most common cause of diving fatalities is cardiovascular diseases. Monitoring the cardiovascular system in actual underwater conditions is necessary to gain insights into cardiac activity during immersion and to trigger preventive measures. We developed a wearable, current-based electrocardiogram (ECG device in the eco-system of the FitnessSHIRT platform. It can be used for normal/dry ECG measuring purposes but is specifically designed to allow underwater signal acquisition without having to use insulated electrodes. Our design is based on a transimpedance amplifier circuit including active current feedback. We integrated additional cascaded filter components to counter noise characteristics specific to the immersed condition of such a system. The results of the evaluation show that our design is able to deliver high-quality ECG signals underwater with no interferences or loss of signal quality. To further evaluate the applicability of the system, we performed an applied study with it using 12 healthy subjects to examine whether differences in the heart rate variability exist between sitting and supine positions of the human body immersed in water and outside of it. We saw significant differences, for example, in the RMSSD and SDSD between sitting outside the water (36 ms and sitting immersed in water (76 ms and the pNN50 outside the water (6.4% and immersed in water (18.2%. The power spectral density for the sitting positions in the TP and HF increased significantly during water immersion while the LF/HF decreased significantly. No significant changes were found for the supine position.

A portable ECG monitoring device with Bluetooth and Holter capabilities for telemedicine applications.

Science.gov (United States)

Lucani, Daniel; Cataldo, Giancarlos; Cruz, Julio; Villegas, Guillermo; Wong, Sara

2006-01-01

A prototype of a portable ECG-monitoring device has been developed for clinical and non-clinical environments as part of a telemedicine system to provide remote and continuous surveillance of patients. The device can acquire, store and/or transmit ECG signals to computer-based platforms or specially configured access points (AP) with Intranet/Internet capabilities in order to reach remote monitoring stations. Acquired data can be stored in a flash memory card in FAT16 format for later recovery, or transmitted via Bluetooth or USB to a local station or AP. This data acquisition module (DAM) operates in two modes: Holter and on-line transmission.

Sticker-type ECG/PPG concurrent monitoring system hybrid integration of CMOS SoC and organic sensor device.

Science.gov (United States)

Yongsu Lee; Hyeonwoo Lee; Seunghyup Yoo; Hoi-Jun Yoo

2016-08-01

The sticker-type sensor system is proposed targeting ECG/PPG concurrent monitoring for cardiovascular diseases. The stickers are composed of two types: Hub and Sensor-node (SN) sticker. Low-power CMOS SoC for measuring ECG and PPG signal is hybrid integrated with organic light emitting diodes (OLEDs) and organic photo detector (OPD). The sticker has only 2g weight and only consumes 141μW. The optical calibration loop is adopted for maintaining SNR of PPG signal higher than 30dB. The pulse arrival time (PAT) and SpO2 value can be extracted from various body parts and verified comparing with the reference device from 20 people in-vivo experiments.

Performance of an Ambulatory Cardiorespiratory Monitoring System During Rest and Exercise

National Research Council Canada - National Science Library

Karis, Anthony

2003-01-01

...), and blood oxygen saturation (SpO2). The results showed that signal performance across all activity levels and sensor types was able to provide an acceptable signal 84% of the time (ECG=96.9 +/- 3.0%, RESP=71.2 +/- 13.1%, and SpO2=83.7 +/- 13.8...

New methodologies for measuring Brugada ECG patterns cannot differentiate the ECG pattern of Brugada syndrome from Brugada phenocopy.

Science.gov (United States)

Gottschalk, Byron H; Garcia-Niebla, Javier; Anselm, Daniel D; Jaidka, Atul; De Luna, Antoni Bayés; Baranchuk, Adrian

2016-01-01

Brugada phenocopies (BrP) are clinical entities characterized by ECG patterns that are identical to true Brugada syndrome (BrS), but are elicited by various clinical circumstances. A recent study demonstrated that the patterns of BrP and BrS are indistinguishable under the naked eye, thereby validating the concept that the patterns are identical. The aim of our study was to determine whether recently developed ECG criteria would allow for discrimination between type-2 BrS ECG pattern and type-2 BrP ECG pattern. Ten ECGs from confirmed BrS (aborted sudden death, transformation into type 1 upon sodium channel blocking test and/or ventricular arrhythmias, positive genetics) cases and 9 ECGs from confirmed BrP were included in the study. Surface 12-lead ECGs were scanned, saved in JPEG format for blind measurement of two values: (i) β-angle; and (ii) the base of the triangle. Cut-off values of ≥58° for the β-angle and ≥4mm for the base of the triangle were used to determine the BrS ECG pattern. Mean values for the β-angle in leads V1 and V2 were 66.7±25.5 and 55.4±28.1 for BrS and 54.1±26.5 and 43.1±16.1 for BrP respectively (p=NS). Mean values for the base of the triangle in V1 and V2 were 7.5±3.9 and 5.7±3.9 for BrS and 5.6±3.2 and 4.7±2.7 for BrP respectively (p=NS). The β-angle had a sensitivity of 60%, specificity of 78% (LR+ 2.7, LR- 0.5). The base of the triangle had a sensitivity of 80%, specificity of 40% (LR+ 1.4, LR- 0.5). New ECG criteria presented relatively low sensitivity and specificity, positive and negative predictive values to discriminate between BrS and BrP ECG patterns, providing further evidence that the two patterns are identical. Copyright © 2016 Elsevier Inc. All rights reserved.

Smart ECG Monitoring Patch with Built-in R-Peak Detection for Long-Term HRV Analysis.

Science.gov (United States)

Lee, W K; Yoon, H; Park, K S

2016-07-01

Since heart rate variability (HRV) analysis is widely used to evaluate the physiological status of the human body, devices specifically designed for such applications are needed. To this end, we developed a smart electrocardiography (ECG) patch. The smart patch measures ECG using three electrodes integrated into the patch, filters the measured signals to minimize noise, performs analog-to-digital conversion, and detects R-peaks. The measured raw ECG data and the interval between the detected R-peaks can be recorded to enable long-term HRV analysis. Experiments were performed to evaluate the performance of the built-in R-wave detection, robustness of the device under motion, and applicability to the evaluation of mental stress. The R-peak detection results obtained with the device exhibited a sensitivity of 99.29%, a positive predictive value of 100.00%, and an error of 0.71%. The device also exhibited less motional noise than conventional ECG recording, being stable up to a walking speed of 5 km/h. When applied to mental stress analysis, the device evaluated the variation in HRV parameters in the same way as a normal ECG, with very little difference. This device can help users better understand their state of health and provide physicians with more reliable data for objective diagnosis.

Pre-Hospital ECG E-Transmission for Patients with Suspected Myocardial Infarction in the Highlands of Scotland

Directory of Open Access Journals (Sweden)

Gordon F. Rushworth

2014-02-01

Full Text Available Patients with ST elevation myocardial infarction (STEMI require prompt treatment, best done by primary percutaneous coronary intervention (PPCI. However, for patients unable to receive PPCI, immediate pre-hospital thrombolysis (PHT is the best alternative. Evidence indicates that diagnostic and management support for staff increases the use of PHT. This study aimed to describe the patient demographics and management of patients, to determine any potential inter-area differences in referral rates to the ECG e-transmission service and to explore the views and experiences of key staff involved in ECG e-transmission within NHS Highland. Data from 2,025 patient episodes of ECG e-transmission identified a statistically significant geographical variation in ECG e-transmission and PHT delivery. Scottish Ambulance Service (SAS staff were more likely than GPs to deliver PHT overall, however, GPs were more likely to deliver in remote areas. Interviews with six Cardiac Care Unit (CCU nurses and six SAS staff highlighted their positive views of ECG e-transmission, citing perceived benefits to patients and interprofessional relationships. Poor access to network signal was noted to be a barrier to engaging in the system. This study has demonstrated that a specialist triage service based on e-transmission of ECGs in patients with suspected STEMI can be implemented in a diverse geographical setting. Work is needed to ensure equity of the service for all patients.

Resting-state FMRI confounds and cleanup

Science.gov (United States)

Murphy, Kevin; Birn, Rasmus M.; Bandettini, Peter A.

2013-01-01

The goal of resting-state functional magnetic resonance imaging (FMRI) is to investigate the brain’s functional connections by using the temporal similarity between blood oxygenation level dependent (BOLD) signals in different regions of the brain “at rest” as an indicator of synchronous neural activity. Since this measure relies on the temporal correlation of FMRI signal changes between different parts of the brain, any non-neural activity-related process that affects the signals will influence the measure of functional connectivity, yielding spurious results. To understand the sources of these resting-state FMRI confounds, this article describes the origins of the BOLD signal in terms of MR physics and cerebral physiology. Potential confounds arising from motion, cardiac and respiratory cycles, arterial CO2 concentration, blood pressure/cerebral autoregulation, and vasomotion are discussed. Two classes of techniques to remove confounds from resting-state BOLD time series are reviewed: 1) those utilising external recordings of physiology and 2) data-based cleanup methods that only use the resting-state FMRI data itself. Further methods that remove noise from functional connectivity measures at a group level are also discussed. For successful interpretation of resting-state FMRI comparisons and results, noise cleanup is an often over-looked but essential step in the analysis pipeline. PMID:23571418

Human Identification by Cross-Correlation and Pattern Matching of Personalized Heartbeat: Influence of ECG Leads and Reference Database Size.

Science.gov (United States)

Jekova, Irena; Krasteva, Vessela; Schmid, Ramun

2018-01-27

Human identification (ID) is a biometric task, comparing single input sample to many stored templates to identify an individual in a reference database. This paper aims to present the perspectives of personalized heartbeat pattern for reliable ECG-based identification. The investigations are using a database with 460 pairs of 12-lead resting electrocardiograms (ECG) with 10-s durations recorded at time-instants T1 and T2 > T1 + 1 year. Intra-subject long-term ECG stability and inter-subject variability of personalized PQRST (500 ms) and QRS (100 ms) patterns is quantified via cross-correlation, amplitude ratio and pattern matching between T1 and T2 using 7 features × 12-leads. Single and multi-lead ID models are trained on the first 230 ECG pairs. Their validation on 10, 20, ... 230 reference subjects (RS) from the remaining 230 ECG pairs shows: (i) two best single-lead ID models using lead II for a small population RS = (10-140) with identification accuracy AccID = (89.4-67.2)% and aVF for a large population RS = (140-230) with AccID = (67.2-63.9)%; (ii) better performance of the 6-lead limb vs. the 6-lead chest ID model-(91.4-76.1)% vs. (90.9-70)% for RS = (10-230); (iii) best performance of the 12-lead ID model-(98.4-87.4)% for RS = (10-230). The tolerable reference database size, keeping AccID > 80%, is RS = 30 in the single-lead ID scenario (II); RS = 50 (6 chest leads); RS = 100 (6 limb leads), RS > 230-maximal population in this study (12-lead ECG).

Ecg changes after dipyridamole infusion in patients undergoing myocardial perfusion imaging

International Nuclear Information System (INIS)

Taherpour, M.; Zakavi, R.; Ariana, K.

2002-01-01

Dipyridamole is used as the main pharmacological stress agent in patient referred for myocardial perfusion imaging. This vasodilator agent makes difference between normal and abnormal coronary perfusion. Some authors believe that post-Dipyridamole Ecg changes have low sensitivity and relatively high specificity for ischemic detection. This study tries to evaluate this issue. All patients who referred to nuclear medicine department for Myocardial Perfusion Imaging and were not suitable for treadmill E T T, and had no L BBB pattern in basal Ecg were included in the study. Basal and post Dipyridamole Ecg were interpreted with a cardiologist after infusion of 142 u g/kg/min of Dipyridamole and all changes as well as basal Ecg abnormalities were recorded. Also Q Tc were calculated in all Ecg records: M P Is were interpreted by a nuclear medicine specialist and summed stress and rest scores were determined. Two hundred patients including 89 female (44.5%) and 111 male (55.5%) with a mean age of 55.2 years and age range of 30-85 years were studied. Mean basal and post Dipyridamole heart rates were 72.2/min and 84.8/min and mean basal and post Dipyridamole Qt Cs were 419.6 msec and 435.7 msec respectively. New Ecg changes were noted in 22.5% of cases and consisted of 1% T-wave flattening, 1% T-wave inversion, 16.5% St depression and 4% Pseudo normalization. Horizontal pattern was the main type of St segment depression (83.%) among new S T changes. Mean St depression severity was 0.8 mm with a range of 0.5-2 mm. New St depression was noted in lateral leads (Excluding high lateral) in 62.5% of new S T changes. M P I was interpreted normal in 4% of cases and showed some degrees of ischemia in 42% of the cases. The mean post Dipyridamole heart rate increment, was 11.2/ min patients with abnormal scintigraphy (infarct and/or ischemia) compared to 14.5/ min in normal cases. (P=0.009). Also Qt c increment in patients with ischemia was significantly more than patients with simple

Study design and rationale for biomedical shirt-based electrocardiography monitoring in relevant clinical situations: ECG-shirt study.

Science.gov (United States)

Balsam, Paweł; Lodziński, Piotr; Tymińska, Agata; Ozierański, Krzysztof; Januszkiewicz, Łukasz; Główczyńska, Renata; Wesołowska, Katarzyna; Peller, Michał; Pietrzak, Radosław; Książczyk, Tomasz; Borodzicz, Sonia; Kołtowski, Łukasz; Borkowski, Mariusz; Werner, Bożena; Opolski, Grzegorz; Grabowski, Marcin

2018-01-01

Today, the main challenge for researchers is to develop new technologies which may help to improve the diagnoses of cardiovascular disease (CVD), thereby reducing healthcare costs and improving the quality of life for patients. This study aims to show the utility of biomedical shirt-based electrocardiography (ECG) monitoring of patients with CVD in different clinical situations using the Nuubo® ECG (nECG) system. An investigator-initiated, multicenter, prospective observational study was carried out in a cardiology (adult and pediatric) and cardiac rehabilitation wards. ECG monitoring was used with the biomedical shirt in the following four independent groups of patients: 1) 30 patients after pulmonary vein isolation (PVI), 2) 30 cardiac resynchronization therapy (CRT) recipients, 3) 120 patients during cardiac rehabilitation after myocardial infarction, and 4) 40 pediatric patients with supraventricular tachycardia (SVT) before electrophysiology study. Approval for all study groups was obtained from the institutional review board. The biomedical shirt captures the electrocardiographic signal via textile electrodes integrated into a garment. The software allows the visualization and analysis of data such as ECG, heart rate, arrhythmia detecting algorithm and relative position of the body is captured by an electronic device. The major advantages of the nECG system are continuous ECG monitoring during daily activities, high quality of ECG recordings, as well as assurance of a proper adherence due to adequate comfort while wearing the shirt. There are only a few studies that have examined wearable systems, especially in pediatric populations. This study is registered in ClinicalTrials.gov: Identifier NCT03068169. (Cardiol J 2018; 25, 1: 52-59).

EP-based wavelet coefficient quantization for linear distortion ECG data compression.

Science.gov (United States)

Hung, King-Chu; Wu, Tsung-Ching; Lee, Hsieh-Wei; Liu, Tung-Kuan

2014-07-01

Reconstruction quality maintenance is of the essence for ECG data compression due to the desire for diagnosis use. Quantization schemes with non-linear distortion characteristics usually result in time-consuming quality control that blocks real-time application. In this paper, a new wavelet coefficient quantization scheme based on an evolution program (EP) is proposed for wavelet-based ECG data compression. The EP search can create a stationary relationship among the quantization scales of multi-resolution levels. The stationary property implies that multi-level quantization scales can be controlled with a single variable. This hypothesis can lead to a simple design of linear distortion control with 3-D curve fitting technology. In addition, a competitive strategy is applied for alleviating data dependency effect. By using the ECG signals saved in MIT and PTB databases, many experiments were undertaken for the evaluation of compression performance, quality control efficiency, data dependency influence. The experimental results show that the new EP-based quantization scheme can obtain high compression performance and keep linear distortion behavior efficiency. This characteristic guarantees fast quality control even for the prediction model mismatching practical distortion curve. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

ECG Denoising Using Marginalized Particle Extended Kalman Filter With an Automatic Particle Weighting Strategy.

Science.gov (United States)

Hesar, Hamed Danandeh; Mohebbi, Maryam

2017-05-01

algorithm had the lowest MSEPWRD for all noise types at low input SNRs. Therefore, the morphology and diagnostic information of ECG signals were much better conserved compared with EKF/EKS frameworks, especially in non-Gaussian nonstationary situations.

Validation of a raw data-based synchronization signal (kymogram) for phase-correlated cardiac image reconstruction

International Nuclear Information System (INIS)

Ertel, Dirk; Kachelriess, Marc; Kalender, Willi A.; Pflederer, Tobias; Achenbach, Stephan; Steffen, Peter

2008-01-01

Phase-correlated reconstruction is commonly used in computed tomography (CT)-based cardiac imaging. Alternatively to the commonly used ECG, the raw data-based kymogram function can be used as a synchronization signal. We used raw data of 100 consecutive patient exams to compare the performance of kymogram function to the ECG signal. For objective validation the correlation of the ECG and the kymogram was assessed. Additionally, we performed a double-blinded comparison of ECG-based and kymogram-based phase-correlated images. The two synchronization signals showed good correlation indicated by a mean difference in the detected heart rate of negligible 0.2 bpm. The mean image quality score was 2.0 points for kymogram-correlated images and 2.3 points for ECG-correlated images, respectively (3: best; 0: worst). The kymogram and the ECG provided images adequate for diagnosis for 93 and 97 patients, respectively. For 50% of the datasets the kymogram provided an equivalent or even higher image quality compared with the ECG signal. We conclude that an acceptable image quality can be assured in most cases by the kymogram. Improvements of image quality by the kymogram function were observed in a noticeable number of cases. The kymogram can serve as a backup solution when an ECG is not available or lacking in quality. (orig.)

Myocardial imaging with 201Tl at rest and during exercise. Comparison with coronary arteriography and resting and stress electrocardiography

International Nuclear Information System (INIS)

Ritchie, J.L.; Trobaugh, G.B.; Hamilton, G.W.; Gould, K.L.; Narahara, K.A.; Murray, J.A.; Williams, D.L.

1977-01-01

Myocardial imaging with intravenous thallium-201 ( 201 Tl) was performed at rest and following maximal treadmill exercise in 101 patients with suspected coronary artery disease. Results were interpreted from Polaroid scintiphotos by three independent observers with complete interobserver agreement in 79%. Of 25 patients with no or insignificant coronary artery disease ( 201 Tl image defect, one (4%) had an exercise 201 Tl defect, none had an ECG Q wave, and four (16%) had exercise ST-segment depression. Among 76 patients with coronary artery disease (greater than or equal to 50% diameter stenosis), 58 (76%) had a defect on either the rest or exercise 201 Tl image. The proportion of patients with an exercise image defect (50/76, 66%) was greater than the proportion with exercise ST depression alone (34/76, 45%; P 201 Tl is easily accomplished with readily available imaging equipment. The image data enhanced the diagnostic sensitivity of stress electrocardiography, and provided spatial identification of the abnormal segment(s) of myocardium

Common ECG Lead Placement Errors. Part I: Limb Lead Reversals

Directory of Open Access Journals (Sweden)

Allison V. Rosen

2015-10-01

Full Text Available Background: Electrocardiography (ECG is a very useful diagnostic tool. However, errors in placement of ECG leads can create artifacts, mimic pathologies, and hinder proper ECG interpretation. It is important for members of the health care team to be able to recognize the common patterns resulting from lead placement errors. Methods: 12-lead ECGs were recorded in a single male healthy subject in his mid 20s. Six different limb lead reversals were compared to ECG recordings from correct lead placement. Results: Classic ECG patterns were observed when leads were reversed. Methods of discriminating these ECG patterns from true pathologic findings were described. Conclusion: Correct recording and interpretation of ECGs is key to providing optimal patient care. It is therefore crucial to be able to recognize common ECG patterns that are indicative of lead reversals.

ECG-gating in non-cardiac digital subtraction angiography

International Nuclear Information System (INIS)

Gattoni, F.; Baldini, V.; Cairo, F.

1987-01-01

This paper reports the results of the ECG-gating in non-cardiac digital subtraction angiography (DSA). One hundred and fifteen patients underwent DSA (126 examinations); ECG-gating was applied in 66/126 examinations: images recorded at 70% of R wave were subtracted. Artifacts produced by vascular movements were evaluated in all patients: only 40 examinations, carried out whithout ECG-gating, showed vascular artifacts. The major advantage of the ECG-gated DSA is the more efficent subtraction because of the better images superimposition: therefore, ECG-gating can be clinically helpful. On the contrary, it could be a problem in arrhytmic or bradycardic patients. ECG-gating is helpful in DSA imaging of the thoracic and abdominal aorta and of the cervical and renal arteries. In the examinations of peripheral vessels of the limbs it is not so efficent as in the trunk or in the neck

Reliability of Computer Analysis of Electrocardiograms (ECG) of ...

African Journals Online (AJOL)

Background: Computer programmes have been introduced to electrocardiography (ECG) with most physicians in Africa depending on computer interpretation of ECG. This study was undertaken to evaluate the reliability of computer interpretation of the 12-Lead ECG in the Black race. Methodology: Using the SCHILLER ...

Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

Science.gov (United States)

Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

2017-06-01

A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

21 CFR 892.1970 - Radiographic ECG/respirator synchronizer.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Radiographic ECG/respirator synchronizer. 892.1970... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1970 Radiographic ECG/respirator synchronizer. (a) Identification. A radiographic ECG/respirator synchronizer is a device intended to be used to...

Expert knowledge for computerized ECG interpretation

NARCIS (Netherlands)

J.A. Kors (Jan)

1992-01-01

textabstractIn this study, two main questions are addressed: (1) Can the time consuming and cumbersome development and refinement of (heuristic) ECG classifiers be alleviated, and (2) Is it possible to increase diagnostic performance of ECG computer programs by combining knowledge from multiple

A wearable wireless ECG monitoring system with dynamic transmission power control for long-term homecare.

Science.gov (United States)

Wang, Yishan; Doleschel, Sammy; Wunderlich, Ralf; Heinen, Stefan

2015-03-01

This paper presents a wearable wireless ECG monitoring system based on novel 3-Lead electrode placements for long-term homecare. The experiment for novel 3-Lead electrode placements is carried out, and the results show that the distance between limb electrodes can be significantly reduced. Based on the new electrode position, a small size sensor node, which is powered by a rechargeable battery, is designed to detect, amplify, filter and transmit the ECG signals. The coordinator receives the data and sends it to PC. Finally the signals are displayed on the GUI. In order to control the power consumption of sensor node, a dynamic power adjustment method is applied to automatically adjust the transmission power of the sensor node according to the received signal strength indicator (RSSI), which is related to the distance and obstacle between sensor node and coordinator. The system is evaluated when the user, who wears the sensor, is walking and running. A promising performance is achieved even under body motion. The power consumption can be significantly reduced with this dynamic power adjustment method.

A cloud computing based 12-lead ECG telemedicine service.

Science.gov (United States)

Hsieh, Jui-Chien; Hsu, Meng-Wei

2012-07-28

Due to the great variability of 12-lead ECG instruments and medical specialists' interpretation skills, it remains a challenge to deliver rapid and accurate 12-lead ECG reports with senior cardiologists' decision making support in emergency telecardiology. We create a new cloud and pervasive computing based 12-lead Electrocardiography (ECG) service to realize ubiquitous 12-lead ECG tele-diagnosis. This developed service enables ECG to be transmitted and interpreted via mobile phones. That is, tele-consultation can take place while the patient is on the ambulance, between the onsite clinicians and the off-site senior cardiologists, or among hospitals. Most importantly, this developed service is convenient, efficient, and inexpensive. This cloud computing based ECG tele-consultation service expands the traditional 12-lead ECG applications onto the collaboration of clinicians at different locations or among hospitals. In short, this service can greatly improve medical service quality and efficiency, especially for patients in rural areas. This service has been evaluated and proved to be useful by cardiologists in Taiwan.

Research on comparison of exposure with electrocardiographic gated mA modulation (ECG) and ECG and CAREDose 4D mode in coronary multi-slice spiral CT angiography

International Nuclear Information System (INIS)

Liu Bin; Guo Senlin; Wei Lan; Fei Xiaolu; Bai Mei

2009-01-01

Objective: The objective of this article was to compare patients dose with electrocardiographic gated mA modulation (ECG) and ECG and CAREDose 4D mode during coronary MSCT angiography. Methods: The research was based on phantom experiment and computer simulation to get the mean value of peak skin dose data and effective dose data respectively and to analyze deterministic and stochastic radiation risk. Results: The peak skin dose using ECG mode alone and using ECG and CAREDose 4D mode with the same image noise level was (87.4 ± 0.9) and (45.9 ± 1.2) mGy respectively. Effective dose was 17 and 10 rosy for ECG mode and ECG and CAREDose 4D mode respectively. Comparing with ECG mode alone, ECG and CAREDose 4D mode reduced organ dose of gonad, red marrow, lung, stomach, breast and thyroid by 40.0%, 36.7%, 39.3%, 37.7%, 38.8% and 38.9%, respectively. Conclusion: Results showed that ECG and CAREDose 4D mode can reduce radiation dose effectively comparing using ECG mode alone, and that ECG and CAREDose 4D mode should be widely applied clinically with appropriate initial settings. (authors)

Automatic screening of obstructive sleep apnea from the ECG based on empirical mode decomposition and wavelet analysis

International Nuclear Information System (INIS)

Mendez, M O; Cerutti, S; Bianchi, A M; Corthout, J; Van Huffel, S; Matteucci, M; Penzel, T

2010-01-01

This study analyses two different methods to detect obstructive sleep apnea (OSA) during sleep time based only on the ECG signal. OSA is a common sleep disorder caused by repetitive occlusions of the upper airways, which produces a characteristic pattern on the ECG. ECG features, such as the heart rate variability (HRV) and the QRS peak area, contain information suitable for making a fast, non-invasive and simple screening of sleep apnea. Fifty recordings freely available on Physionet have been included in this analysis, subdivided in a training and in a testing set. We investigated the possibility of using the recently proposed method of empirical mode decomposition (EMD) for this application, comparing the results with the ones obtained through the well-established wavelet analysis (WA). By these decomposition techniques, several features have been extracted from the ECG signal and complemented with a series of standard HRV time domain measures. The best performing feature subset, selected through a sequential feature selection (SFS) method, was used as the input of linear and quadratic discriminant classifiers. In this way we were able to classify the signals on a minute-by-minute basis as apneic or nonapneic with different best-subset sizes, obtaining an accuracy up to 89% with WA and 85% with EMD. Furthermore, 100% correct discrimination of apneic patients from normal subjects was achieved independently of the feature extractor. Finally, the same procedure was repeated by pooling features from standard HRV time domain, EMD and WA together in order to investigate if the two decomposition techniques could provide complementary features. The obtained accuracy was 89%, similarly to the one achieved using only Wavelet analysis as the feature extractor; however, some complementary features in EMD and WA are evident

Wearable Textile Electrodes for ECG Measurement

Directory of Open Access Journals (Sweden)

Lukas Vojtech

2013-01-01

Full Text Available The electrocardiogram (ECG is one of the most important parameters for monitoring of the physiological state of a person. Currently available systems for ECG monitoring are both stationary and wearable, but the comfort of the monitored person is not at a satisfactory level because these systems are not part of standard clothing. This article is therefore devoted to the development and measurement of wearable textile electrodes for ECG measurement device with high comfort for the user. The electrode material is made of electrically conductive textile. This creates a textile composite that guarantees high comfort for the user while ensuring good quality of ECG measurements. The composite is implemented by a carrier (a T-shirt with flame retardant and sensing electrodes embroidered with yarn based on a mixture of polyester coated with silver nanoparticles and cotton. The electrodes not only provide great comfort but are also antibacterial and antiallergic due to silver nanoparticles.

Reconstruction of ECG signals in presence of corruption.

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Ganeshapillai, Gartheeban; Liu, Jessica F; Guttag, John

2011-01-01

We present an approach to identifying and reconstructing corrupted regions in a multi-parameter physiological signal. The method, which uses information in correlated signals, is specifically designed to preserve clinically significant aspects of the signals. We use template matching to jointly segment the multi-parameter signal, morphological dissimilarity to estimate the quality of the signal segment, similarity search using features on a database of templates to find the closest match, and time-warping to reconstruct the corrupted segment with the matching template. In experiments carried out on the MIT-BIH Arrhythmia Database, a two-parameter database with many clinically significant arrhythmias, our method improved the classification accuracy of the beat type by more than 7 times on a signal corrupted with white Gaussian noise, and increased the similarity to the original signal, as measured by the normalized residual distance, by more than 2.5 times.

Robust suppression of nonstationary power-line interference in electrocardiogram signals

International Nuclear Information System (INIS)

Li, Guojun; Zeng, Xiaopin; Zhou, Yu; Liu, Guojin; Zhou, Xichuan; Zhou, Xiaona

2012-01-01

It is a challenge to suppress time-varying power-line interference (PLI) with various levels in electrocardiogram (ECG) signals. Most previous attempts of tracking and suppressing the nonstationary PLI signal are based on the least-squares (LS) algorithm. This makes these methods susceptible to QRS complex in suppressing a low-level PLI signal which is frequently coupled in battery-operated ECG equipment. To address the limitation of LS-based methods, this study presents a robust PLI suppression system based on a robust extension of the Kalman filter. In addition, we used an improved version of empirical mode decomposition to further attenuate the QRS complex. Experiments show that our system could effectively suppress the PLI while preserving meaningful ECG components at various interference levels. (paper)

Interchangeability of electrocardiography and blood pressure measurement for determining heart rate and heart rate variability in free-moving domestic pigs in various behavioral contexts

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Annika eKrause

2015-11-01

Full Text Available This study assessed the interchangeability between heart rate (HR and heart rate variability (HRV measures derived from a series of interbeat intervals (IBIs recorded via electrocardiogram (ECG and intra-arterial blood pressure (BP in various behavioral contexts. Five minutes of simultaneously recorded IBIs from ECG and BP signals in 11 female domestic pigs during resting, feeding and active behavior were analyzed. Comparisons were made for measures of HR, SDNN (the standard deviation of IBIs and RMSSD (the root mean of the squared distances of subsequent IBIs derived from ECG and BP signals for each behavior category using statistical procedures with different explanatory power (linear regression, intraclass correlation coefficient (ICC, Bland and Altman plots and analysis of variance (ANOVA. Linear regression showed a strong relationship for HR during all behaviors and for HRV during resting. Excellent ICCs (lower 95% CI > 0.75 and narrow limits of agreement (LoA in all behavior categories were found for HR. ICCs for HRV reached the critical lower 95% CI value of 0.75 only during resting. Using Bland and Altman plots, HRV agreement was unacceptable for all of the behavior categories. ANOVA showed significant differences between the methods in terms of HRV. BP systematically overestimated HRV compared with ECG. Our findings reveal that HR data recorded via BP agree well those recorded using ECG independently of the activity of the subject, whereas ECG and BP cannot be used interchangeably in the context of HRV in free-moving domestic pigs.

A New Method to Detect Driver Fatigue Based on EMG and ECG Collected by Portable Non-Contact Sensors

Directory of Open Access Journals (Sweden)

Lin Wang

2017-11-01

Full Text Available Recently, detection and prediction on driver fatigue have become interest of research worldwide. In the present work, a new method is built to effectively evaluate driver fatigue based on electromyography (EMG and electrocardiogram (ECG collected by portable real-time and non-contact sensors. First, under the non-disturbance condition for driver’s attention, mixed physiological signals (EMG, ECG and artefacts are collected by non-contact sensors located in a cushion on the driver’s seat. EMG and ECG are effectively separated by FastICA, and de-noised by empirical mode decomposition (EMD. Then, three physiological features, complexity of EMG, complexity of ECG, and sample entropy (SampEn of ECG, are extracted and analysed. Principal components are obtained by principal components analysis (PCA and are used as independent variables. Finally, a mathematical model of driver fatigue is built, and the accuracy of the model is up to 91%. Moreover, based on the questionnaire, the calculation results of model are consistent with real fatigue felt by the participants. Therefore, this model can effectively detect driver fatigue.

Resting and postexercise heart rate variability in professional handball players.

Science.gov (United States)

Kayacan, Yildirim; Yildiz, Sedat

2016-03-01

The aim of this study was to evaluate heart rate variability (HRV) in professional handball players during rest and following a 5 min mild jogging exercise. For that purpose, electrocardiogram (ECG) of male handball players (N.=12, mean age 25±3.95 years) and sedentary controls (N.=14, mean age 23.5±2.95 years) were recorded for 5 min at rest and just after 5 min of mild jogging. ECGs were recorded and following HRV parameters were calculated: time-domain variables such as heart rate (HR), average normal-to-normal RR intervals, standard deviation of normal-to-normal RR intervals, square root of the mean of the squares of differences between adjacent NN intervals, percentage of differences between adjacent NN intervals that are greater than 50 milliseconds (pNN50), and frequency-domain variables such as very low frequency, low (LF) and high frequency (HF) of the power and LF/HF ratio. Unpaired t-test was used to find out differences among groups while paired t-test was used for comparison of each group for pre- and postjogging HRV. Pearson correlations were carried out to find out the relationships between the parameters. Blood pressures were not different between handball players and sedentary controls but exercise increased systolic blood pressure (Phandball players (Phandball players (Phandball players in response to a mild, short-time (5 min) jogging exercise. However, in sedentary subjects, either the sympathetic regulation of the autonomous nervous system increased or vagal withdrawal occurred.

Basic principles of the ECG. The normal ECG

African Journals Online (AJOL)

Angel_D

Southern Sudan Medical Journal vol 3. no 2. 26. How to read an ... Reduce some of the anxiety juniors often experience when faced with an ECG. ... This overall direction of travel of the electrical .... Anne Lancey, Education Centre, St Mary's Hospital, Isle of Wight, UK. .... 'method' section explains how the literature search.

Are ECG abnormalities in Noonan syndrome characteristic for the syndrome?

Science.gov (United States)

Raaijmakers, R; Noordam, C; Noonan, J A; Croonen, E A; van der Burgt, C J A M; Draaisma, J M T

2008-12-01

Of all patients with Noonan syndrome, 50-90% have one or more congenital heart defects. The most frequent occurring are pulmonary stenosis (PS) and hypertrophic cardiomyopathy. The electrocardiogram (ECG) of a patient with Noonan syndrome often shows a characteristic pattern, with a left axis deviation, abnormal R/S ratio over the left precordium, and an abnormal Q wave. The objective of this study was to determine if these ECG characteristics are an independent feature of the Noonan syndrome or if they are related to the congenital heart defect. A cohort study was performed with 118 patients from two university hospitals in the United States and in The Netherlands. All patients were diagnosed with definite Noonan syndrome and had had an ECG and echocardiography. Sixty-nine patients (58%) had characteristic abnormalities of the ECG. In the patient group without a cardiac defect (n = 21), ten patients had a characteristic ECG abnormality. There was no statistical relationship between the presence of a characteristic ECG abnormality and the presence of a cardiac defect (p = 0.33). Patients with hypertrophic cardiomyopathy had more ECG abnormalities in total (p = 0.05), without correlation with a specific ECG abnormality. We conclude that the ECG features in patients with Noonan syndrome are characteristic for the syndrome and are not related to a specific cardiac defect. An ECG is very useful in the diagnosis of Noonan syndrome; every child with a Noonan phenotype should have an ECG and echocardiogram for evaluation.

Freeware eLearning Flash-ECG for learning electrocardiography.

Science.gov (United States)

Romanov, Kalle; Kuusi, Timo

2009-06-01

Electrocardiographic (ECG) analysis can be taught in eLearning programmes with suitable software that permits the effective use of basic tools such as a ruler and a magnifier, required for measurements. The Flash-ECG (Research & Development Unit for Medical Education, University of Helsinki, Finland) was developed to enable teachers and students to use scanned and archived ECGs on computer screens and classroom projectors. The software requires only a standard web browser with a Flash plug-in and can be integrated with learning environments (Blackboard/WebCT, Moodle). The Flash-ECG is freeware and is available to medical teachers worldwide.

Efficient Skin Temperature Sensor and Stable Gel-Less Sticky ECG Sensor for a Wearable Flexible Healthcare Patch.

Science.gov (United States)

Yamamoto, Yuki; Yamamoto, Daisuke; Takada, Makoto; Naito, Hiroyoshi; Arie, Takayuki; Akita, Seiji; Takei, Kuniharu

2017-09-01

Wearable, flexible healthcare devices, which can monitor health data to predict and diagnose disease in advance, benefit society. Toward this future, various flexible and stretchable sensors as well as other components are demonstrated by arranging materials, structures, and processes. Although there are many sensor demonstrations, the fundamental characteristics such as the dependence of a temperature sensor on film thickness and the impact of adhesive for an electrocardiogram (ECG) sensor are yet to be explored in detail. In this study, the effect of film thickness for skin temperature measurements, adhesive force, and reliability of gel-less ECG sensors as well as an integrated real-time demonstration is reported. Depending on the ambient conditions, film thickness strongly affects the precision of skin temperature measurements, resulting in a thin flexible film suitable for a temperature sensor in wearable device applications. Furthermore, by arranging the material composition, stable gel-less sticky ECG electrodes are realized. Finally, real-time simultaneous skin temperature and ECG signal recordings are demonstrated by attaching an optimized device onto a volunteer's chest. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A cloud computing based 12-lead ECG telemedicine service

Science.gov (United States)

2012-01-01

Background Due to the great variability of 12-lead ECG instruments and medical specialists’ interpretation skills, it remains a challenge to deliver rapid and accurate 12-lead ECG reports with senior cardiologists’ decision making support in emergency telecardiology. Methods We create a new cloud and pervasive computing based 12-lead Electrocardiography (ECG) service to realize ubiquitous 12-lead ECG tele-diagnosis. Results This developed service enables ECG to be transmitted and interpreted via mobile phones. That is, tele-consultation can take place while the patient is on the ambulance, between the onsite clinicians and the off-site senior cardiologists, or among hospitals. Most importantly, this developed service is convenient, efficient, and inexpensive. Conclusions This cloud computing based ECG tele-consultation service expands the traditional 12-lead ECG applications onto the collaboration of clinicians at different locations or among hospitals. In short, this service can greatly improve medical service quality and efficiency, especially for patients in rural areas. This service has been evaluated and proved to be useful by cardiologists in Taiwan. PMID:22838382

A cloud computing based 12-lead ECG telemedicine service

Directory of Open Access Journals (Sweden)

Hsieh Jui-chien

2012-07-01

Full Text Available Abstract Background Due to the great variability of 12-lead ECG instruments and medical specialists’ interpretation skills, it remains a challenge to deliver rapid and accurate 12-lead ECG reports with senior cardiologists’ decision making support in emergency telecardiology. Methods We create a new cloud and pervasive computing based 12-lead Electrocardiography (ECG service to realize ubiquitous 12-lead ECG tele-diagnosis. Results This developed service enables ECG to be transmitted and interpreted via mobile phones. That is, tele-consultation can take place while the patient is on the ambulance, between the onsite clinicians and the off-site senior cardiologists, or among hospitals. Most importantly, this developed service is convenient, efficient, and inexpensive. Conclusions This cloud computing based ECG tele-consultation service expands the traditional 12-lead ECG applications onto the collaboration of clinicians at different locations or among hospitals. In short, this service can greatly improve medical service quality and efficiency, especially for patients in rural areas. This service has been evaluated and proved to be useful by cardiologists in Taiwan.

Cardiovascular screening in adolescents and young adults: a prospective study comparing the Pre-participation Physical Evaluation Monograph 4th Edition and ECG.

Science.gov (United States)

Fudge, Jessie; Harmon, Kimberly G; Owens, David S; Prutkin, Jordan M; Salerno, Jack C; Asif, Irfan M; Haruta, Alison; Pelto, Hank; Rao, Ashwin L; Toresdahl, Brett G; Drezner, Jonathan A

2014-08-01

This study compares the accuracy of cardiovascular screening in active adolescents and young adults using a standardised history, physical examination and resting 12-lead ECG. Participants were prospectively screened using a standardised questionnaire based on the Pre-participation Physical Evaluation Monograph 4th Edition (PPE-4), physical examination and ECG interpreted using modern standards. Participants with abnormal findings had focused echocardiography and further evaluation. Primary outcomes included disorders associated with sudden cardiac arrest (SCA). From September 2010 to July 2011, 1339 participants underwent screening: age 13-24 (mean 16) years, 49% male, 68% Caucasian, 17% African-American and 1071 (80%) participating in organised sports. Abnormal history responses were reported on 916 (68%) questionnaires. After physician review, 495/916 (54%) participants with positive questionnaires were thought to have non-cardiac symptoms and/or a benign family history and did not warrant additional evaluation. Physical examination was abnormal in 124 (9.3%) participants, and 72 (5.4%) had ECG abnormalities. Echocardiograms were performed in 586 (44%) participants for abnormal history (31%), physical examination (8%) or ECG (5%). Five participants (0.4%) were identified with a disorder associated with SCA, all with ECG-detected Wolff-Parkinson-White. The false-positive rates for history, physical examination and ECG were 31.3%, 9.3% and 5%, respectively. A standardised history and physical examination using the PPE-4 yields a high false-positive rate in a young active population with limited sensitivity to identify those at risk for SCA. ECG screening has a low false-positive rate using modern interpretation standards and improves detection of primary electrical disease at risk of SCA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Noise-assisted data processing with empirical mode decomposition in biomedical signals.

Science.gov (United States)

Karagiannis, Alexandros; Constantinou, Philip

2011-01-01

In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures. Simulation campaign results reveal that a decrease of processing time is accomplished with the introduction of preprocessing stage, prior to the application of EMD in biomedical time series. Furthermore, the variation in the number of IMFs according to the type of the preprocessing stage is studied as a function of SNR and time-series length. The application of the methodology in MIT-BIH ECG records is also presented in order to verify the findings in real ECG signals.

Methods for Improving the Diagnosis of a Brugada ECG Pattern.

Science.gov (United States)

Gottschalk, Byron H; Garcia-Niebla, Javier; Anselm, Daniel D; Glover, Benedict; Baranchuk, Adrian

2016-03-01

Brugada syndrome (BrS) is an inherited channelopathy that predisposes individuals to malignant arrhythmias and can lead to sudden cardiac death. The condition is characterized by two electrocardiography (ECG) patterns: the type-1 or "coved" ECG and the type-2 or "saddleback" ECG. Although the type-1 Brugada ECG pattern is diagnostic for the condition, the type-2 Brugada ECG pattern requires differential diagnosis from conditions that produce a similar morphology. In this article, we present a case that is suspicious but not diagnostic for BrS and discuss the application of ECG methodologies for increasing or decreasing suspicion for a diagnosis of BrS. © 2015 Wiley Periodicals, Inc.

Serial thallium-201 imaging at rest in patients with unstable and stable angina pectoris: relationship of myocardial perfusion at rest to presenting clinical syndrome

International Nuclear Information System (INIS)

Brown, K.A.; Okada, R.D.; Boucher, C.A.; Phillips, H.R.; Strauss, H.W.; Pohost, G.M.

1983-01-01

In order to determine whether there are differences in myocardial perfusion at rest among patients with various unstable and stable angina syndromes, serial thallium-201 imaging was performed at rest in 19 patients presenting with rapidly worsening exertional angina (unstable angina, group A), 12 patients with rest angina alone without exertional symptoms (unstable angina, group B), and 34 patients with chronic stable angina. No patient had an episode of angina within 4 hours of study. Nineteen of 19 (100%) patients in group A demonstrated transient defects compared to only 3 of 12 (25%) patients in group B (p less than 0.0001) and 4 of 34 (12%) stable angina patients (p less than 0.0001). The majority of zones demonstrating transient defects in group A were associated with hypokinesis of the corresponding left ventriculogram segment without associated ECG evidence of previous infarction. There were no significant differences in the frequency of persistent thallium defects, severity of angiographic coronary artery disease, or frequency of regional wall motion abnormalities of myocardial segments supplied by stenotic coronary arteries among the three groups of patients. Transient defects have been shown to reflect reduction in regional coronary blood flow to viable myocardium. Therefore, we conclude that regional resting hypoperfusion of viable myocardium is far more common in patients with exertional unstable angina symptoms than in patients with rest angina alone or chronic stable angina

The value of radionuclide phase analysis and parameters of cardial function for diagnosis CAD at rest and during exercise

International Nuclear Information System (INIS)

Huang Gang

1990-01-01

27 patients and 5 normal were studied with ECG-gated cardial blood pool images and radionuclide phase analysis at rest and during exercise. The results showed that the sensitivity of LVEF in CAD at rest and during exercise were 57% and 71% respectively, and the sensitivity of the ventricular phase in CAD were 79% at rest and 90% during exercise, and the sensitivity of phase angle in CAD were higher than of LVEF. This suggested that the ventricular phase angle was important for diagnosing early CAD. In addition, regional EF, phase image and ventricular wall motion were useful to detect the lesion of ischemia in CAD

Usefulness of ST elevation score by using vector-projected virtual 187-channel ECG for risk stratification in patients with Brugada-type ECG pattern

Directory of Open Access Journals (Sweden)

Shoko Ishikawa

2012-08-01

Conclusion: The ST elevation score in VP-ECG objectively documented the degree of ST elevation in surface ECG in Brugada-type ECG patterns. The ST-elevation score might be useful for risk stratification in patients with asymptomatic Brugada syndrome.

[Biometric identification method for ECG based on the piecewise linear representation (PLR) and dynamic time warping (DTW)].

Science.gov (United States)

Yang, Licai; Shen, Jun; Bao, Shudi; Wei, Shoushui

2013-10-01

To treat the problem of identification performance and the complexity of the algorithm, we proposed a piecewise linear representation and dynamic time warping (PLR-DTW) method for ECG biometric identification. Firstly we detected R peaks to get the heartbeats after denoising preprocessing. Then we used the PLR method to keep important information of an ECG signal segment while reducing the data dimension at the same time. The improved DTW method was used for similarity measurements between the test data and the templates. The performance evaluation was carried out on the two ECG databases: PTB and MIT-BIH. The analystic results showed that compared to the discrete wavelet transform method, the proposed PLR-DTW method achieved a higher accuracy rate which is nearly 8% of rising, and saved about 30% operation time, and this demonstrated that the proposed method could provide a better performance.

The application of root mean square electrocardiography (RMS ECG) for the detection of acquired and congenital long QT syndrome.

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Lux, Robert L; Sower, Christopher Todd; Allen, Nancy; Etheridge, Susan P; Tristani-Firouzi, Martin; Saarel, Elizabeth V

2014-01-01

Precise measurement of the QT interval is often hampered by difficulty determining the end of the low amplitude T wave. Root mean square electrocardiography (RMS ECG) provides a novel alternative measure of ventricular repolarization. Experimental data have shown that the interval between the RMS ECG QRS and T wave peaks (RTPK) closely reflects the mean ventricular action potential duration while the RMS T wave width (TW) tracks the dispersion of repolarization timing. Here, we tested the precision of RMS ECG to assess ventricular repolarization in humans in the setting of drug-induced and congenital Long QT Syndrome (LQTS). RMS ECG signals were derived from high-resolution 24 hour Holter monitor recordings from 68 subjects after receiving placebo and moxifloxacin and from standard 12 lead ECGs obtained in 97 subjects with LQTS and 97 age- and sex-matched controls. RTPK, QTRMS and RMS TW intervals were automatically measured using custom software and compared to traditional QT measures using lead II. All measures of repolarization were prolonged during moxifloxacin administration and in LQTS subjects, but the variance of RMS intervals was significantly smaller than traditional lead II measurements. TW was prolonged during moxifloxacin and in subjects with LQT-2, but not LQT-1 or LQT-3. These data validate the application of RMS ECG for the detection of drug-induced and congenital LQTS. RMS ECG measurements are more precise than the current standard of care lead II measurements.

High spatial correspondence at a columnar level between activation and resting state fMRI signals and local field potentials.

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Shi, Zhaoyue; Wu, Ruiqi; Yang, Pai-Feng; Wang, Feng; Wu, Tung-Lin; Mishra, Arabinda; Chen, Li Min; Gore, John C

2017-05-16

Although blood oxygenation level-dependent (BOLD) fMRI has been widely used to map brain responses to external stimuli and to delineate functional circuits at rest, the extent to which BOLD signals correlate spatially with underlying neuronal activity, the spatial relationships between stimulus-evoked BOLD activations and local correlations of BOLD signals in a resting state, and whether these spatial relationships vary across functionally distinct cortical areas are not known. To address these critical questions, we directly compared the spatial extents of stimulated activations and the local profiles of intervoxel resting state correlations for both high-resolution BOLD at 9.4 T and local field potentials (LFPs), using 98-channel microelectrode arrays, in functionally distinct primary somatosensory areas 3b and 1 in nonhuman primates. Anatomic images of LFP and BOLD were coregistered within 0.10 mm accuracy. We found that the point spread functions (PSFs) of BOLD and LFP responses were comparable in the stimulus condition, and both estimates of activations were slightly more spatially constrained than local correlations at rest. The magnitudes of stimulus responses in area 3b were stronger than those in area 1 and extended in a medial to lateral direction. In addition, the reproducibility and stability of stimulus-evoked activation locations within and across both modalities were robust. Our work suggests that the intrinsic resolution of BOLD is not a limiting feature in practice and approaches the intrinsic precision achievable by multielectrode electrophysiology.

Hyperkalemia on ECG

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Bryson Hicks

2016-09-01

Full Text Available History of present illness: A 34-year-old diabetic female presented to the emergency department with chest pain status-post AICD firing. She described the pain as a “12 out of 10” which woke her from sleep at 0200, one hour prior to arrival. Vitals were unremarkable. She had no known history of renal failure. Due to frequent ED visits for chronic pain, patient had difficult vascular access and nursing was initially unable to obtain IV access. An abnormal rhythm was noted on the cardiac monitor, and ECG was ordered. Significant findings: Initial ECG shows tall, peaked T waves, most prominently in V3 and V4, as well as QRS widening. These findings are consistent with hyperkalemia, which was promptly treated. Follow-up ECG post-treatment shows narrowing of the QRS complexes and normalization of peaked T waves. Discussion: The etiology of hyperkalemia may be due to an acute insult such as crush injury, drug side effect, or in acute renal failure, but may also occur in the setting of a chronic insult such as chronic kidney disease.1 As potassium rises, several abnormalities can be identified on ECG. Initially the T waves become peaked and the QRS complexes widen.2,3 This can devolve into a wide complex rhythm, ventricular tachycardia, ventricular fibrillation, or asystole. Patients may also experience systemic symptoms such as weakness or paralysis.1 In this particular case, labs showed a potassium of 7.6-mmol/L after initial treatment (see repeat EKG. While the incidence of hyperkalemia in the general population is not defined, the incidence in hospitalized patients is 1.3-10%.4-8 Impaired kidney function is the most common risk factor found in 33-83% of affected patients.4,5,8,9 Treatment for hyperkalemia generally includes IV insulin and IV dextrose and nebulized albuterol for intracellular shift of potassium, IV furosemide and IV fluids for dilution and renal excretion of furosemide, and IV calcium for stabilization of cardiac membranes.2,3

Ability of a 5-minute electrocardiography (ECG) for predicting arrhythmias in Doberman Pinschers with cardiomyopathy in comparison with a 24-hour ambulatory ECG.

Science.gov (United States)

Wess, G; Schulze, A; Geraghty, N; Hartmann, K

2010-01-01

Ventricular premature contractions (VPCs) are common in the occult stage of cardiomyopathy in Doberman Pinschers. Although the gold standard for detecting arrhythmia is the 24-hour ambulatory electrocardiography (ECG) (Holter), this method is more expensive, time-consuming and often not as readily available as common ECG. Comparison of 5-minute ECGs with Holter examinations. Eight hundred and seventy-five 5-minute ECGs and Holter examinations of 431 Doberman Pinschers. Each examination included a 5-minute ECG and Holter examination. A cut-off value of > 100 VPCs/24 hours using Holter was considered diagnostic for the presence of cardiomyopathy. Statistical evaluation included calculation of sensitivity, specificity, positive predictive value, and negative predictive value. Holter examinations revealed > 100 VPCs/24 hours in 204/875 examinations. At least 1 VPC during a 5-minute ECG was detected in 131 (64.2%) of these 204 examinations. No VPCs were found in the 5-minute ECG in 73 (35.8%) examinations of affected Doberman Pinschers. A 5-minute ECG with at least 1 VPC as cut-off had a sensitivity of 64.2%, a specificity of 96.7%, a positive predictive value of 85.6% and a negative predictive value of 89.9% for the presence of > 100 VPCs/24 hours. A 5-minute ECG is a rather insensitive method for detecting arrhythmias in Doberman Pinschers. However, the occurrence of at least 1 VPC in 5 minutes strongly warrants further examination of the dog, because specificity (96.7%) and positive predictive value (85.6%) are high and could suggest occult cardiomyopathy.

[ECG for non-competitive sports in childhood: strengths and disputes].

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Poggi, Elena; Giannattasio, Alessandro; Bolloli, Sara; Beccaria, Andrea; Mezzano, Paola; Rocca, Paola; Del Vecchio, Cecilia

2016-11-01

Sport is very important for health promotion and conservation. Active lifestyle and regular exercise reduce cardiovascular disease incidence. The Italian Ministry of Health issued the Law Decree no. 243 (10/18/2014) concerning "guidelines for certification about non-competitive sports" to promote safety in sports. This regulation defines the activities for which a certificate is required, the professional actors involved and the clinical exams to be performed according to the patient's health status. In particular, the Law Decree recommends to perform an electrocardiogram (ECG) "at least once in a lifetime", introducing much greater news into pediatric practice. We proposed a survey evaluating frequency of ECG implementation for non-competitive sports and cardiovascular diseases incidence was administered to 7 Ligurian pediatricians. The number of ECG/year for pediatrician increased from 10 ECG/year to 50 ECG/year with an indication of suitability to non-competitive sports. One case of QT prolongation and 2 cases of type 1 Brugada ECG pattern were diagnosed. In addition, 3 patients had an atrial septal defect and 3 children had a ventricular septal defect. Forty-three percent of the pediatricians considered useful performing the ECG. ECG in children has enhanced the positive effects on the community health. However, it remains to be defined in agreement with scientific societies the age at which to perform ECG, the sports for which ECG is required and the cost-benefit ratio for the National Health System and families.

Female False Positive Exercise Stress ECG Testing - Fact Verses Fiction.

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Fitzgerald, Benjamin T; Scalia, William M; Scalia, Gregory M

2018-03-07

Exercise stress testing is a well validated cardiovascular investigation. Accuracy for treadmill stress electrocardiograph (ECG) testing has been documented at 60%. False positive stress ECGs (exercise ECG changes with non-obstructive disease on anatomical testing) are common, especially in women, limiting the effectiveness of the test. This study investigates the incidence and predictors of false positive stress ECG findings, referenced against stress echocardiography (SE) as a standard. Stress echocardiography was performed using the Bruce treadmill protocol. False positive stress ECG tests were defined as greater than 1mm of ST depression on ECG during exertion, without pain, with a normal SE. Potential causes for false positive tests were recorded before the test. Three thousand consecutive negative stress echocardiograms (1036 females, 34.5%) were analysed (age 59+/-14 years. False positive (F+) stress ECGs were documented in 565/3000 tests (18.8%). F+ stress ECGs were equally prevalent in females (194/1036, 18.7%) and males (371/1964, 18.9%, p=0.85 for the difference). Potential causes (hypertension, left ventricular hypertrophy, known coronary disease, arrhythmia, diabetes mellitus, valvular heart disease) were recorded in 36/194 (18.6%) of the female F+ ECG tests and 249/371 (68.2%) of the male F+ ECG tests (preinforce the value of stress imaging, particularly in women. Copyright © 2018 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). All rights reserved.

ECG abnormalities in patients with chronic kidney disease

International Nuclear Information System (INIS)

Shafi, S.; Saleem, M.; Anjum, R.; Abdullah, W.; Shafi, T.

2017-01-01

Chronic kidney disease (CKD) is associated with increased risk of cardiovascular disease. Electrocardiographic (ECG) abnormalities are common in CKD patients. However, there is variation in literature regarding frequency of ECG abnormalities in CKD patients and limited information in local population. Methods: The study design was cross-sectional in nature. All patients between ages of 20-80 years with CKD not previously on renal replacement therapy who were admitted to nephrology ward at a tertiary care facility over a 6-month period were included. All patients underwent 12 lead electrocardiograms (ECG). ECG abnormalities were defined based on accepted standard criteria. Results: Total number of patients included in the study was 124. Mean age of all patients was 49.9+-13.8 years, 106 (84.8%) had hypertension, 84 (70%) had diabetes mellitus, and 35 (29.9%) had known cardiovascular disease. Mean serum creatinine was 7.2+-3.4 mg/dl, mean eGFR was 10.6+-9.2 ml/min/1.73 m/sup 2/. Overall 78.4% of all CKD patients have one or more ECG abnormality. Left ventricular hypertrophy (40%), Q waves (27.2%), ST segment elevation or depression (23.4%), prolonged QRS duration (19.2%), tachycardia (17.6%) and left and right atrial enlargement (17.6%) were the most common abnormalities. Conclusion: ECG abnormalities are common in hospitalized CKD patients in local population. All hospitalized CKD patients should undergo ECG to screen for cardiovascular disease. (author)

Effect of Head-Down Bed Rest and Artificial Gravity Countermeasure on Cardiac Autonomic and Advanced Electrocardiographic Function

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Schlegel, T. T.; Platts, S.; Stenger, M.; Ribeiro, C.; Natapoff, A.; Howarth, M.; Evans, J.

2007-01-01

To study the effects of 21 days of head-down bed rest (HDBR), with versus without an artificial gravity (AG) countermeasure, on cardiac autonomic and advanced electrocardiographic function. Fourteen healthy men participated in the study: seven experienced 21 days of HDBR alone ("HDBR controls") and seven the same degree and duration of HDBR but with approximately 1hr daily short-arm centrifugation as an AG countermeasure ("AG-treated"). Five minute supine high-fidelity 12-lead ECGs were obtained in all subjects: 1) 4 days before HDBR; 2) on the last day of HDBR; and 3) 7 days after HDBR. Besides conventional 12-lead ECG intervals and voltages, all of the following advanced ECG parameters were studied: 1) both stochastic (time and frequency domain) and deterministic heart rate variability (HRV); 2) beat-to-beat QT interval variability (QTV); 3) T-wave morphology, including signal-averaged T-wave residua (TWR) and principal component analysis ratios; 4) other SAECG-related parameters including high frequency QRS ECG and late potentials; and 5) several advanced ECG estimates of left ventricular (LV) mass. The most important results by repeated measures ANOVA were that: 1) Heart rates, Bazett-corrected QTc intervals, TWR, LF/HF power and the alpha 1 of HRV were significantly increased in both groups (i.e., by HDBR), but with no relevant HDBR*group differences; 2) All purely "vagally-mediated" parameters of HRV (e.g., RMSSD, HF power, Poincare SD1, etc.), PR intervals, and also several parameters of LV mass (Cornell and Sokolow-Lyon voltages, spatial ventricular activation times, ventricular gradients) were all significantly decreased in both groups (i.e., by HDBR), but again with no relevant HDBR*group differences); 3) All "generalized" or "vagal plus sympathetic" parameters of stochastic HRV (i.e., SDNN, total power, LF power) were significantly more decreased in the AG-treated group than in the HDBR-only group (i.e., here there was a relevant HDBR*group difference

A Study on the Optimal Positions of ECG Electrodes in a Garment for the Design of ECG-Monitoring Clothing for Male.

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