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Sample records for ballistocardiography

  1. J peak extraction from non-standard ballistocardiography data: a preliminary study.

    Science.gov (United States)

    Xin Li; Ye Li

    2016-08-01

    In recent years, several advanced algorithms based on clustering, multi-method or data fusion approaches have been proposed to estimate heartbeat intervals from non-standard ballistocardiography (BCG) data. These advanced algorithms generally have higher computational complexity than J-peak based algorithms. This fact motivated us to study the problem of extracting J peaks from non-standard BCG data, because if this extraction can be realized, then a low-complexity J-peak based algorithm can be used to fast estimate heartbeat intervals from non-standard BCG data. We found that most of the energy in J peaks is contained in a relatively narrow frequency band, called J-peak band, and that the heartbeat harmonics outside the J-peak band can cause the non-standard BCG waveform. According to these findings, a FIR linear phase filter with the J-peak band as its pass-band is proposed. The experimental result demonstrates the ability of the proposed filter to extract J peaks from non-standard BCG data.

  2. Applying Novel Time-Frequency Moments Singular Value Decomposition Method and Artificial Neural Networks for Ballistocardiography

    Directory of Open Access Journals (Sweden)

    Koivistoinen Teemu

    2007-01-01

    Full Text Available As we know, singular value decomposition (SVD is designed for computing singular values (SVs of a matrix. Then, if it is used for finding SVs of an -by-1 or 1-by- array with elements representing samples of a signal, it will return only one singular value that is not enough to express the whole signal. To overcome this problem, we designed a new kind of the feature extraction method which we call ''time-frequency moments singular value decomposition (TFM-SVD.'' In this new method, we use statistical features of time series as well as frequency series (Fourier transform of the signal. This information is then extracted into a certain matrix with a fixed structure and the SVs of that matrix are sought. This transform can be used as a preprocessing stage in pattern clustering methods. The results in using it indicate that the performance of a combined system including this transform and classifiers is comparable with the performance of using other feature extraction methods such as wavelet transforms. To evaluate TFM-SVD, we applied this new method and artificial neural networks (ANNs for ballistocardiogram (BCG data clustering to look for probable heart disease of six test subjects. BCG from the test subjects was recorded using a chair-like ballistocardiograph, developed in our project. This kind of device combined with automated recording and analysis would be suitable for use in many places, such as home, office, and so forth. The results show that the method has high performance and it is almost insensitive to BCG waveform latency or nonlinear disturbance.

  3. Applying Novel Time-Frequency Moments Singular Value Decomposition Method and Artificial Neural Networks for Ballistocardiography

    Directory of Open Access Journals (Sweden)

    Alpo Värri

    2007-01-01

    Full Text Available As we know, singular value decomposition (SVD is designed for computing singular values (SVs of a matrix. Then, if it is used for finding SVs of an m-by-1 or 1-by-m array with elements representing samples of a signal, it will return only one singular value that is not enough to express the whole signal. To overcome this problem, we designed a new kind of the feature extraction method which we call ‘‘time-frequency moments singular value decomposition (TFM-SVD.’’ In this new method, we use statistical features of time series as well as frequency series (Fourier transform of the signal. This information is then extracted into a certain matrix with a fixed structure and the SVs of that matrix are sought. This transform can be used as a preprocessing stage in pattern clustering methods. The results in using it indicate that the performance of a combined system including this transform and classifiers is comparable with the performance of using other feature extraction methods such as wavelet transforms. To evaluate TFM-SVD, we applied this new method and artificial neural networks (ANNs for ballistocardiogram (BCG data clustering to look for probable heart disease of six test subjects. BCG from the test subjects was recorded using a chair-like ballistocardiograph, developed in our project. This kind of device combined with automated recording and analysis would be suitable for use in many places, such as home, office, and so forth. The results show that the method has high performance and it is almost insensitive to BCG waveform latency or nonlinear disturbance.

  4. Applying Novel Time-Frequency Moments Singular Value Decomposition Method and Artificial Neural Networks for Ballistocardiography

    Science.gov (United States)

    Akhbardeh, Alireza; Junnila, Sakari; Koivuluoma, Mikko; Koivistoinen, Teemu; Värri, Alpo

    2006-12-01

    As we know, singular value decomposition (SVD) is designed for computing singular values (SVs) of a matrix. Then, if it is used for finding SVs of an [InlineEquation not available: see fulltext.]-by-1 or 1-by- [InlineEquation not available: see fulltext.] array with elements representing samples of a signal, it will return only one singular value that is not enough to express the whole signal. To overcome this problem, we designed a new kind of the feature extraction method which we call ''time-frequency moments singular value decomposition (TFM-SVD).'' In this new method, we use statistical features of time series as well as frequency series (Fourier transform of the signal). This information is then extracted into a certain matrix with a fixed structure and the SVs of that matrix are sought. This transform can be used as a preprocessing stage in pattern clustering methods. The results in using it indicate that the performance of a combined system including this transform and classifiers is comparable with the performance of using other feature extraction methods such as wavelet transforms. To evaluate TFM-SVD, we applied this new method and artificial neural networks (ANNs) for ballistocardiogram (BCG) data clustering to look for probable heart disease of six test subjects. BCG from the test subjects was recorded using a chair-like ballistocardiograph, developed in our project. This kind of device combined with automated recording and analysis would be suitable for use in many places, such as home, office, and so forth. The results show that the method has high performance and it is almost insensitive to BCG waveform latency or nonlinear disturbance.

  5. Multi-Channel Optical Sensor-Array for Measuring Ballistocardiograms and Respiratory Activity in Bed

    NARCIS (Netherlands)

    Brueser, C.; Winter, S.; Leonhardt, S.

    2013-01-01

    Recent research on ballistocardiography (BCG) or seismocardiography(SCG) has focused on two major application areas for these technologies: non-invasive diagnostics of hemodynamic parameters and unobtrusive, long-term monitoring of cardiac (and respiratory) rhythms. Forthe former application, an ele

  6. A simple ballistocardiographic system for a medical cardiovascular physiology course.

    Science.gov (United States)

    Eblen-Zajjur, Antonio

    2003-12-01

    Ballistocardiography is an old, noninvasive technique used to record the movements of the body synchronous with the heartbeat due to left ventricular pump activity. Despite the fact that this technique to measure cardiac output has been superseded by more advanced and precise techniques, it is useful for teaching cardiac cycle physiology in an undergraduate practical course because of its noninvasive application in humans, clear physiological and physiopathological analysis, and practical approach to considering cardiac output issues. In the present report, a simple, low cost, easy-to-build ballistocardiography system is implemented together with a theoretical and practical session that includes Newton's laws, cardiac output, cardiac pump activity, anatomy and physiology of the vessel circulation, vectorial composition, and signal transduction, which makes cardiovascular physiology easy to understand and focuses on the study of cardiac output otherwise seen only with the help of computer simulation or echocardiography. The proposed system is able to record body displacement or force as ballistocardiography traces and its changes caused by different physiological factors. The ballistocardiography session was included in our medical physiology course six years ago with very high acceptance and approval rates from the students.

  7. Multi-Channel Optical Sensor-Array for Measuring Ballistocardiograms and Respiratory Activity in Bed

    OpenAIRE

    Brueser, C.; Winter, S; Leonhardt, S.

    2013-01-01

    Recent research on ballistocardiography (BCG) or seismocardiography(SCG) has focused on two major application areas for these technologies: non-invasive diagnostics of hemodynamic parameters and unobtrusive, long-term monitoring of cardiac (and respiratory) rhythms. Forthe former application, an electrocardiogram (ECG) is usually recorded simultaneously to delineate individual heart beats in the cardiacvibration signals and to derive the relevant hemodynamic parameters. Our work, however, cov...

  8. Multi-channel optical sensor-array for measuring ballistocardiograms and respiratory activity in bed.

    Science.gov (United States)

    Brüser, Christoph; Kerekes, Anna; Winter, Stefan; Leonhardt, Steffen

    2012-01-01

    Our work covers improvements in sensors and signal processing for unobtrusive, long-term monitoring of cardiac (and respiratory) rhythms using only non-invasive vibration sensors. We describe a system for the unobtrusive monitoring of vital signs by means of an array of novel optical ballistocardiography (BCG) sensors placed underneath a regular bed mattress. Furthermore, we analyze the systems spatial sensitivity and present proof-of-concept results comparing our system to a more conventional BCG system based on a single electromechanical-film (EMFi) sensor. Our preliminary results suggest that the proposed optical multi-channel system could have the potential to reduce beat-to-beat heart rate estimation errors, as well as enable the analysis of more complex breathing patterns.

  9. Detecting Aortic Valve Opening and Closing from Distal Body Vibrations

    CERN Document Server

    Wiens, Andrew D; Inan, Omer T

    2016-01-01

    Objective: Proximal and whole-body vibrations are well studied in seismocardiography and ballistocardiography, yet distal vibrations are still poorly understood. In this paper we develop two methods to measure aortic valve opening (AVO) and closing (AVC) from distal vibrations. Methods: AVO and AVC were detected for each heartbeat with accelerometers on the upper arm (A), wrist (W), and knee (K) of 22 consenting adults following isometric exercise. Exercise-induced changes were recorded with impedance cardiography, and nine-beat ensemble averaging was applied. Our first method, FilterBCG, detects peaks in distal vibrations after filtering with individually-tuned bandpass filters while RidgeBCG uses ridge regression to estimate AVO and AVC without peaks. Pseudocode is provided. Results: In agreement with recent studies, we did not find peaks at AVO and AVC in distal vibrations, and the conventional R-J interval method from the literature also correlated poorly with AVO (r2 = 0.22 A, 0.14 W, 0.12 K). Interestin...

  10. Heartbeat Cycle Length Detection by a Ballistocardiographic Sensor in Atrial Fibrillation and Sinus Rhythm

    Directory of Open Access Journals (Sweden)

    Matthias Daniel Zink

    2015-01-01

    Full Text Available Background. Heart rate monitoring is especially interesting in patients with atrial fibrillation (AF and is routinely performed by ECG. A ballistocardiography (BCG foil is an unobtrusive sensor for mechanical vibrations. We tested the correlation of heartbeat cycle length detection by a novel algorithm for a BCG foil to an ECG in AF and sinus rhythm (SR. Methods. In 22 patients we obtained BCG and synchronized ECG recordings before and after cardioversion and examined the correlation between heartbeat characteristics. Results. We analyzed a total of 4317 heartbeats during AF and 2445 during SR with a correlation between ECG and BCG during AF of r=0.70 (95% CI 0.68–0.71, P<0.0001 and r=0.75 (95% CI 0.73–0.77, P<0.0001 during SR. By adding a quality index, artifacts could be reduced and the correlation increased for AF to 0.76 (95% CI 0.74–0.77, P<0.0001, n=3468 and for SR to 0.85 (95% CI 0.83–0.86, P<0.0001, n=2176. Conclusion. Heartbeat cycle length measurement by our novel algorithm for BCG foil is feasible during SR and AF, offering new possibilities of unobtrusive heart rate monitoring. This trial is registered with IRB registration number EK205/11. This trial is registered with clinical trials registration number NCT01779674.

  11. A novel system identification technique for improved wearable hemodynamics assessment.

    Science.gov (United States)

    Wiens, Andrew D; Inan, Omer T

    2015-05-01

    Recent advances have led to renewed interest in ballistocardiography (BCG), a noninvasive measure of the small movements of the body due to cardiovascular events. A broad range of platforms have been developed and verified for BCG measurement including beds, chairs, and weighing scales: while the body is coupled to such a platform, the cardiogenic movements are measured. Wearable BCG, measured with an accelerometer affixed to the body, may enable continuous, or more regular, monitoring during the day; however, the signals from such wearable BCGs represent local or distal accelerations of skin and tissue rather than the whole body. In this paper, we propose a novel method to reconstruct the BCG measured with a weighing scale (WS BCG) from a wearable sensor via a training step to remove these local effects. Preliminary validation of this method was performed with 15 subjects: the wearable sensor was placed at three locations on the surface of the body while WS BCG measurements were recorded simultaneously. A regularized system identification approach was used to reconstruct the WS BCG from the wearable BCG. Preliminary results suggest that the relationship between local and central disturbances is highly dependent on both the individual and the location where the accelerometer is placed on the body and that these differences can be resolved via calibration to accurately measure changes in cardiac output and contractility from a wearable sensor. Such measurements could be highly effective, for example, for improved monitoring of heart failure patients at home.

  12. The application of a piezo-resistive cardiorespiratory sensor system in an automobile safety belt.

    Science.gov (United States)

    Hamdani, Syed Talha Ali; Fernando, Anura

    2015-03-30

    Respiratory and heart failure are conditions that can occur with little warning and may also be difficult to predict. Therefore continuous monitoring of these bio-signals is advantageous for ensuring human health. The car safety belt is mainly designed to secure the occupants of the vehicle in the event of an accident. In the current research a prototype safety belt is developed, which is used to acquire respiratory and heart signals, under laboratory conditions. The current safety belt is constructed using a copper ink based nonwoven material, which works based on the piezo-resistive effect due to the pressure exerted on the sensor as a result of expansion of the thorax/abdomen area of the body for respiration and due to the principle of ballistocardiography (BCG) in heart signal sensing. In this research, the development of a theoretical model to qualitatively describe the piezo-resistive material is also presented in order to predict the relative change in the resistance of the piezo-resistive material due to the pressure applied.

  13. The Application of a Piezo-Resistive Cardiorespiratory Sensor System in an Automobile Safety Belt

    Directory of Open Access Journals (Sweden)

    Syed Talha Ali Hamdani

    2015-03-01

    Full Text Available Respiratory and heart failure are conditions that can occur with little warning and may also be difficult to predict. Therefore continuous monitoring of these bio-signals is advantageous for ensuring human health. The car safety belt is mainly designed to secure the occupants of the vehicle in the event of an accident. In the current research a prototype safety belt is developed, which is used to acquire respiratory and heart signals, under laboratory conditions. The current safety belt is constructed using a copper ink based nonwoven material, which works based on the piezo-resistive effect due to the pressure exerted on the sensor as a result of expansion of the thorax/abdomen area of the body for respiration and due to the principle of ballistocardiography (BCG in heart signal sensing. In this research, the development of a theoretical model to qualitatively describe the piezo-resistive material is also presented in order to predict the relative change in the resistance of the piezo-resistive material due to the pressure applied.

  14. Weighing Scale-Based Pulse Transit Time is a Superior Marker of Blood Pressure than Conventional Pulse Arrival Time

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    Martin, Stephanie L.-O.; Carek, Andrew M.; Kim, Chang-Sei; Ashouri, Hazar; Inan, Omer T.; Hahn, Jin-Oh; Mukkamala, Ramakrishna

    2016-12-01

    Pulse transit time (PTT) is being widely pursued for cuff-less blood pressure (BP) monitoring. Most efforts have employed the time delay between ECG and finger photoplethysmography (PPG) waveforms as a convenient surrogate of PTT. However, these conventional pulse arrival time (PAT) measurements include the pre-ejection period (PEP) and the time delay through small, muscular arteries and may thus be an unreliable marker of BP. We assessed a bathroom weighing scale-like system for convenient measurement of ballistocardiography and foot PPG waveforms – and thus PTT through larger, more elastic arteries – in terms of its ability to improve tracking of BP in individual subjects. We measured “scale PTT”, conventional PAT, and cuff BP in humans during interventions that increased BP but changed PEP and smooth muscle contraction differently. Scale PTT tracked the diastolic BP changes well, with correlation coefficient of ‑0.80 ± 0.02 (mean ± SE) and root-mean-squared-error of 7.6 ± 0.5 mmHg after a best-case calibration. Conventional PAT was significantly inferior in tracking these changes, with correlation coefficient of ‑0.60 ± 0.04 and root-mean-squared-error of 14.6 ± 1.5 mmHg (p < 0.05). Scale PTT also tracked the systolic BP changes better than conventional PAT but not to an acceptable level. With further development, scale PTT may permit reliable, convenient measurement of BP.