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Sample records for ballistocardiography

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Pulse and vital sign measurement in mixed reality using a HoloLens

    OpenAIRE

    Mcduff , Daniel; Hurter , Christophe; Gonzalez-Franco , Mar

    2017-01-01

    International audience; Cardiography, quantitative measurement of the functioning of the heart, traditionally requires customized obtrusive contact sensors. Using new methods photoplethysmography and ballistocardiography signals can be captured using ubiquitous sensors, such as webcams and accelerometers. However, these signals are not visible to the unaided eye. We present Cardiolens-a mixed reality system that enables real-time, hands-free measurement and visu-alization of blood ow and vita...

  6. Ambient and Unobtrusive Cardiorespiratory Monitoring Techniques.

    Science.gov (United States)

    Bruser, Christoph; Antink, Christoph Hoog; Wartzek, Tobias; Walter, Marian; Leonhardt, Steffen

    2015-01-01

    Monitoring vital signs through unobtrusive means is a goal which has attracted a lot of attention in the past decade. This review provides a systematic and comprehensive review over the current state of the field of ambient and unobtrusive cardiorespiratory monitoring. To this end, nine different sensing modalities which have been in the focus of current research activities are covered: capacitive electrocardiography, seismo- and ballistocardiography, reflective photoplethysmography (PPG) and PPG imaging, thermography, methods relying on laser or radar for distance-based measurements, video motion analysis, as well as methods using high-frequency electromagnetic fields. Current trends in these subfields are reviewed. Moreover, we systematically analyze similarities and differences between these methods with respect to the physiological and physical effects they sense as well as the resulting implications. Finally, future research trends for the field as a whole are identified.

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

    Science.gov (United States)

    Hamdani, Syed Talha Ali; Fernando, Anura

    2015-01-01

    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. PMID:25831088

  8. Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring

    Directory of Open Access Journals (Sweden)

    Christoph Hoog Antink

    2017-12-01

    Full Text Available Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNR S is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario.

  9. 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.

  10. Non-Invasive Detection of Respiration and Heart Rate with a Vehicle Seat Sensor.

    Science.gov (United States)

    Wusk, Grace; Gabler, Hampton

    2018-05-08

    This study demonstrates the feasibility of using a seat sensor designed for occupant classification from a production passenger vehicle to measure an occupant’s respiration rate (RR) and heart rate (HR) in a laboratory setting. Relaying occupant vital signs after a crash could improve emergency response by adding a direct measure of the occupant state to an Advanced Automatic Collision Notification (AACN) system. Data was collected from eleven participants with body weights ranging from 42 to 91 kg using a Ford Mustang passenger seat and seat sensor. Using a ballistocardiography (BCG) approach, the data was processed by time domain filtering and frequency domain analysis using the fast Fourier transform to yield RR and HR in a 1-min sliding window. Resting rates over the 30-min data collection and continuous RR and HR signals were compared to laboratory physiological instruments using the Bland-Altman approach. Differences between the seat sensor and reference sensor were within 5 breaths per minute for resting RR and within 15 beats per minute for resting HR. The time series comparisons for RR and HR were promising with the frequency analysis technique outperforming the peak detection technique. However, future work is necessary for more accurate and reliable real-time monitoring of RR and HR outside the laboratory setting.

  11. Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring

    Science.gov (United States)

    Hoog Antink, Christoph; Schulz, Florian; Walter, Marian

    2017-01-01

    Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNRS is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario. PMID:29295594

  12. A NOVEL BCG SENSOR-ARRAY FOR UNOBTRUSIVE CARDIAC MONITORING

    Directory of Open Access Journals (Sweden)

    Anna Böhm

    2013-12-01

    Full Text Available Unobtrusive heart rate monitoring is a popular research topic in biomedical engineering. The reason is that convential methods, e.g. the clinical gold standard electrocardiography, require conductive contact to the human body. Other methods such as ballistocardiography try to record these vital signs without electrodes that are attached to the body. So far, these systems cannot replace routine procedures. Most systems have some drawbacks that cannot be compensated, such as aging of the sensor materials or movement artifacts. In addition, the signal form differs greatly from an ECG, which is an electrical signal. The ballistocardiogram has a mechanical source, which makes it harder to evaluate. We have developed a new sensor array made of near-IR-LEDs to record BCGs. IR-sensors do not age in relevant time scales. Analog filtering was neccesary, because the signal amplitude was very small. The digitized data was then processed by various algorithms to extract beat-to-beat or breath-to-breath intervals. The redundancy of multiple BCG channels was used to provide a robust estimation of beat-to-beat intervals and heart rate. We installed the system beneath a mattress topper of a hospital bed, but any other bed would have been sufficient. The validation of this measurement system shows that it is well suited for BCG recordings. The use of multiple channels has proven to be superior to relying on a single BCG channel.

  13. Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring.

    Science.gov (United States)

    Hoog Antink, Christoph; Schulz, Florian; Leonhardt, Steffen; Walter, Marian

    2017-12-25

    Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNR S is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario.

  14. A low-noise ac-bridge amplifier for ballistocardiogram measurement on an electronic weighing scale

    International Nuclear Information System (INIS)

    Inan, O T; Kovacs, G T A

    2010-01-01

    Ballistocardiography is a non-invasive technique for evaluating cardiovascular health. This note presents an ac-bridge amplifier for low-noise ballistocardiogram (BCG) recording from a modified weighing scale. The strain gauges in a commercial scale were excited by an ac source—square or sine wave—and the differential output voltage resulting from the BCG was amplified and demodulated synchronously with the excitation waveform. A standard BCG amplifier, with a simple dc-bridge excitation, was also built and the performance was compared to both the square- and sine-wave excited ac-bridge amplifiers. The total input-referred voltage noise (rms) integrated over the relevant BCG bandwidth of 0.3–10 Hz was found to be 30 nV (square wave source) or 25 nV (sine-wave source) for the ac-bridge amplifier and 52 nV for the standard amplifier: an improvement of 4.8 dB or 6 dB, respectively. These correspond to input-referred force noise (rms) values of 5 mN, 4 mN and 8.3 mN. The improvement in SNR was also observed in recorded waveforms from a seated subject whose BCG signal was measured with both dc- and ac-bridge circuits. (note)

  15. 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.

  16. 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.

  17. Unobtrusive Nocturnal Heartbeat Monitoring by a Ballistocardiographic Sensor in Patients with Sleep Disordered Breathing.

    Science.gov (United States)

    Zink, Matthias Daniel; Brüser, Christoph; Stüben, Björn-Ole; Napp, Andreas; Stöhr, Robert; Leonhardt, Steffen; Marx, Nikolaus; Mischke, Karl; Schulz, Jörg B; Schiefer, Johannes

    2017-10-13

    Sleep disordered breathing (SDB) is known for fluctuating heart rates and an increased risk of developing arrhythmias. The current reference for heartbeat analysis is an electrocardiogram (ECG). As an unobtrusive alternative, we tested a sensor foil for mechanical vibrations to perform a ballistocardiography (BCG) and applied a novel algorithm for beat-to-beat cycle length detection. The aim of this study was to assess the correlation between beat-to-beat cycle length detection by the BCG algorithm and simultaneously recorded ECG. In 21 patients suspected for SDB undergoing polysomnography, we compared ECG to simultaneously recorded BCG data analysed by our algorithm. We analysed 362.040 heartbeats during a total of 93 hours of recording. The baseline beat-to-beat cycle length correlation between BCG and ECG was r s  = 0.77 (n = 362040) with a mean absolute difference of 15 ± 162 ms (mean cycle length: ECG 923 ± 220 ms; BCG 908 ± 203 ms). After filtering artefacts and improving signal quality by our algorithm, the correlation increased to r s  = 0.95 (n = 235367) with a mean absolute difference in cycle length of 4 ± 72 ms (ECG 920 ± 196 ms; BCG 916 ± 194 ms). We conclude that our algorithm, coupled with a BCG sensor foil provides good correlation of beat-to-beat cycle length detection with simultaneously recorded ECG.

  18. Measurement of Aortic Pulse Wave Velocity With a Connected Bathroom Scale.

    Science.gov (United States)

    Campo, David; Khettab, Hakim; Yu, Roger; Genain, Nicolas; Edouard, Paul; Buard, Nadine; Boutouyrie, Pierre

    2017-09-01

    Measurement of arterial stiffness should be more available. Our aim was to show that aortic pulse wave velocity can be reliably measured with a bathroom scale combining the principles of ballistocardiography (BCG) and impedance plethysmography on a single foot. The calibration of the bathroom scale was conducted on a group of 106 individuals. The aortic pulse wave velocity was measured with the SphygmoCor in the supine position. Three consecutive measurements were then performed on the Withings scale in the standing position. This aorta-leg pulse transit time (alPTT) was then converted into a velocity with the additional input of the height of the person. Agreement between the SphygmoCor and the bathroom scale so calibrated is assessed on a separate group of 86 individuals, following the same protocol. The bias is 0.25 m·s-1 and the SE 1.39 m·s-1. This agreement with Sphygmocor is "acceptable" according to the ARTERY classification. The alPTT correlated well with cfPTT with (Spearman) R = 0.73 in pooled population (cal 0.79, val 0.66). The aorta-leg pulse wave velocity correlated with carotid-femoral pulse wave velocity with R = 0.76 (cal 0.80, val 0.70). Estimation of the aortic pulse wave velocity is feasible with a bathroom scale. Further investigations are needed to improve the repeatability of measurements and to test their accuracy in different populations and conditions. © The Author 2017. Published by Oxford University Press on behalf of American Journal of Hypertension.

  19. Balistocardiógrafo: historia de un instrumento para medir en forma indirecta el desempeño del corazón Balistocardiograph: history of an instrument for indirect assessment of heart performance

    Directory of Open Access Journals (Sweden)

    Alberto Barón C

    2009-02-01

    with phonocardiography and the registry of carotid and venous pulse, and the apexcardiogram, was of great importance to relate the waves with physiological events. Dr. Starr recognized the relationship between the waves and cardiac output and it’s usefulness in the follow-up of patients with heart failure. Luis Carlos Barón Plata, a cardiologist born in Bogotá, designed and handcrafted a direct ballistocardiograph. It differed from Dock and Taubman’s machine in the way of obtaining the corporal movements: he designed a sensor placed in contact with the head in order to record the displacement of the cranium. With this he was able to register adequately the ballistocardiographic waves. The construction was austere and was connected by two cables to the electrocardiograph. With the development of simpler and more accurate methods to observe and quantify the heart’s physiology, the ballistocardiography lost popularity, and that technique has disappeared from almost all the cardiology units.