Chest-accelerometry for hemodynamic trending during valsalva-recovery

Pandia, Keya; Ravindran, Sourabh; Kovacs, G.T.A.; Giovangrandi, Laurent; Cole, Randy

doi:10.1109/isabel.2010.5702877

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…The novelty of this article reflects a not yet examined location of the SCG sensor when the MEMS is integrated into the driver's safety belt for measuring the cardio mechanical vibrations. Hence, the SCG signal is affected not only by the already known respiratory and body movement artifacts but also by the movement of the car [28] and the acoustic components [42]. The aim is to obtain a useful SCG signal sufficient for heart rate calculation.…”

Section: Introductionmentioning

confidence: 99%

Driver Cardiovascular Disease Detection Using Seismocardiogram

et al. 2022

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This article deals with the treatment and application of cardiac biosignals, an excited accelerometer, and a gyroscope in the prevention of accidents on the road. Previously conducted studies say that the seismocardiogram is a measure of cardiac microvibration signals that allows for detecting rhythms, heart valve opening and closing disorders, and monitoring of patients' breathing. This article refers to the seismocardiogram hypothesis that the measurements of a seismocardiogram could be used to identify drivers' heart problems before they reach a critical condition and safely stop the vehicle by informing the relevant departments in a nonclinical manner. The proposed system works without an electrocardiogram, which helps to detect heart rhythms more easily. The estimation of the heart rate (HR) is calculated through automatically detected aortic valve opening (AO) peaks. The system is composed of two micro-electromechanical systems (MEMSs) to evaluate physiological parameters and eliminate the effects of external interference on the entire system. The few digital filtering methods are discussed and benchmarked to increase seismocardiogram efficiency. As a result, the fourth adaptive filter obtains the estimated HR = 65 beats per min (bmp) in a still noisy signal (SNR = −11.32 dB). In contrast with the low processing benefit (3.39 dB), 27 AO peaks were detected with a 917.56-ms peak interval mean over 1.11 s, and the calculated root mean square error (RMSE) was 0.1942 m/s2 when the adaptive filter order is 50 and the adaptation step is equal to 0.933.

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Section: Introductionmentioning

confidence: 99%

Driver Cardiovascular Disease Detection Using Seismocardiogram

et al. 2022

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Unified frame of reference improves inter-subject variability of seismocardiograms

et al. 2015

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BackgroundSeismocardiography is the noninvasive measurement of cardiac vibrations transmitted to the chest wall by the heart during its movement. While most applications for seismocardiography are based on unidirectional acceleration measurement, several studies have highlighted the importance of three-dimensional measurements in cardiac vibration studies. One of the main challenges in using three-dimensional measurements in seismocardiography is the significant inter-subject variability of waveforms. This study investigates the feasibility of using a unified frame of reference to improve the inter-subject variability of seismocardiographic waveforms.MethodsThree-dimensional seismocardiography signals were acquired from ten healthy subjects to test the feasibility of the present method for improving inter-subject variability of three-dimensional seismocardiograms. The first frame of reference candidate was the orientation of the line connecting the points representing mitral valve closure and aortic valve opening in seismocardiograms. The second candidate was the orientation of the line connecting the two most distant points in the three dimensional seismocardiogram. The unification of the frame of reference was performed by rotating each subject’s three-dimensional seismocardiograms so that the lines connecting the desired features were parallel between subjects.ResultsThe morphology of the three-dimensional seismocardiograms varied strongly from subject to subject. Fixing the frame of reference to the line connecting the MC and AO peaks enhanced the correlation between the subjects in the y axis from 0.42 ± 0.30 to 0.83 ± 0.14. The mean correlation calculated from all axes increased from 0.56 ± 0.26 to 0.71 ± 0.24 using the line connecting the mitral valve closure and aortic valve opening as the frame of reference. When the line connecting the two most distant points was used as a frame of reference, the correlation improved to 0.60 ± 0.22.ConclusionsThe results indicate that using a unified frame of reference is a promising method for improving the inter-subject variability of three-dimensional seismocardiograms. Also, it is observed that three-dimensional seismocardiograms seem to have latent inter-subject similarities, which are feasible to be revealed. Because the projections of the cardiac vibrations on the measurement axes differ significantly, it seems obligatory to use three-dimensional measurements when seismocardiogram analysis is based on waveform morphology.

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Chest-accelerometry for hemodynamic trending during valsalva-recovery

Cited by 2 publications

References 11 publications

Driver Cardiovascular Disease Detection Using Seismocardiogram

Driver Cardiovascular Disease Detection Using Seismocardiogram

Unified frame of reference improves inter-subject variability of seismocardiograms

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