» Articles » PMID: 27541330

Quantifying and Reducing Motion Artifacts in Wearable Seismocardiogram Measurements During Walking to Assess Left Ventricular Health

Overview
Date 2016 Aug 20
PMID 27541330
Citations 30
Authors
Affiliations
Soon will be listed here.
Abstract

Goal: Our objective is to provide a framework for extracting signals of interest from the wearable seismocardiogram (SCG) measured during walking at normal (subject's preferred pace) and moderately fast (1.34-1.45 m/s) speeds.

Methods: We demonstrate, using empirical mode decomposition (EMD) and feature tracking algorithms, that the pre-ejection period (PEP) can be accurately estimated from a wearable patch that simultaneously measures electrocardiogram and sternal acceleration signals. We also provide a method to determine the minimum number of heartbeats required for an accurate estimate to be obtained for the PEP from the accelerometer signals during walking.

Results: The EMD-based denoising approach provides a statistically significant increase in the signal-to-noise ratio of wearable SCG signals and also improves estimation of PEP during walking.

Conclusion: The algorithms described in this paper can be used to provide hemodynamic assessment from wearable SCG during walking.

Significance: A major limitation in the use of the SCG, a measure of local chest vibrations caused by cardiac ejection of blood in the vasculature, is that a user must remain completely still for high-quality measurements. The motion can create artifacts and practically render the signal unreadable. Addressing this limitation could allow, for the first time, SCG measurements to be obtained reliably during movement-aside from increasing the coverage throughout the day of cardiovascular monitoring, analyzing SCG signals during movement would quantify the cardiovascular system's response to stress (exercise), and thus provide a more holistic assessment of overall health.

Citing Articles

Enhancing visual seismocardiography in noisy environments with adaptive bidirectional filtering for Cardiac Health Monitoring.

N G, Bhat C, Tr M, Yimer T BMC Med Inform Decis Mak. 2024; 24(1):282.

PMID: 39354526 PMC: 11445874. DOI: 10.1186/s12911-024-02690-1.


EmoWear: Wearable Physiological and Motion Dataset for Emotion Recognition and Context Awareness.

Rahmani M, Symons M, Sobhani O, Berkvens R, Weyn M Sci Data. 2024; 11(1):648.

PMID: 38898046 PMC: 11187197. DOI: 10.1038/s41597-024-03429-3.


A Wavelet-Based Approach for Motion Artifact Reduction in Ambulatory Seismocardiography.

Skoric J, DMello Y, Plant D IEEE J Transl Eng Health Med. 2024; 12:348-358.

PMID: 38606390 PMC: 11008810. DOI: 10.1109/JTEHM.2024.3368291.


Contactless remote monitoring of sleep: evaluating the feasibility of an under-mattress sensor mat in a real-life deployment.

Sadek I, Abdulrazak B Health Syst (Basingstoke). 2023; 12(3):264-280.

PMID: 37860595 PMC: 10583615. DOI: 10.1080/20476965.2022.2072777.


Postural and longitudinal variability in seismocardiographic signals.

Azad M, Gamage P, Dhar R, Sandler R, Mansy H Physiol Meas. 2023; 44(2).

PMID: 36638534 PMC: 9969814. DOI: 10.1088/1361-6579/acb30e.


References
1.
Mukkamala R, Hahn J, Inan O, Mestha L, Kim C, Toreyin H . Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Theory and Practice. IEEE Trans Biomed Eng. 2015; 62(8):1879-901. PMC: 4515215. DOI: 10.1109/TBME.2015.2441951. View

2.
van der Hoeven G, Clerens P, Donders J, Beneken J, VONK J . A study of systolic time intervals during uninterrupted exercise. Br Heart J. 1977; 39(3):242-54. PMC: 483228. DOI: 10.1136/hrt.39.3.242. View

3.
Mozaffarian D, Benjamin E, Go A, Arnett D, Blaha M, Cushman M . Executive Summary: Heart Disease and Stroke Statistics--2016 Update: A Report From the American Heart Association. Circulation. 2016; 133(4):447-54. DOI: 10.1161/CIR.0000000000000366. View

4.
McCombie D, Shaltis P, Reisner A, Asada H . Adaptive hydrostatic blood pressure calibration: development of a wearable, autonomous pulse wave velocity blood pressure monitor. Annu Int Conf IEEE Eng Med Biol Soc. 2007; 2007:370-3. DOI: 10.1109/IEMBS.2007.4352301. View

5.
Tavakolian K, Ngai B, Blaber A, Kaminska B . Infrasonic cardiac signals: complementary windows to cardiovascular dynamics. Annu Int Conf IEEE Eng Med Biol Soc. 2012; 2011:4275-8. DOI: 10.1109/IEMBS.2011.6091061. View