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Sensors 2018, 18(2), 379; doi:10.3390/s18020379

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

1
Department of Computer Science and Information Engineering, Chang Gung University, Guishan 33302, Taiwan
2
Department of Electrical Engineering and Center for Biomedical Engineering/College of Engineering, Chang Gung University, Guishan 33302, Taiwan
3
Graduate Institute of Medical Mechatronics, Center for Biomedical Engineering, Chang Gung University, Guishan 33302, Taiwan
4
Division of Cardiology, Department of Internal Medicine, Chang Gung Memorial Hospital, Linkou 33305, Taiwan
*
Author to whom correspondence should be addressed.
Received: 30 November 2017 / Revised: 21 January 2018 / Accepted: 24 January 2018 / Published: 28 January 2018
(This article belongs to the Special Issue Sensors for Health Monitoring and Disease Diagnosis)
View Full-Text   |   Download PDF [4201 KB, uploaded 29 January 2018]   |  

Abstract

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 standalone use of ECG and SCG. View Full-Text
Keywords: cardiovascular disease (CVD); electrocardiogram (ECG); seismocardiogram (SCG); cardiac anomalies cardiovascular disease (CVD); electrocardiogram (ECG); seismocardiogram (SCG); cardiac anomalies
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MDPI and ACS Style

Sahoo, P.K.; Thakkar, H.K.; Lin, W.-Y.; Chang, P.-C.; Lee, M.-Y. On the Design of an Efficient Cardiac Health Monitoring System Through Combined Analysis of ECG and SCG Signals. Sensors 2018, 18, 379.

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