On the design of an efficient cardiac health monitoring system through combined analysis of ECG and SCG signals

Prasan Kumar Sahoo, Hiren Kumar Thakkar, Wen Yen Lin, Po Cheng Chang, Ming Yih Lee*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

54 Scopus citations

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.

Original languageEnglish
Article number379
JournalSensors
Volume18
Issue number2
DOIs
StatePublished - 02 2018

Bibliographical note

Publisher Copyright:
© 2018 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Cardiac anomalies
  • Cardiovascular disease (CVD)
  • Electrocardiogram (ECG)
  • Seismocardiogram (SCG)

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