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

Prasan Kumar Sahoo1,2, Hiren Kumar Thakkar3, Wen-Yen Lin4,5

  • 1Department of Computer Science and Information Engineering, Chang Gung University, Guishan 33302, Taiwan. pksahoo@mail.cgu.edu.tw.

Insights

This study introduces a low-cost, non-invasive method for continuous cardiac health monitoring by combining electrocardiogram (ECG) and seismocardiogram (SCG) signals. Joint analysis of ECG and SCG offers more reliable detection of cardiac anomalies than using ECG alone.

Area of Science:

  • Biomedical Engineering
  • Cardiology
  • Signal Processing

Background:

  • Cardiovascular disease (CVD) poses a significant global health and economic burden.
  • Current high-end cardiac monitoring systems (MRI, CT, Echo) are expensive and unsuitable for continuous, unobtrusive monitoring.
  • Electrocardiogram (ECG) alone provides limited information on cardiac activity.

Purpose of the Study:

  • To explore continuous, non-invasive, and low-cost cardiac health monitoring.
  • To investigate the combined use of seismocardiogram (SCG) and ECG signals for robust cardiac monitoring.
  • To develop novel methods for early detection of cardiac anomalies.

Main Methods:

  • Simultaneous acquisition of ECG and SCG signals using an in-laboratory model.
  • Development of automatic feature point delineation mechanisms for both ECG and SCG signals.
  • Implementation of a Naïve Bayes classifier for combined ECG and SCG signal analysis.

Main Results:

  • Proposed feature delineation and abnormality detection methods demonstrated consistent performance.
  • Experiments on 12,000 cardiac cycles showed promising results.
  • Combined ECG and SCG analysis proved more reliable for cardiac health monitoring than standalone methods.

Conclusions:

  • The joint analysis of ECG and SCG signals provides a feasible, low-cost, and reliable alternative for continuous cardiac health monitoring.
  • This approach enables early detection of cardiac anomalies, improving patient outcomes.
  • The developed methods offer a significant advancement over traditional ECG-only monitoring.

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