Time Domain and Frequency Domain Heart Rate Variability Analysis on Electrocardiograms and Mechanocardiograms from...

Area of Science:

• Cardiology
• Biomedical Engineering
• Physiology

Background:

• Heart rate variability (HRV) quantifies autonomic nervous system activity using interbeat interval variations.
• Electrocardiograms (ECG) are standard for HRV analysis, but cardiac mechanical signals like seismocardiograms (SCG) and gyrocardiograms (GCG) offer alternative insights.
• Valvular heart disease (VHD) can alter cardiac signal morphology, potentially impacting HRV analysis.

Purpose of the Study:

• To assess the influence of VHD on the correlation between HRV indices derived from ECG, SCG, and GCG.
• To compare HRV indices obtained from these three cardiac signal types in the context of VHD.

Main Methods:

• Collected ECG, SCG, and GCG signals from individuals with and without VHD.
• Performed time and frequency domain HRV analysis on all three signal types.
• Quantified the linear correlation between HRV indices across the different signal modalities.

Main Results:

• HRV indices derived from ECG, SCG, and GCG demonstrated strong linear correlations.
• Results remained within standard deviation, indicating consistency across signal types.
• VHD influenced SCG and GCG waveforms but did not invalidate the derived HRV indices.

Conclusions:

• Cardiac mechanical signals (SCG and GCG) are valid for HRV assessment, even in the presence of VHD.
• HRV analysis using SCG and GCG can complement ECG-based methods for evaluating cardiac health.
• These findings support the clinical relevance of non-invasive mechanical cardiac signal analysis for HRV monitoring.