Key result
Seismocardiography and gyrocardiography strongly correlate with ECG for measuring heart rate variability indices.
Why the study?
SCG and GCG monitor cardiac mechanical activity and may allow simultaneous HRV analysis and evaluation of valvular heart diseases, but comparison against ECG-derived indices across these populations was needed.
Do seismocardiography and gyrocardiography provide reliable time-domain, frequency-domain, and nonlinear heart rate variability indices compared with electrocardiography in healthy volunteers and patients with valvular heart diseases?
Cross-Sectional (n=59)
No
Do seismocardiography and gyrocardiography provide reliable time-domain, frequency-domain, and nonlinear heart rate variability indices compared with electrocardiography in healthy volunteers and patients with valvular heart diseases?
Heart rate variability indices derived from seismocardiograms and gyrocardiograms strongly correlate with reference ECG indices in both healthy subjects and patients with valvular heart disease, supporting the feasibility of mechanocardiography for simultaneous autonomic and valvular monitoring.
Answers are grounded in this paper and cite their sources.
Supports concurrent HRV monitoring in valvular disease; extends mechanocardiography validation but leaves open prospective utility.
Heart rate variability (HRV) is the physiological variation in the intervals between consecutive heartbeats that reflects the activity of the autonomic nervous system. This parameter is traditionally evaluated based on electrocardiograms (ECG signals). Seismocardiography (SCG) and/or gyrocardiography (GCG) are used to monitor cardiac mechanical activity; therefore, they may be used in HRV analysis and the evaluation of valvular heart diseases (VHDs) simultaneously. The purpose of this study was to compare the time domain, frequency domain and nonlinear HRV indices obtained from electrocardiograms, seismocardiograms (SCG signals) and gyrocardiograms (GCG signals) in healthy volunteers and patients with valvular heart diseases. An analysis of the time domain, frequency domain and nonlinear heart rate variability was conducted on electrocardiograms and gyrocardiograms registered from 29 healthy male volunteers and 30 patients with valvular heart diseases admitted to the Columbia University Medical Center (New York City, NY, USA). The results of the HRV analysis show a strong linear correlation with the HRV indices calculated from the ECG, SCG and GCG signals and prove the feasibility and reliability of HRV analysis despite the influence of VHDs on the SCG and GCG waveforms.
No takes yet. Share an insight, caveat, or question.
Sieciński et al. (2023) conducted a cross-sectional in Valvular heart disease and healthy controls (n=59). Seismocardiography (SCG) and gyrocardiography (GCG) heart rate variability (HRV) analysis vs. Electrocardiography (ECG) heart rate variability (HRV) analysis (and healthy volunteers vs. patients with valvular heart disease) was evaluated on Time-domain, frequency-domain, and nonlinear heart rate variability (HRV) indices (AVNN, SDNN, RMSSD, pNN50, VLF, LF, HF, LF/HF, SD1, SD2, SD1/SD2) and Pearson's linear correlation (ρ) between ECG, SCG, and GCG signals (p=<0.001). Seismocardiography and gyrocardiography-derived heart rate variability indices showed strong linear correlation (ρ > 0.7, p < 0.001) with ECG-derived indices in healthy and valvular heart disease subjects.
Synapse has enriched 10 related papers. Consider them for comparative context: