Features extraction from cardiac-related signals: comparison among different measurement methods

Abstract

Abstract Heart Rate (HR), Heart Rate Variability (HRV), and cardiac time intervals are clinically relevant parameters, which can be assessed from the analysis of electrocardiogram (ECG). Some aspects of cardiac activity can be investigated also by means of different noninvasive and non-intrusive measurement methods, such as phonocardiograph (PCG), photoplethysmograph (PPG), and vibrocardiograph (VCG). However, the standard processing algorithms (i.e., Pan & Tompkins) do not allow to fully characterize waveforms different from ECG. In the past, some of the authors have already demonstrated the efficiency of a novel processing procedure for the precise HR measurement from the above-mentioned signals. In the present work, data processing procedure has been improved and deeply extended to assess HRV parameters and time intervals from all the signals acquired on an extended experimental campaign, involving 26 subjects, on whom ECG, PPG, PCG, and VCG signals were simultaneously measured. Results prove that this approach can overcome the drawbacks of standard algorithms and can be widely applied to signals of different nature to derive HR, HRV, and time intervals. As regards HR measurement, PPG proved to be the most accurate measurement method (±1.2 bpm), followed by VCG (±1.6 bpm) and PCG (±2.5 bpm). For HRV analysis in the time domain, the use of the proposed methodology allows to obtain clinically relevant parameters statistically comparable to the ECG ones. Finally, the measurement of QT interval by applying personal calibration lines allows to obtain results comparable to the gold standard technique, i.e., ECG (maximum percentage deviation reduced from 10.9% up to <4.3% in VCG).