A Method for Detecting Key Fiducial Points in Electrocardiographic Signals for Wave Characterization and HRV Analysis

The analysis of physiological signals is fundamental in fields such as healthcare and sports science, while cardiovascular disease remains a significant global health challenge. This study presents a method for detecting key fiducial points in electrocardiographic (ECG) signals. ECG signals were acquired using the Zephyr BioHarness 3.0 (reference device) and a new wireless ECG device (test device) to conduct the study. Measurements, including wave amplitude and duration, were obtained by identifying these points in the averaged waveform of each ECG signal. Hence, features such as P-wave, QRS complex, T-wave and their relative intervals were extracted from ECG signals provided by both devices. In addition, a heart rate variability (HRV) analysis was conducted, which provides additional information about cardiac health. HRV was analyzed in both time and frequency domains. The results demonstrate the reliability of both devices in identifying significant ECG features, with only minor variations in specific parameters. Notably, the QRS complex shows biases between 0 to 20 ms with percentage differences up to 30%, while the PR interval exhibits biases from 2 to 22 ms and percentage differences up to 33%. The HRV analysis shows strong agreement between the two devices. The study also highlights that both devices consistently measure heart rate (HR) (Pearson’s correlation coefficient: 0.88), further validating their accuracy and reliability for clinical and remote monitoring applications. These findings suggest that both devices are suitable for clinical and remote monitoring. Integrating these advanced ECG analysis methods could significantly improve patient monitoring and outcomes in both clinical and non-clinical environments.