Metrological Evaluation of Wearable ECG Systems: Heart Rate Estimation and PQRST Waveform Analysis

Wearable devices with electrocardiographic (ECG) sensors offer a strong and practical alternative to clinical systems monitoring physiological parameters. Identifying key ECG waveform points is essential for extracting cardiac features (e.g., PR intervals, QRS duration, QT intervals) and understanding cardiac function. This study evaluates heart rate (HR) estimation accuracy and precision using the Zephyr BioHarness 3.0 (reference device) and a 12-lead wireless ECG (test device) during rest and treadmill walking. It also develops an algorithm to detect PQRST wave points for extracting ECG features during various conditions (rest, walking, inclined walking, recovery). Compared to the BioHarness, the test device demonstrated high agreement in HR estimation (mean ± standard deviation = 0.11 bpm ± 2.04 bpm, p = 0.99), with minimal error in resting conditions. However, motion artifacts introduced variability, particularly during walking and inclined walking (walking MAE: 1.47 bpm ± 2.07 bpm; inclined walking MAE: 2.09 bpm ± 5.78 bpm; mean ± standard). Feature extraction analysis revealed increased errors in QRS and QT interval detection under dynamic conditions. In contrast, P-wave and PR interval related residuals were lower under dynamic conditions (inclined walking P-wave MAE: 18.22 ms ± 14.16 ms; PR interval MAE: 28.58 ms ± 22.66 ms; mean ± standard).