Assessment of Physiological Signals from Photoplethysmography Sensors Compared to an Electrocardiogram Sensor: A Validation Study in Daily Life

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 21; p. 6826
• Main Authors: Rehman, Rana Zia Ur, Chatterjee, Meenakshi, Manyakov, Nikolay V, Daans, Melina, Jackson, Amanda, O’Brisky, Andrea, Telesky, Tacie, Smets, Sophie, Berghmans, Pieter-Jan, Yang, Dongyan, Reynoso, Elena, Lucas, Molly V, Huo, Yanran, Thirugnanam, Vasanth T, Mansi, Tommaso, Morris, Mark
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 24-10-2024; MDPI
• Subjects: Accelerometers; Accuracy; Agreements; Algorithms; Body temperature; Comparative analysis; Data collection; ECG; Electrocardiogram; Electrocardiography; Heart beat; Heart rate; heart rate variability; Medical research; Medicine, Experimental; Nervous system; Personal health; Physiological aspects; Physiology; PPG; pulse rate; Respiration; Sensors; Skin; Sleep; Smartwatches; Usability testing; Wearable computers; wearables; United States > US
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24216826

Wearables with photoplethysmography (PPG) sensors are being increasingly used in clinical research as a non-invasive, inexpensive method for remote monitoring of physiological health. Ensuring the accuracy and reliability of PPG-derived measurements is critical, as inaccuracies can impact research findings and clinical decisions. This paper systematically compares heart rate (HR) and heart rate variability (HRV) measures from PPG against an electrocardiogram (ECG) monitor in free-living settings. Two devices with PPG and one device with an ECG sensor were worn by 25 healthy volunteers for 10 days. PPG-derived HR and HRV showed reasonable accuracy and reliability, particularly during sleep, with mean absolute error < 1 beat for HR and 6–15 ms for HRV. The relative error of HRV estimated from PPG varied with activity type and was higher than during the resting state by 14–51%. The accuracy of HR/HRV was impacted by the proportion of usable data, body posture, and epoch length. The multi-scale peak and trough detection algorithm demonstrated superior performance in detecting beats from PPG signals, with an F1 score of 89% during sleep. The study demonstrates the trade-offs of utilizing PPG measurements for remote monitoring in daily life and identifies optimal use conditions by recommending enhancements.