Quantitative Biology > Tissues and Organs
[Submitted on 4 Mar 2025
(v1)
, last revised 21 Mar 2025 (this version, v3)]
Title: Passive Heart Rate Monitoring During Smartphone Use in Everyday Life
Title: 日常生活中智能手机使用期间的被动心率监测
Abstract: Resting heart rate (RHR) is an important biomarker of cardiovascular health and mortality, but tracking it longitudinally generally requires a wearable device, limiting its availability. We present PHRM, a deep learning system for passive heart rate (HR) and RHR measurements during everyday smartphone use, using facial video-based photoplethysmography. Our system was developed using 225,773 videos from 495 participants and validated on 185,970 videos from 205 participants in laboratory and free-living conditions, representing the largest validation study of its kind. Compared to reference electrocardiogram, PHRM achieved a mean absolute percentage error (MAPE) < 10% for HR measurements across three skin tone groups of light, medium and dark pigmentation; MAPE for each skin tone group was non-inferior versus the others. Daily RHR measured by PHRM had a mean absolute error < 5 bpm compared to a wearable HR tracker, and was associated with known risk factors. These results highlight the potential of smartphones to enable passive and equitable heart health monitoring.
Submission history
From: Ming-Zher Poh [view email][v1] Tue, 4 Mar 2025 23:28:10 UTC (12,700 KB)
[v2] Sat, 8 Mar 2025 03:42:34 UTC (12,700 KB)
[v3] Fri, 21 Mar 2025 20:09:40 UTC (12,700 KB)
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