Passive Heart Rate Monitoring During Smartphone Use in Everyday Life
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 14 of its 71 references that are in the map. First posted on arXiv 4 Mar 2025.
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14 of 71 references.
References · 14
- 2021Ensemble deep learning: A reviewcited by 284
- 2020Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurementcited by 134
- 2019Remote Photoplethysmograph Signal Measurement from Facial Videos Using Spatio-Temporal Networkscited by 128
- 2021PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformercited by 120
- 2018A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillationcited by 110
- 2019RhythmNet: End-to-end Heart Rate Estimation from Face via Spatial-temporal Representationcited by 105
- 2021EfficientPhys: Enabling Simple, Fast and Accurate Camera-Based Vitals Measurementcited by 73
- 2022rPPG-Toolbox: Deep Remote PPG Toolboxcited by 64
- 2023MMPD: Multi-Domain Mobile Video Physiology Datasetcited by 57
- 2018A Comprehensive Analysis of Deep Regressioncited by 48
- 2022SimPer: Simple Self-Supervised Learning of Periodic Targetscited by 44
- 2024RhythmMamba: Fast, Lightweight, and Accurate Remote Physiological Measurementcited by 20
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.