A High-Throughput Platform to Bench Test Smartphone-Based Heart Rate Measurements Derived From Video

• URL: http://arxiv.org/abs/2506.23414v1
• Date: Sun, 29 Jun 2025 22:19:40 GMT
• Title: A High-Throughput Platform to Bench Test Smartphone-Based Heart Rate Measurements Derived From Video
• Authors: Ming-Zher Poh, Jonathan Wang, Jonathan Hsu, Lawrence Cai, Eric Teasley, James A. Taylor, Jameson K. Rogers, Anupam Pathak, Shwetak Patel,
• Abstract summary: Smartphone-based heart rate (HR) monitoring apps face significant challenges in performance evaluation and device compatibility due to device variability and fragmentation.<n>This paper presents a novel, high- throughput bench-testing platform to address this critical need.<n>This platform offers a scalable solution for pre-deployment testing of smartphone HR apps to improve app performance, ensure device compatibility, and advance the field of mobile health.
• Score: 1.1764451419983009
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Smartphone-based heart rate (HR) monitoring apps using finger-over-camera photoplethysmography (PPG) face significant challenges in performance evaluation and device compatibility due to device variability and fragmentation. Manual testing is impractical, and standardized methods are lacking. This paper presents a novel, high-throughput bench-testing platform to address this critical need. We designed a system comprising a test rig capable of holding 12 smartphones for parallel testing, a method for generating synthetic PPG test videos with controllable HR and signal quality, and a host machine for coordinating video playback and data logging. The system achieved a mean absolute percentage error (MAPE) of 0.11% +/- 0.001% between input and measured HR, and a correlation coefficient of 0.92 +/- 0.008 between input and measured PPG signals using a clinically-validated smartphone-based HR app. Bench-testing results of 20 different smartphone models correctly classified all the devices as meeting the ANSI/CTA accuracy standards for HR monitors (MAPE <10%) when compared to a prospective clinical study with 80 participants, demonstrating high positive predictive value. This platform offers a scalable solution for pre-deployment testing of smartphone HR apps to improve app performance, ensure device compatibility, and advance the field of mobile health.

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