搭建12台手机并行测试平台，精准验证手机心率测量性能。
A High-Throughput Platform to Bench Test Smartphone-Based Heart Rate Measurements Derived From Video
- 设计可同时测12部手机的测试架与可控信号视频生成方法。
- 误差仅0.11%，相关性达0.92，准确识别所有机型符合医疗标准。
- 适合开发者、医疗器械厂商做手机心率应用预测试。
基于手机摄像头的手指-摄像头光电容积脉搏波描记法（PPG）心率监测应用面临性能评估难、设备兼容性差的问题，因设备差异大且缺乏标准化测试方法。本文提出一种高通量桌面测试平台，包含可容纳12部手机的测试支架、可调控心率与信号质量的合成PPG视频生成方法，以及用于协调播放与数据记录的主机系统。该平台在临床验证的心率应用中实现输入与测量心率均值绝对百分比误差（MAPE）为0.11% ± 0.001%，输入与测量PPG信号相关系数为0.92 ± 0.008。对20款不同手机型号的测试结果表明，所有设备均正确分类为符合ANSI/CTA心率监测仪精度标准（MAPE <10%），与包含80名参与者的前瞻性临床研究结果一致，展现出高阳性预测价值。该平台为手机心率应用的部署前测试提供可扩展解决方案，提升应用性能与设备兼容性，推动移动健康发展。
原文摘要 · Abstract (English)
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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