标题： 日常生活中智能手机使用期间的被动心率监测 显示英文标题

标题： Passive Heart Rate Monitoring During Smartphone Use in Everyday Life

摘要： 静息心率（RHR）是心血管健康和死亡率的重要生物标志物，但纵向跟踪通常需要可穿戴设备，限制了其可用性。 我们提出了PHRM，这是一种深度学习系统，在日常智能手机使用过程中通过基于面部视频的光电容积描记法进行被动的心率（HR）和RHR测量。 我们的系统使用了来自495名参与者的225,773个视频进行开发，并在实验室和自由生活条件下对来自205名参与者的185,970个视频进行了验证，这是同类中最大的验证研究。 与参考心电图相比，PHRM在轻度、中度和深色色素三种皮肤色调群体中的心率测量平均绝对百分比误差（MAPE）小于10%；每种皮肤色调群体的MAPE与其他群体相比不劣。 由PHRM测得的每日RHR与可穿戴心率追踪器相比，平均绝对误差小于5 bpm，并且与已知的风险因素相关。 这些结果突显了智能手机在实现被动和公平的心脏健康监测方面的潜力。 显示英文摘要

摘要： 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.