Data Science and Information Technology Research Center, Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, China.
Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China.
Sensors (Basel). 2020 Mar 30;20(7):1923. doi: 10.3390/s20071923.
Heart rate variability (HRV) provides essential health information such as the risks of heart attacks and mental disorders. However, inconvenience related to the accurate detection of HRV limits its potential applications. The ubiquitous use of smartphones makes them an excellent choice for regular and portable health monitoring. Following this trend, smartphone photoplethysmography (PPG) has recently garnered prominence; however, the lack of robustness has prevented both researchers and practitioners from embracing this technology. This study aimed to bridge the gap in the literature by developing a novel smartphone PPG quality index (SPQI) that can filter corrupted data. A total of 226 participants joined the study, and results from 1343 samples were used to validate the proposed sinusoidal function-based model. In both the correlation coefficient and Bland-Altman analyses, the agreement between HRV measurements generated by both the smartphone PPG and the reference electrocardiogram improved when data were filtered through the SPQI. Our results support not only the proposed approach but also the general value of using smartphone PPG in HRV analysis.
心率变异性（HRV）提供了重要的健康信息，例如心脏病发作和精神障碍的风险。然而，由于 HRV 的精确检测存在不便，限制了其潜在的应用。智能手机的广泛使用使其成为常规和便携式健康监测的绝佳选择。顺应这一趋势，智能手机光电容积脉搏波（PPG）最近备受关注；然而，由于缺乏稳健性，研究人员和从业者都无法接受这项技术。本研究旨在通过开发一种新的智能手机 PPG 质量指数（SPQI）来填补文献中的空白，该指数可以过滤掉损坏的数据。共有 226 名参与者参加了这项研究，使用 1343 个样本的结果来验证基于正弦函数的模型。在相关系数和 Bland-Altman 分析中，当通过 SPQI 过滤数据时，智能手机 PPG 和参考心电图生成的 HRV 测量之间的一致性得到了改善。我们的结果不仅支持所提出的方法，还支持在 HRV 分析中使用智能手机 PPG 的一般价值。
