Liu Ivan, Ni Shiguang, Peng Kaiping
Data Science and Information Technology Research Center, Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China.
Graduate School at Shenzhen, Tsinghua University, Shenzhen, China.
Telemed J E Health. 2020 Dec;26(12):1483-1491. doi: 10.1089/tmj.2019.0283. Epub 2020 Feb 26.
Heart rate variability (HRV) provides essential mental health information for clinical diagnosis, telemedicine, preventive medicine, and public health; however, the lack of a convenient detection method limits its potential. This study aims to investigate the feasibility and credibility of smartphone photoplethysmogram (PPG)-based HRV analysis for mental well-being and health assessment. Data were collected from 93 students and university employees in Shenzhen, China. Forty-six percent were male, and the average age was 23.71 years (σ = 4.33). An app recorded a 4-min video of their fingertips and converted the frames into five HRV measures, including the root mean square of successive differences (rMSSD), standard deviation of the normal-to-normal (NN) intervals (SDNN), percentage of successive NN intervals differing by ≥50 ms (pNN50), log high-frequency (HF) HRV, and log low-frequency (LF) HRV. The data verify the positive relationship between mental well-being and HRV measures. Participants with higher Satisfaction With Life Scale (SWLS) scores have a higher rMSSD ( = 0.047), SDNN ( = 0.009), log HF ( = 0.02), and log LF ( = 0.003). Participants who suffer from depression have lower log HF ( = 0.048) and log LF ( = 0.02). Participants in the high-anxiety group have lower pNN50 ( = 0.04) and log HF ( = 0.03). The results of this study validate the feasibility of using the smartphone PPG by demonstrating similar results to previous findings. Our data also support the theorized positive link between mental health and HRV.
心率变异性（HRV）为临床诊断、远程医疗、预防医学和公共卫生提供重要的心理健康信息；然而，缺乏便捷的检测方法限制了其潜力。本研究旨在探讨基于智能手机光电容积脉搏波描记图（PPG）的HRV分析用于心理健康和健康评估的可行性和可信度。数据收集自中国深圳的93名学生和大学员工。其中46%为男性，平均年龄为23.71岁（标准差=4.33）。一款应用程序记录了他们指尖的4分钟视频，并将这些帧转换为五项HRV指标，包括逐次差值的均方根（rMSSD）、正常到正常（NN）间期的标准差（SDNN）、逐次NN间期相差≥50毫秒的百分比（pNN50）、高频（HF）HRV的对数以及低频（LF）HRV的对数。这些数据证实了心理健康与HRV指标之间的正相关关系。生活满意度量表（SWLS）得分较高的参与者具有较高的rMSSD（=0.047）、SDNN（=0.009）、HF对数（=0.02）和LF对数（=0.003）。患有抑郁症的参与者HF对数（=0.048）和LF对数（=0.02）较低。高焦虑组的参与者pNN50（=0.04）和HF对数（=0.03）较低。本研究结果通过展示与先前研究结果相似的结果，验证了使用智能手机PPG的可行性。我们的数据还支持了心理健康与HRV之间理论上的正向联系。
