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使用智能手机在呼吸动作和身体运动期间进行非接触式心率变异性(HRV)估计。

Contactless Heart Rate Variability (HRV) Estimation Using a Smartphone During Respiratory Maneuvers and Body Movement.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:84-87. doi: 10.1109/EMBC46164.2021.9630167.

DOI:10.1109/EMBC46164.2021.9630167
PMID:34891245
Abstract

Heart rate variability (HRV) has been extensively investigated as a noninvasive marker to evaluate the functionality of the autonomic nervous system (ANS). Many studies have provided photoplethysmography (PPG) as a surrogate for electrocardiogram (ECG) signal HRV measurements. Remote PPG (rPPG) has been also investigated for pulse rate variability (PRV) estimation but in controlled conditions. We remotely extracted PRV using a smartphone camera for subjects in static and lateral motion while their respiratory rate was set to three breathing rates in an indoor illumination environment. PRV was compared with ECG-based HRV as a gold standard. We tested our algorithms on five healthy subjects. The results showed high correlation for rPPG-based HRV by presenting means of standard deviation of normal-to-normal intervals (SDNN) and root mean square of successive heartbeat interval differences (RMSSD) correlation coefficient greater than 0.95 in rest and greater than 0.87 in motion. The error of mean low frequency over high frequency (LF/HF) ratio estimated from PRV was 0.13 in rest and 0.25 in lateral motion. Moreover, a statistically significant correlation was obtained between HRV and PRV power spectra and temporal signals for all performed tasks. The obtained results contributed to confirm that remote imaging measurement of cardiac parameters is a promising, convenient, and low-cost alternative to specialized biomedical sensors in a diversity of relevant experimental maneuver.

摘要

心率变异性(HRV)已被广泛研究作为评估自主神经系统(ANS)功能的非侵入性标志物。许多研究已经提供了光体积描记法(PPG)作为心电图(ECG)信号 HRV 测量的替代方法。远程 PPG(rPPG)也已被用于脉冲率变异性(PRV)估计,但仅在受控条件下进行。我们在室内照明环境中,使用智能手机摄像头远程提取了 PRV,同时让受测者保持静态和侧向运动,且他们的呼吸率设置为三种。PRV 与基于 ECG 的 HRV 作为金标准进行了比较。我们在五名健康受试者上测试了我们的算法。结果表明,rPPG 基于 HRV 的相关性很高,在休息时表示正常到正常间隔的标准差(SDNN)和连续心跳间隔差异的均方根(RMSSD)相关系数大于 0.95,在运动时大于 0.87。PRV 估计的低频与高频之比(LF/HF)的平均值误差在休息时为 0.13,在侧向运动时为 0.25。此外,在所有执行的任务中,HRV 和 PRV 功率谱和时间信号之间都获得了具有统计学意义的相关性。所获得的结果有助于证实,在各种相关的实验操作中,远程成像测量心脏参数是一种有前途、方便且低成本的替代专门生物医学传感器的方法。

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