Institute of Cognitive Neuroscience, University College London, University of London, London, United Kingdom.
Experimental Psychology, University College London, University of London, London, United Kingdom.
PeerJ. 2022 Mar 23;10:e13147. doi: 10.7717/peerj.13147. eCollection 2022.
Heart rate and heart rate variability have enabled insight into a myriad of psychophysiological phenomena. There is now an influx of research attempting using these metrics within both laboratory settings (typically derived through electrocardiography or pulse oximetry) and ecologically-rich contexts ( wearable photoplethysmography, , smartwatches). However, these signals can be prone to artifacts and a low signal to noise ratio, which traditionally are detected and removed through visual inspection. Here, we developed an open-source Python package, RapidHRV, dedicated to the preprocessing, analysis, and visualization of heart rate and heart rate variability. Each of these modules can be executed with one line of code and includes automated cleaning. In simulated data, RapidHRV demonstrated excellent recovery of heart rate across most levels of noise (>=10 dB) and moderate-to-excellent recovery of heart rate variability even at relatively low signal to noise ratios (>=20 dB) and sampling rates (>=20 Hz). Validation in real datasets shows good-to-excellent recovery of heart rate and heart rate variability in electrocardiography and finger photoplethysmography recordings. Validation in wrist photoplethysmography demonstrated RapidHRV estimations were sensitive to heart rate and its variability under low motion conditions, but estimates were less stable under higher movement settings.
心率和心率变异性使人们能够深入了解各种心理生理现象。现在有大量的研究试图在实验室环境（通常通过心电图或脉搏血氧饱和度仪获得）和生态丰富的环境中（可穿戴光电容积脉搏波描记法、智能手表）使用这些指标。然而，这些信号容易受到伪影和低信噪比的影响，传统上通过视觉检查来检测和去除这些影响。在这里，我们开发了一个名为 RapidHRV 的开源 Python 包，专门用于心率和心率变异性的预处理、分析和可视化。这些模块中的每一个都可以用一行代码执行，并包括自动清理。在模拟数据中，RapidHRV 表现出在大多数噪声水平（>=10dB）下对心率的出色恢复能力，以及在相对较低的信噪比（>=20dB）和采样率（>=20Hz）下对心率变异性的良好到出色的恢复能力。在真实数据集的验证中，RapidHRV 在心电图和手指光电容积脉搏波描记法记录中表现出对心率和心率变异性的良好到出色的恢复能力。在腕部光电容积脉搏波描记法的验证中，RapidHRV 的估计值对低运动条件下的心率及其变异性敏感，但在更高的运动设置下，估计值不太稳定。
