基于光电容积描记仪的腕戴式心率恢复估计

Daivaras Sokas, A. Petrėnas, S. Daukantas, Andrius Rapalis, V. Marozas
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引用次数: 1

摘要

从光体积描记图(PPG)信号中估计脉搏率导致了智能腕带技术的突破。本研究介绍了一种估算心率恢复(HRR)的方法,该方法使用一种定制的腕带设备,能够获取瞬时脉搏率,以及一种消费者智能腕带,可以提供间隔5秒或更长时间的脉搏率。通过与同步获取的参考心电图进行比较,评估使用基于ppg的设备估计HRR参数的可行性。对22名健康受试者进行标准化爬楼梯测试,并对脉搏数据进行三个HRR参数的研究。研究结果表明,与消费者智能腕带相比,使用腕带估计的HRR参数的绝对误差要低两倍,这强调了瞬时脉搏率对确保足够准确的参数估计的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Photoplethysmography-based estimation of heart rate recovery using a wrist-worn device
Estimation of pulse rate from photoplethysmogram (PPG) signals has led to a breakthrough in a smart wristband technology. This study introduces a method for estimating heart rate recovery (HRR) using a custom-made wrist-worn device, capable of acquiring instantaneous pulse rate, as well as a consumer smart wristband, which provides pulse rate at intervals of 5 s or longer. The feasibility to estimate HRR parameters using the PPG-based devices was assessed by comparing to the synchronously acquired reference electrocardiogram. Three HRR parameters were studied on pulse rate data, obtained from 22 healthy participants, instructed to perform standardized stair climbing test. Study findings show that HRR parameters, estimated using the wrist-worn device, are associated with twice lower absolute error compared to the consumer smart wristband, emphasizing the importance of an instantaneous pulse rate to ensure a sufficiently accurate parameter estimation.
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