Biomedical Signal Interpretation & Computational Simulation (BSICoS) Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, 50018 Zaragoza, Spain.
Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain.
Sensors (Basel). 2018 Aug 10;18(8):2619. doi: 10.3390/s18082619.
Heart rate variability (HRV) analysis is a noninvasive tool widely used to assess autonomic nervous system state. The market for wearable devices that measure the heart rate has grown exponentially, as well as their potential use for healthcare and wellbeing applications. Still, there is a lack of validation of these devices. In particular, this work aims to validate the Apple Watch in terms of HRV derived from the RR interval series provided by the device, both in temporal (HRM (mean heart rate), SDNN, RMSSD and pNN50) and frequency (low and high frequency powers, LF and HF) domain. For this purpose, a database of 20 healthy volunteers subjected to relax and a mild cognitive stress was used. First, RR interval series provided by Apple Watch were validated using as reference the RR interval series provided by a Polar H7 using Bland-Altman plots and reliability and agreement coefficients. Then, HRV parameters derived from both RR interval series were compared and their ability to identify autonomic nervous system (ANS) response to mild cognitive stress was studied. Apple Watch measurements presented very good reliability and agreement (>0.9). RR interval series provided by Apple Watch contain gaps due to missing RR interval values (on average, 5 gaps per recording, lasting 6.5 s per gap). Temporal HRV indices were not significantly affected by the gaps. However, they produced a significant decrease in the LF and HF power. Despite these differences, HRV indices derived from the Apple Watch RR interval series were able to reflect changes induced by a mild mental stress, showing a significant decrease of HF power as well as RMSSD in stress with respect to relax, suggesting the potential use of HRV measurements derived from Apple Watch for stress monitoring.
心率变异性(HRV)分析是一种广泛用于评估自主神经系统状态的非侵入性工具。测量心率的可穿戴设备市场呈指数级增长,其在医疗保健和健康应用方面的潜力也越来越大。然而,这些设备的验证仍然缺乏。特别是,这项工作旨在从设备提供的 RR 间隔序列方面验证 Apple Watch 的 HRV,包括时域(HRM(平均心率)、SDNN、RMSSD 和 pNN50)和频域(低频和高频功率、LF 和 HF)。为此,使用了一个由 20 名健康志愿者组成的数据库,他们接受了放松和轻度认知压力。首先,使用 Bland-Altman 图和可靠性和一致性系数,使用 Polar H7 提供的 RR 间隔序列来验证 Apple Watch 提供的 RR 间隔序列。然后,比较了从这两个 RR 间隔序列中导出的 HRV 参数,并研究了它们识别自主神经系统(ANS)对轻度认知应激反应的能力。Apple Watch 的测量结果具有非常好的可靠性和一致性(>0.9)。Apple Watch 提供的 RR 间隔序列由于缺少 RR 间隔值而存在间隙(平均每个记录有 5 个间隙,每个间隙持续 6.5 秒)。时域 HRV 指数不受间隙的影响。然而,它们会导致 LF 和 HF 功率显著下降。尽管存在这些差异,但 Apple Watch RR 间隔序列导出的 HRV 指数能够反映轻度精神压力引起的变化,在压力下 HF 功率和 RMSSD 显著降低,提示 HRV 测量可用于 Apple Watch 压力监测。