HRVEST:在随机临床试验中使用可穿戴智能技术测量生理压力变量的新型数据解决方案

Jeffrey N. Gerwin, Gustavo de Oliveira Almeida, Michael W. Boyce, Melissa Joseph, Ambrose H. Wong, Winslow Burleson, Leigh V. Evans
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摘要

本研究的目的是解决在一项临床试验中使用可穿戴技术测量心率变异性(HRV)作为 COVID-19 大流行期间紧急医疗服务提供者生理压力标志物所面临的后勤和数据挑战。在使用这些可穿戴智能服装时,面临着两方面的困境:(1)产生的原始生理数据量巨大,而且记录的格式不易被标准分析软件移植;(2)相应的数据分析通常需要专用软件。我们的团队反复开发了一种名为 HRVEST 的新型算法,它能成功处理可穿戴智能服装产生的大量原始生理数据,并满足心率变异分析的特定需求。HRVEST 是一种噪声过滤和数据处理算法,可精确测量急诊科(ED)临床医生的心率变异性(HRV)。HRVEST 可在 15 分钟内自动处理从 413 次心电图(ECG)记录中获得的生物计量数据。此外,在整个研究过程中,我们还发现了使用这些技术所面临的独特挑战,并提出了解决方案,以促进未来在更广泛的环境中使用这些技术。有了 HRVEST,使用可穿戴智能服装来长时间监测心率变异在未来的研究中将变得更加合理可行。我们还看到了实时反馈的潜力,可以预防性地减轻急诊医生的压力,比如告知最佳休息时间或短期冥想以降低心率。这可以改善情绪,进而改善临床决策和患者治疗效果。
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HRVEST: a novel data solution for using wearable smart technology to measure physiologic stress variables during a randomized clinical trial
The purpose of this study was to address the logistical and data challenges of using wearable technologies in the context of a clinical trial to measure heart rate variability (HRV) as a marker of physiologic stress in emergency healthcare providers during the COVID-19 pandemic. When using these wearable smart garments, the dilemma is two-fold: (1) the volume of raw physiological data produced is enormous and is recorded in formats not easily portable in standard analytic software, and (2) the commensurate data analysis often requires proprietary software. Our team iteratively developed a novel algorithm called HRVEST that can successfully process enormous volumes of physiologic raw data generated by wearable smart garments and meet the specific needs of HRV analyses. HRVEST is a noise-filtering and data-processing algorithm that allows the precise measurements of heart rate variability (HRV) of clinicians working in an Emergency Department (ED). HRVEST automatically processed the biometric data derived from 413 electrocardiogram (ECG) recordings in just over 15 min. Furthermore, throughout this study, we identified unique challenges of working with these technologies and proposed solutions that may facilitate future use in broader contexts. With HRVEST, using wearable smart garments to monitor HRV over long periods of time becomes logistically and feasibly viable for future studies. We also see the potential for real-time feedback to prophylactically reduce emergency physician stress, like informing optimal break-taking or short meditation sessions to lower heart rate. This could improve emotional wellbeing and, subsequently, clinical decision-making and patient outcomes.
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