Automate, Illuminate, Predict: A Universal Framework for Integrating Wearable Sensors in Healthcare.

Q1 Computer Science
Digital Biomarkers Pub Date : 2024-08-26 eCollection Date: 2024-01-01 DOI:10.1159/000540492
Megan K O'Brien, Kristen Hohl, Richard L Lieber, Arun Jayaraman
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引用次数: 0

Abstract

Background: Wearable sensors have been heralded as revolutionary tools for healthcare. However, while data are easily acquired from sensors, users still grapple with questions about how sensors can meaningfully inform everyday clinical practice and research.

Summary: We propose a simple, comprehensive framework for utilizing sensor data in healthcare. The framework includes three key processes that are applied together or separately to (1) automate traditional clinical measures, (2) illuminate novel correlates of disease and impairment, and (3) predict current and future outcomes. We demonstrate applications of the Automate-Illuminate-Predict framework using examples from rehabilitation medicine.

Key messages: Automate-Illuminate-Predict provides a universal approach to extract clinically meaningful data from wearable sensors. This framework can be applied across the care continuum to enhance patient care and inform personalized medicine through accessible, noninvasive technology.

自动化、照明、预测:将可穿戴传感器整合到医疗保健领域的通用框架。
背景:可穿戴传感器被誉为医疗保健领域的革命性工具。然而,虽然从传感器上获取数据很容易,但用户仍在为传感器如何为日常临床实践和研究提供有意义的信息而苦恼。摘要:我们提出了一个在医疗保健领域利用传感器数据的简单而全面的框架。该框架包括三个关键过程,它们可一起或单独应用于:(1)传统临床测量的自动化;(2)阐明疾病和损伤的新型相关性;以及(3)预测当前和未来的结果。我们以康复医学为例,展示了自动-启示-预测框架的应用:Automate-Illuminate-Predict 提供了一种通用方法,可从可穿戴传感器中提取有临床意义的数据。该框架可应用于整个护理过程,通过可获取的无创技术加强对患者的护理并为个性化医疗提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Digital Biomarkers
Digital Biomarkers Medicine-Medicine (miscellaneous)
CiteScore
10.60
自引率
0.00%
发文量
12
审稿时长
23 weeks
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