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为人们提供一个用户友好的可穿戴平台,用于对重要生理参数进行非侵入式监测。

Empowering People with a User-Friendly Wearable Platform for Unobtrusive Monitoring of Vital Physiological Parameters.

机构信息

Applied Electronics Laboratory, Department of Electrical and Computer Engineering, University of Patras, 26504 Patras, Greece.

Industrial Systems Institute, ATHENA RC, 26504 Patras, Greece.

出版信息

Sensors (Basel). 2022 Jul 13;22(14):5226. doi: 10.3390/s22145226.

Abstract

Elderly people feel vulnerable especially after they are dismissed from health care facilities and return home. The purpose of this work was to alleviate this sense of vulnerability and empower these people by giving them the opportunity to unobtrusively record their vital physiological parameters. Bearing in mind all the parameters involved, we developed a user-friendly wrist-wearable device combined with a web-based application, to adequately address this need. The proposed compilation obtains the photoplethysmogram (PPG) from the subject's wrist and simultaneously extracts, in real time, the physiological parameters of heart rate (HR), blood oxygen saturation (SpO) and respiratory rate (RR), based on algorithms embedded on the wearable device. The described process is conducted solely within the device, favoring the optimal use of the available resources. The aggregated data are transmitted via Wi-Fi to a cloud environment and stored in a database. A corresponding web-based application serves as a visualization and analytics tool, allowing the individuals to catch a glimpse of their physiological parameters on a screen and share their digital information with health professionals who can perform further processing and obtain valuable health information.

摘要

老年人在离开医疗保健机构并返回家中后会感到脆弱。这项工作的目的是通过让他们有机会不引人注目地记录自己重要的生理参数来减轻这种脆弱感并赋予他们权力。考虑到所有涉及的参数,我们开发了一款用户友好的可穿戴腕带设备,并结合了基于网络的应用程序,以充分满足这一需求。该提议的编译从主体的手腕获取光体积描记图(PPG),并基于可穿戴设备上嵌入的算法实时提取心率(HR)、血氧饱和度(SpO)和呼吸率(RR)的生理参数。描述的过程仅在设备内进行,有利于最佳利用可用资源。聚合数据通过 Wi-Fi 传输到云环境并存储在数据库中。相应的基于网络的应用程序用作可视化和分析工具,允许个人在屏幕上查看自己的生理参数,并与可以执行进一步处理和获取有价值健康信息的健康专业人员共享他们的数字信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c2/9317673/113310498757/sensors-22-05226-g001.jpg

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