arXiv 2402.094522024-02-03eess.SPcs.LGcs.SYeess.SY

家庭医疗保健中基于真实世界WiFi的患者活动监测的数据分布动态

Data Distribution Dynamics in Real-World WiFi-Based Patient Activity Monitoring for Home Healthcare

University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）；University of Texas Health Science Center at San Antonio（德克萨斯大学圣安东尼奥健康科学中心）；University of Texas at San Antonio（德克萨斯大学圣安东尼奥分校）；Florida State University（佛罗里达州立大学）；Bosch Research and Technology Center（博世研究技术中心）

Mahathir Monjur, Jia Liu, Jingye Xu, Yuntong Zhang, Xiaomeng Wang, Chengdong Li, Hyejin Park, Wei Wang, Karl Shieh, Sirajum Munir, Jing Wang, Lixin Song, Shahriar Nirjon

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AI总结：

本文研究了基于WiFi的家庭日常活动监测，分析了真实场景中环境、受试者及系统变量对识别准确性的影响，旨在指导开发稳健且具备上下文感知能力的WiFi感知系统，以弥合学术研究与实际应用的差距。

摘要：

本文探讨了在家庭医疗保健场景下，利用WiFi信号对日常活动进行真实世界监测的应用。尽管基于WiFi的活动识别在实验室环境中表现出良好前景，但在真实场景中，由于环境、受试者和系统配置变量的影响，其准确性和适应性面临挑战。研究在多种环境中部署了系统并分析了数据分布的偏移。其旨在指导开发适用于老年人护理的稳健且具备上下文感知能力的WiFi感知系统。研究结果表明，基于WiFi的活动感知正在发生转变，弥合了学术研究与实际应用之间的差距，通过技术提升生活质量。

英文摘要：

This paper examines the application of WiFi signals for real-world monitoring of daily activities in home healthcare scenarios. While the state-of-the-art of WiFi-based activity recognition is promising in lab environments, challenges arise in real-world settings due to environmental, subject, and system configuration variables, affecting accuracy and adaptability. The research involved deploying systems in various settings and analyzing data shifts. It aims to guide realistic development of robust, context-aware WiFi sensing systems for elderly care. The findings suggest a shift in WiFi-based activity sensing, bridging the gap between academic research and practical applications, enhancing life quality through technology.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。