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利用可穿戴传感器对老年人日常活动进行分类。

Classification of Daily Activities for the Elderly Using Wearable Sensors.

机构信息

Division of Applied Science and Technology, Marshall University, Huntington, WV, USA.

Department of Physical Education, College of Culture Convergence, Jeonju University, Jeonju, Republic of Korea.

出版信息

J Healthc Eng. 2017;2017:8934816. doi: 10.1155/2017/8934816. Epub 2017 Nov 26.

Abstract

Monitoring of activities of daily living (ADL) using wearable sensors can provide an objective indication of the activity levels or restrictions experienced by patients or elderly. The current study presented a two-sensor ADL classification method designed and tested specifically with elderly subjects. Ten healthy elderly were involved in a laboratory testing with 6 types of daily activities. Two inertial measurement units were attached to the thigh and the trunk of each subject. The results indicated an overall rate of misdetection being 2.8%. The findings of the current study can be used as the first step towards a more comprehensive activity monitoring technology specifically designed for the aging population.

摘要

使用可穿戴传感器监测日常生活活动 (ADL) 可以提供患者或老年人所经历的活动水平或限制的客观指示。本研究提出了一种专门为老年受试者设计和测试的双传感器 ADL 分类方法。十名健康的老年人参与了实验室测试,涉及六种日常活动。两个惯性测量单元分别附着在每个受试者的大腿和躯干上。结果表明总体误检率为 2.8%。本研究的结果可以作为迈向更全面的专为老年人口设计的活动监测技术的第一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab08/5727831/230919e750cf/JHE2017-8934816.001.jpg

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