Wearable sensor-based activity recognition for housekeeping task

Kai-Chun Liu, Chien-Yi Yen, Li-Han Chang, Chia-Yeh Hsieh, Chia-Tai Chan
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引用次数: 19

Abstract

In order to improve healthcare services and support clinical professionals, it is important to develop the unobstructive and automatic ADLs monitoring system for healthcare applications. Currently, various works have been developed for the monitoring of daily activities, such as ambulation, kitchen task, food and fluid intake, dressing, and medication intake while only few works paid attention to the housekeeping task. Housekeeping activity is a complex task, generally important for the several clinical assessment tools. In this work, we design and develop a wearable sensor-based activity recognition system recognize housekeeping tasks and classify the activity level. The proposed system achieves 90.67% accuracy for housekeeping tasks recognition, and 94.35% accuracy for activity level classification, respectively. The results of the experiment demonstrate that the system is reliable and fulfills the requirements of the unobstructive, objective, and long-term monitoring system.
基于可穿戴传感器的家务活动识别
为了改善医疗服务和支持临床专业人员,开发无障碍、自动的ADLs监测系统是非常重要的。目前已经开发了各种日常活动的监测作品,如行走、厨房任务、食物和液体摄入、穿衣、药物摄入等,而很少有作品关注家政任务。管家活动是一项复杂的任务,通常对几种临床评估工具很重要。在这项工作中,我们设计并开发了一个基于可穿戴传感器的活动识别系统,该系统可以识别家务任务并对活动级别进行分类。本文提出的系统对内务任务的识别准确率为90.67%,对活动级别的分类准确率为94.35%。实验结果表明,该系统运行可靠,满足了无障碍、客观、长期监测系统的要求。
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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