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Updated: Feb 15, 2026

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
Published on: December 11, 2015
Classification of Daily Activities for the Elderly Using Wearable Sensors
Jian Liu1, Jeehoon Sohn2, Sukwon Kim3
1Division of Applied Science and Technology, Marshall University, Huntington, WV, USA.
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.
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