Classification of Daily Activities for the Elderly Using Wearable Sensors

Author:

Liu Jian1,Sohn Jeehoon2,Kim Sukwon3ORCID

Affiliation:

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

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

3. Department of Physical Education, College of Education, Chonbuk National University, Jeonju, Republic of Korea

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.

Publisher

Hindawi Limited

Subject

Health Informatics,Biomedical Engineering,Surgery,Biotechnology

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