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A practical multi-sensor activity recognition system for home-based care
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DOI：10.1016/j.dss.2014.06.005.png)
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摘要
En 中文
To cope with the increasing number of aging population, a type of care which can help prevent or postpone entry into institutional care is preferable. Activity recognition can be used for home-based care in order to help elderly people to remain at home as long as possible. This paper proposes a practical multi-sensor activity recognition system for home-based care utilizing on-body sensors. Seven types of sensors are investigated on their contributions toward activity classification. We collected a real data set through the experiments participated by a group of elderly people. Seven classification models are developed to explore contribution of each sensor. We conduct a comparison study of four feature selection techniques using the developed models and the collected data. The experimental results show our proposed system is superior to previous works achieving 97% accuracy. The study also demonstrates how the developed activity recognition model can be applied to promote a home-based care and enhance decision support system in health care. (C) 2014 Elsevier B.V. All rights reserved.
Keyword:
Multi-sensor activity recognition
Home-based care
Feature selection
Classification
Mutual information
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3.8K
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1.5W
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