A practical multi-sensor activity recognition system for home-based care

作者:

Highlights:

• Propose a practical multi-sensor activity recognition system for home-based care.

• Collect a real data set from a group of elderly people using seven on-body sensors.

• Conduct investigation on the effect of different sensor in human activity classification.

• Evaluate different feature selection and classification techniques for activity recognition.

摘要

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.

论文关键词:Multi-sensor activity recognition,Home-based care,Feature selection,Classification,Mutual information

论文评审过程:Received 6 November 2013, Revised 16 April 2014, Accepted 7 June 2014, Available online 26 June 2014.

论文官网地址:https://doi.org/10.1016/j.dss.2014.06.005