Research Article
Design of an Antagonistic Exercise Support System Using a Depth Image Sensor
@INPROCEEDINGS{10.4108/eai.16-5-2016.2263317, author={Toshiya Watanabe and Kazuki Kamata and Sheik Hasan and Susumu Shibusawa and Masaru Kamada and Tatsuhiro Yonekura and Minoru Yamada}, title={Design of an Antagonistic Exercise Support System Using a Depth Image Sensor}, proceedings={10th EAI International Conference on Pervasive Computing Technologies for Healthcare}, publisher={ACM}, proceedings_a={PERVASIVEHEALTH}, year={2016}, month={6}, keywords={antagonistic exercise depth sensor joint distance exercise support system design rhythm games preventive care}, doi={10.4108/eai.16-5-2016.2263317} }
- Toshiya Watanabe
Kazuki Kamata
Sheik Hasan
Susumu Shibusawa
Masaru Kamada
Tatsuhiro Yonekura
Minoru Yamada
Year: 2016
Design of an Antagonistic Exercise Support System Using a Depth Image Sensor
PERVASIVEHEALTH
EAI
DOI: 10.4108/eai.16-5-2016.2263317
Abstract
Dementia is one of the main reasons for elderly people becoming dependent on care. In addition to lifestyle improvements, it is thought that cognitive function exercises and motor function exercises are also effective for the prevention of dementia. Antagonistic exercise, which involves performing different movements with the upper and lower limbs on the left and right sides, is a form of exercise that uses cognitive and motor functions at the same time. Preventive care specialists that can lead this sort of exercise are few in number compared with elderly people, and are under a heavy burden. Therefore, there is a need for an exercise support system that can reduce the burden on specialists. On the other hand, the Kinect has become popular as a low-cost device that can acquire human actions. The Kinect uses a depth image sensor to obtain precise measurements of human joint movements, and can thus be used to recognize antagonistic exercises. In this study we designed and implemented an antagonistic exercise support system using a Kinect. To recognize exercises, data representing the positions of the person’s joints as acquired from the depth sensor is used. This system uses audiovisual displays to explain to users how to perform the exercises, and displays model images to promote the exercises. We have also prepared four types of rhythm game where people can perform exercises in time with music. We performed recognition accuracy tests with young and elderly test subjects.