ETRI-Knowledge Sharing Plaform



논문 검색
구분 SCI
연도 ~ 키워드


학술대회 The Gesture Recognition Technology based on IMU Sensor for Personal Active Spinning
Cited 14 time in scopus Download 3 time Share share facebook twitter linkedin kakaostory
강미선, 강현우, 이철효, 문기영
International Conference on Advanced Communications Technology (ICACT) 2018, pp.546-552
17ZD1100, 대경권 지역산업연계 IT융합기술개발 및 산업계 지원사업, 문기영
Recently, as the desire for sustaining good health, has increased, spinning exercise to increase the exercise effect in a short time is getting the spotlight. In this paper, we developed a gesture recognition technology which enables busy persons to enjoy spinning exercise at any time and at any place they want using easy to carry wearable device. The proposed scheme provides a training system which collects real time data from an IMU (Inertial Measurement Unit) sensor attached to wrist and head of sports participants and analyzes the accuracy of spinning exercise using the decision tree-based classification scheme. For the validation of the spinning gesture recognition technology, we analyzed the performance of the proposal algorithm by applying it to the interactive gaming content platform. The results shows that the proposed the proposed technology can help users to enjoy correct spinning exercise program.
KSP 제안 키워드
Classification scheme, Decision Tree(DT), Exercise program, IMU sensor, Inertial Measurement Unit(IMU), Real-time data, Short time, Training system, Tree-based, Wearable device, gesture recognition technology