ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술대회 Movement Detection and Analysis of Resistance Exercises for Smart Fitness Platform
Cited 2 time in scopus Download 3 time Share share facebook twitter linkedin kakaostory
저자
이철효
발행일
201707
출처
International Conference on Ubiquitous and Future Networks (ICUFN) 2017, pp.1-6
DOI
https://dx.doi.org/10.1109/ICUFN.2017.7993818
협약과제
16CD1300, 운동 및 생체 정보 융합을 통한 스마트 피트니스 서비스 플랫폼 기술 개발, 이철효
초록
According to the rapid advance of healthcare services, fitness exercise is one of the attracting fields for the usage of wearable devices. In order to apply the wearable devices to fitness services, this paper proposes a method of detecting and analyzing the periodic movement of the resistance exercises such as squat, arm curl and triceps extension. Firstly, the slope tracing for peak detection algorithm is proposed to detect clearly the peak value of the noisy acceleration signals. Secondly, seven exercise features are defined for the exercise evaluations, which are measured according to the experimental executions. Finally, those results are analyzed and their conclusive remarks are presented.
키워드
Exercise features, Flexion and extension, Resistance exercise, Slope tracing and peak detection, Smart ftness pllatform
KSP 제안 키워드
Acceleration Signals, Detection and analysis, Exercise features, Flexion and extension, Healthcare Services, Movement Detection, Peak Value, Peak detection algorithm, Slope tracing and peak detection, Smart ftness pllatform, Wearable device