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Conference Paper Movement Detection and Analysis of Resistance Exercises for Smart Fitness Platform
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Authors
Cheolhyo Lee
Issue Date
2017-07
Citation
International Conference on Ubiquitous and Future Networks (ICUFN) 2017, pp.1-6
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICUFN.2017.7993818
Project Code
16CD1300, The Development of Smart Fitness Service Platform Technology using Multi-sensing Information based on Motion and Bio-signal , Lee Cheolhyo
Abstract
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.
KSP Keywords
Acceleration Signals, Detection and analysis, Exercise features, Healthcare Services, Movement Detection, Peak Value, Peak detection algorithm, Wearable device, periodic movement