Movement detection and analysis of resistance exercises for smart fitness platform
Cheolhyo Lee · 2017
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.