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http://dx.doi.org/10.7236/IJASC.2022.11.4.57

The Development of Exercise Accuracy Measurement Algorithm Supporting Personal Training's Exercise Amount Improvement  

Oh, Seung-Taek (Smart Natural Space Research Center, Kongju National University)
Kim, Hyeong-Seok (Department of Computer Science & Engineering, Kongju National University)
Lim, Jae-Hyun (Department of Computer Science & Engineering, Kongju National University)
Publication Information
International journal of advanced smart convergence / v.11, no.4, 2022 , pp. 57-67 More about this Journal
Abstract
The demand for personal training (PT), through which high exercise effects can be achieved within short-term, has recently increased. PT can achieve an exercise amount improvement effect, only if accurate postures are maintained upon performing PT, and exercise with inaccurate postures can cause injuries. However, research is insufficient on exercise amount comparisons and judging exercise accuracy on PT. This study proposes an exercise accuracy measurement algorithm and compares differences in exercise amounts according to exercise postures through experiments using a respiratory gas analyzer. The exercise accuracy measurement algorithm acquires Euler anglesfrom major body parts operated upon exercise through a motion device, based on which the joint angles are calculated. By comparing the calculated joint angles with each reference angle in each exercise step, the status of exercise accuracy is judged. The calculated results of exercise accuracy on squats, lunges, and push-ups showed 0.02% difference in comparison with actually measured results through a goniometer. As a result of the exercise amount comparison experiment according to accurate posture through a respiratory gas analyzer, the exercise amount was higher by 45.19% on average in accurate postures. Through this, it was confirmed that maintaining accurate postures contributes to exercise amount improvement.
Keywords
Exercise Accuracy; Personal Training; Exercise Amount; measurement Algorithm;
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Times Cited By KSCI : 3  (Citation Analysis)
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