Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : June 01, 2022 - June 04, 2022
In recent years, people tend to be more health-conscious. Due to this, strength training has been attracting attention as an effective way to maintain and improve muscle strength which affects QoL. In this study, we developed a resistance training device for multi kinds of muscle trainings, which is able to set an arbitrary load by motor control. To effectively improve athletic performance with a small risk of injury, the training variables including load, repetitions, and intervals should be determined appropriately based on muscle characteristics such as maximum muscle force. Therefore, we examined the method to estimate 1RM easily based on the load-velocity profile (LVP) to evaluate muscle characteristics such as maximum muscle force. The experimental results show that 1RM (1 Repetition Maximum) can be estimated with high accuracy using several LVP datasets. Finally, we propose a protocol to evaluate muscle characteristics non-invasively based on the experimental results.
