In order to measure muscle activity, EMG sensors have been widely used. However, there is a need for musculoskeletal software for deep understanding of the human musculoskeletal system and for analyzing the mechanism of internal muscles. The process is used to analyze the human motion itself, to change the motion when the robot is equipped, and to verify the actual effects of the robot during the rehabilitation process. In addition, through comparison with Electromyography, the reliability of current algorithm techniques and derive kinetic implications of related parameters are studied.
Introduction
Goal
Using an algorithm (Computed muscle control, Static Optimization) for estimating human muscle activity, kinematic interpretation of human motion is performed at the muscle level, and quantitative results can be derived as to how robot and human collaborations affect human beings in detail.
Using an algorithm (Computed muscle control, Static Optimization) for estimating human muscle activity, human motion is analyzed.
The process is used to analyze the human motion itself, to change the motion when the robot is equipped, and to verify the actual effects of the robot during the rehabilitation process. Through comparison with Electromyography, the reliability of current algorithm techniques and derive kinetic implications of related parameters are studied.

In this way, kinematic interpretation of human motion is performed at the muscle level, and quantitative results can be derived as to how robot and human collaborations affect human beings in detail.
Outcomes
1.International conference: Verification of Computed Muscle Control and Static Optimization for Isokinetic, Isometric and Isotonic Exercise of Upper Limb, Wiha Choi and Sehoon Oh, IEEE Engineering in Medicine and Biology Society (EMBC) 2018, 2018.
Funding
This work was supported by,
1.the Ministry of Trade, Industry and Energy of Korea(MOTIE) (NO. 10080547)
2.the National Research Foundation of Korea(NRF) grant(NRF-2016R1A2B4016163)
participants
Wiha Choi
