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http://dx.doi.org/10.7736/KSPE.2013.30.6.650

Torque Estimation of the Human Elbow Joint using the MVS (Muscle Volume Sensor)  

Lee, Hee Don (Department of Mechanical Engineering, Hanyang Univ.)
Lim, Dong Hwan (Department of Mechanical Engineering, Hanyang Univ.)
Kim, Wan Soo (Department of Mechanical Engineering, Hanyang Univ.)
Han, Jung Soo (Department of Mechanical System Engineering, Hansung Univ.)
Han, Chang Soo (Department of Mechanical Engineering, Hanyang Univ.)
An, Jae Yong (Department of Pathology and Orthopedics, Cheil General Hospital, Kwandong Univ.)
Publication Information
Journal of the Korean Society for Precision Engineering / v.30, no.6, 2013 , pp. 650-657 More about this Journal
Abstract
This study uses a muscle activation sensor and elbow joint model to develop an estimation algorithm for human elbow joint torque for use in a human-robot interface. A modular-type MVS (Muscle Volume Sensor) and calibration algorithm are developed to measure the muscle activation signal, which is represented through the normalization of the calibrated signal of the MVS. A Hill-type model is applied to the muscle activation signal and the kinematic model of the muscle can be used to estimate the joint torques. Experiments were performed to evaluate the performance of the proposed algorithm by isotonic contraction motion using the KIN-COM$^{(R)}$ equipment at 5, 10, and 15Nm. The algorithm and its feasibility for use as a human-robot interface are verified by comparing the joint load condition and the torque estimated by the algorithm.
Keywords
Muscle Volume Sensor; Human Intent Estimation; Human Joint Torque Estimation; Muscle Activation Signal; Human Muscle Model;
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Times Cited By KSCI : 3  (Citation Analysis)
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