Human elbow motor learning skills of varying loads: Proof of internal model generation using joint stiffness estimation
Author:
Affiliation:
1. Korea Advanced Institute of Science and Technology
2. Incheon National University
Publisher
Japan Society of Mechanical Engineers
Subject
Biomedical Engineering
Link
https://www.jstage.jst.go.jp/article/jbse/16/3/16_21-00088/_pdf
Reference14 articles.
1. Bennett, D. J., et al. "Time-varying stiffness of human elbow joint during cyclic voluntary movement." Experimental Brain Research 88.2 (1992): 433-442.
2. Burdet, Etienne, et al. "The central nervous system stabilizes unstable dynamics by learning optimal impedance." Nature 414.6862 (2001): 446-449.
3. Chang, Handdeut, Sangjoon Jonathan Kim, and Jung Kim. "Development of self-stabilizing manipulator inspired by the musculoskeletal system using the Lyapunov method." IEEE Transactions on Robotics 33.6 (2017): 1425-1437.
4. Chang, Handdeut, Sangjoon J. Kim, and Jung Kim. "Feedforward motion control with a variable stiffness actuator inspired by muscle cross-bridge kinematics." IEEE Transactions on Robotics 35.3 (2019): 747-760.
5. Franklin, David W., et al. "CNS learns stable, accurate, and efficient movements using a simple algorithm." Journal of neuroscience 28.44 (2008): 11165-11173.
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1. Elbow Joint Stiffness Functional Scales Based on Hill’s Muscle Model and Genetic Optimization;Sensors;2023-02-03
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