Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/17531
Title: Feedback error learning at the muscle level: A unified model of human motor adaptation to stable and unstable dynamics
Authors: TEE KENG PENG
Keywords: impedance; model; human; arm; muscle; adaptation
Issue Date: 27-Nov-2003
Source: TEE KENG PENG (2003-11-27). Feedback error learning at the muscle level: A unified model of human motor adaptation to stable and unstable dynamics. ScholarBank@NUS Repository.
Abstract: This thesis presents a computational model of human motor adaptation to novel dynamics. It is shown that feedback error learning at the muscle level, in addition to a deactivation strategy to minimize agonist-antagonist cocontraction, can acquire an inverse dynamics model compensating for reproducible dynamics and anisotropic impedance to counteract irreproducible dynamics. This ensures the learning of appropriate motor commands to compensate for stable and unstable novel dynamics. The motion trajectories, evolution of muscle activity, and endpoint impedance resulting from full dynamics simulation are consistent with all available experimental results (Burdet et al 2001A, Franklin et al 2003A, Franklin et al 2003B, Osu et al 2003), indicating that the model is plausible. The sensitivity to model parameters and the predicted results in various novel dynamics are also examined.
URI: http://scholarbank.nus.edu.sg/handle/10635/17531
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
TeeKengPeng.pdf2.11 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

213
checked on Dec 11, 2017

Download(s)

212
checked on Dec 11, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.