Adaptive regulation of assistance 'as needed' in robot-assisted motor skill learning and neuro-rehabilitation

We propose a general adaptive procedure to select the appropriate degree of assistance based on a Bayesian mechanism used to estimate psychophysical thresholds. This technique does not need an accurate model of learning and recovery processes. This procedure is validated in the context of a motor sk...

Full description

Saved in:
Bibliographic Details
Published in2011 IEEE International Conference on Rehabilitation Robotics Vol. 2011; pp. 1 - 6
Main Authors Squeri, V., Basteris, A., Sanguineti, V.
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 2011
Subjects
Adaptation models
Bayes Theorem
Bayesian methods
guidance
Humans
Learning - physiology
Models, Theoretical
motor skill learning
Motor Skills - physiology
Noise
Process control
robot-therapy
Robotics - methods
Robots
Robustness
shaping
Training
Online AccessGet full text

Cover

More Information
Summary:We propose a general adaptive procedure to select the appropriate degree of assistance based on a Bayesian mechanism used to estimate psychophysical thresholds. This technique does not need an accurate model of learning and recovery processes. This procedure is validated in the context of a motor skill learning problem (control of a virtual object), in which the controller is used to gradually increase task difficulty as learning proceeds. These automatic adjustments of task difficulty or the degree of assistance can be used to promote not only motor skill learning but also neuromotor recovery.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISBN:1424498635
9781424498635
ISSN:1945-7898
1945-7901
DOI:10.1109/ICORR.2011.5975375