DocumentCode :
414343
Title :
Robotic therapy for persons with disabilities using Hidden Markov Model based skill learning
Author :
Yu, Wentao ; Dubey, Rajiv ; Pernalete, Norali
Author_Institution :
Rehabilitation Robotics Lab., Univ. of South Florida, Tampa, FL, USA
Volume :
2
fYear :
2004
fDate :
April 26-May 1, 2004
Firstpage :
2074
Abstract :
This paper describes the Hidden Markov Model (HMM) based skill learning and its application in a motion therapy system using a haptic interface. A relatively complex task, requiring motion along a labyrinth is used. A normal subject executes this task for a number of times and the best trajectory is selected as the learned skill, which is considered as a virtual therapist who can train persons with disabilities to complete the task. Two persons with disabilities on upper limb (cerebral palsy) were trained using the virtual therapist. The performance before and after therapy training, including the smoothness of the trajectory, distance ratio, time taken, tremor and impact forces are presented in this paper. This labyrinth can be used as a physical therapy for upper limb coordination, tremor reduction and motion control capabilities.
Keywords :
haptic interfaces; hidden Markov models; learning (artificial intelligence); medical robotics; patient rehabilitation; cerebral palsy; disabled persons; distance ratio; haptic interface; hidden Markov model; impact forces; labyrinth; motion control; motion therapy system; robotic therapy; skill learning; therapy training; tremor forces; upper limb coordination; virtual therapist; Educational robots; Hidden Markov models; Humans; Laboratories; Medical treatment; Rehabilitation robotics; Robot kinematics; Robotic assembly; Stochastic processes; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on
ISSN :
1050-4729
Print_ISBN :
0-7803-8232-3
Type :
conf
DOI :
10.1109/ROBOT.2004.1308129
Filename :
1308129
Link To Document :
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