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Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/17182

Title: Design of an Adaptive System for Upper-limb Stroke Rehabilitation
Authors: Kan, Patricia Wai Ling
Advisor: Mihailidis, Alex
Department: Biomedical Engineering
Keywords: rehabilitation
artificial intelligence
Issue Date: 24-Feb-2009
Abstract: Stroke is the primary cause of adult disability. To support this large population in recovery, robotic technologies are being developed to assist in the delivery of rehabilitation. A partially observable Markov decision process (POMDP) system was designed for a rehabilitation robotic device that guides stroke patients through an upper-limb reaching task. The performance of the POMDP system was evaluated by comparing the decisions made by the POMDP system with those of a human therapist. Overall, the therapist agreed with the POMDP decisions approximately 65% of the time. The therapist thought the POMDP decisions were believable and could envision this system being used in both the clinic and home. The patient would use this system as the primary method of rehabilitation. Limitations of the current system have been identified which require improvement in future research stages. This research has shown that POMDPs have promising potential to facilitate upper extremity rehabilitation.
URI: http://hdl.handle.net/1807/17182
Appears in Collections:Master
Institute of Biomaterials and Biomedical Engineering - Master theses

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