Recognition of occupational therapy exercises for cerebral palsy
Author
Ongun, Mehmet Faruk
Advisor
Güdükbay, Uğur
Date
2018-09Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
Depth camera-based virtual rehabilitation systems are gaining traction in occupational
therapy for approaching patients with cerebral palsy. When developing
such a system, a domain speci c exercise recognition method is vital. In order
to design a successful gesture recognition solution for this speci c purpose, some
obstacles needs to be overcome, namely; detection of gestures that are not related
to the de ned exercise set and recognition of incorrect exercises that are
performed by the patients to compensate for their lack of ability. A combination
of solutions, that are based on hidden Markov models, targeting aforementioned
obstacles are proposed and elaborated on. The proposed solution works for upper
extremity functional exercises and critical compensation mistakes together with
restrictions for classifying these mistakes are determined with the help of occupational
therapists. Afterwards, we rst aim to eliminate the unde ned gestures by
designing two models that produce adaptive threshold values. Then, we utilize
speci c negative models based on an approach named feature thresholding and
train them speci cally for each exercise to distinguish the compensation mistakes.
We conducted various tests using our method in a laboratory environment under
the supervision of occupational therapists and presented the results of our
proposed approach.
Keywords
Gesture RecognitionCerebral Palsy
Occupational Therapy
Hidden Markov Model
Exercise Recognition
Depth Camera
Virtual Rehabilitation