Browsing by Author "Ongun, Mehmet Faruk"

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Open Access
Recognition of occupational therapy exercises and detection of compensation mistakes for cerebral palsy
(Elsevier, 2020) Ongun, Mehmet Faruk; Güdükbay, Uğur; Aksoy, Selim
Depth camera-based virtual rehabilitation systems are gaining attention in occupational therapy for cerebral palsy patients. When developing such a system, domain-specific exercise recognition is vital. To design such a gesture recognition method, some obstacles need to be overcome: detection of gestures not related to the defined exercise set and recognition of incorrect exercises performed by the patients to compensate for their lack of ability. We propose a framework based on hidden Markov models for the recognition of upper extremity functional exercises. We determine critical compensation mistakes together with restrictions for classifying these mistakes with the help of occupational therapists. We first eliminate undefined gestures by evaluating two models that produce adaptive threshold values. Then we utilize specific negative models based on feature thresholding and train them for each exercise to detect compensation mistakes. We perform various tests using our method in a laboratory environment under the supervision of occupational therapists.
Open Access
Recognition of occupational therapy exercises for cerebral palsy
(2018-09) Ongun, Mehmet Faruk
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.