Publication:
Game-based Enhancement for Rehabilitation Based on Action Recognition Using Kinect

dc.contributor.authorChanat Sinpithakkulen_US
dc.contributor.authorWorapan Kusakunniranen_US
dc.contributor.authorSunee Bovonsunthonchaien_US
dc.contributor.authorPeemongkon Wattananonen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherFaculty of Information and Communication Technologyen_US
dc.date.accessioned2020-01-27T08:21:12Z
dc.date.available2020-01-27T08:21:12Z
dc.date.issued2019-02-22en_US
dc.description.abstract© 2018 IEEE. The physical rehabilitation is a way to improve physical abilities of patients. One of the main problems is patients can get bored from repeated rehab-activities which must be worked out for a long period or even for a lifetime. This can decrease patients' motivations to do the rehabilitation. In addition, game is considered as an entertainment media that is able to use to motivate players to engage in particular activities by giving rewards in exchange. Therefore, this paper proposes the digital game-based enhancement for the Cerebral Palsy (CP) rehabilitation. The CP is the congenital disease caused by the damage on a part of the brain that controls the movement functionality. In this study, the patient must perform specific rehab-actions to control the games. Four games are developed for four rehab-actions including shoulder flexion, shoulder abduction, shoulder horizontal abduction and elbow flexion/extension. They are parts of fundamental movements needed for the Activities of Daily Living (ADL). In each game, the patient must perform the requested rehab-action naturally without carrying any controller. The Kinect is used to track the movements from the patient. Then, the rule-based system is trained and used to detect the correct rehab-action for controlling the game. Then, the experiment is performed to see possibility of using the game-based system for the rehabilitation enhancement. It shows the promising performance in terms of action recognition accuracy that is flexible enough for the patient, the play records, and the expert review.en_US
dc.identifier.citationIEEE Region 10 Annual International Conference, Proceedings/TENCON. Vol.2018-October, (2019), 303-308en_US
dc.identifier.doi10.1109/TENCON.2018.8650226en_US
dc.identifier.issn21593450en_US
dc.identifier.issn21593442en_US
dc.identifier.other2-s2.0-85063195234en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/50649
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85063195234&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titleGame-based Enhancement for Rehabilitation Based on Action Recognition Using Kinecten_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85063195234&origin=inwarden_US

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