Vision‐based game design and assessment for physical exercise in a robot‐assisted rehabilitation system
Engagement is a key factor in gaming. Especially, in gamification applications, users’ engagement levels have to be assessed in order to determine the usability of the developed games. The authors first present computer vision‐based game design for physical exercise. All games are played with gestur...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-02-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2017.0122 |
| _version_ | 1797684353719861248 |
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| author | Huseyin Erdogan Yunus Palaska Engin Masazade Duygun Erol Barkana Hazım Kemal Ekenel |
| author_facet | Huseyin Erdogan Yunus Palaska Engin Masazade Duygun Erol Barkana Hazım Kemal Ekenel |
| author_sort | Huseyin Erdogan |
| collection | DOAJ |
| description | Engagement is a key factor in gaming. Especially, in gamification applications, users’ engagement levels have to be assessed in order to determine the usability of the developed games. The authors first present computer vision‐based game design for physical exercise. All games are played with gesture controls. The authors conduct user studies in order to evaluate the perception of the games using a game engagement questionnaire. Participants state that the games are interesting and they want to play them again. Next, as a use case, the authors integrate one of these games into a robot‐assisted rehabilitation system. The authors perform additional user studies by employing self‐assessment manikin to assess the difficulty levels that can range from boredom to excitement. The authors observe that with the increasing difficulty level, users’ arousal increases. Additionally, the authors perform psychophysiological signal analysis of the participants during the execution of the game under two distinctive difficulty levels. The authors derive features from the signals obtained from blood volume pulse (BVP), skin conductance, and skin temperature sensors. As a result of analysis of variance and sequential forward selection, the authors find that changes in the temperature and frequency content of BVP provide useful information to estimate the players’ engagement. |
| first_indexed | 2024-03-12T00:28:29Z |
| format | Article |
| id | doaj.art-b98a015489454de9b8e535024be8e27e |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:28:29Z |
| publishDate | 2018-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-b98a015489454de9b8e535024be8e27e2023-09-15T10:31:30ZengWileyIET Computer Vision1751-96321751-96402018-02-01121596810.1049/iet-cvi.2017.0122Vision‐based game design and assessment for physical exercise in a robot‐assisted rehabilitation systemHuseyin Erdogan0Yunus Palaska1Engin Masazade2Duygun Erol Barkana3Hazım Kemal Ekenel4Informatics InstituteMiddle East Technical UniversityAnkara06800TurkeyDepartment of Electrical and Electronics EngineeringYeditepe UniversityIstanbul34755TurkeyDepartment of Electrical and Electronics EngineeringYeditepe UniversityIstanbul34755TurkeyDepartment of Electrical and Electronics EngineeringYeditepe UniversityIstanbul34755TurkeyDepartment of Computer EngineeringIstanbul Technical UniversityIstanbul34469TurkeyEngagement is a key factor in gaming. Especially, in gamification applications, users’ engagement levels have to be assessed in order to determine the usability of the developed games. The authors first present computer vision‐based game design for physical exercise. All games are played with gesture controls. The authors conduct user studies in order to evaluate the perception of the games using a game engagement questionnaire. Participants state that the games are interesting and they want to play them again. Next, as a use case, the authors integrate one of these games into a robot‐assisted rehabilitation system. The authors perform additional user studies by employing self‐assessment manikin to assess the difficulty levels that can range from boredom to excitement. The authors observe that with the increasing difficulty level, users’ arousal increases. Additionally, the authors perform psychophysiological signal analysis of the participants during the execution of the game under two distinctive difficulty levels. The authors derive features from the signals obtained from blood volume pulse (BVP), skin conductance, and skin temperature sensors. As a result of analysis of variance and sequential forward selection, the authors find that changes in the temperature and frequency content of BVP provide useful information to estimate the players’ engagement.https://doi.org/10.1049/iet-cvi.2017.0122sequential forward selectionskin temperature sensorsskin conductanceBVPblood volume pulseself-assessment manikin |
| spellingShingle | Huseyin Erdogan Yunus Palaska Engin Masazade Duygun Erol Barkana Hazım Kemal Ekenel Vision‐based game design and assessment for physical exercise in a robot‐assisted rehabilitation system IET Computer Vision sequential forward selection skin temperature sensors skin conductance BVP blood volume pulse self-assessment manikin |
| title | Vision‐based game design and assessment for physical exercise in a robot‐assisted rehabilitation system |
| title_full | Vision‐based game design and assessment for physical exercise in a robot‐assisted rehabilitation system |
| title_fullStr | Vision‐based game design and assessment for physical exercise in a robot‐assisted rehabilitation system |
| title_full_unstemmed | Vision‐based game design and assessment for physical exercise in a robot‐assisted rehabilitation system |
| title_short | Vision‐based game design and assessment for physical exercise in a robot‐assisted rehabilitation system |
| title_sort | vision based game design and assessment for physical exercise in a robot assisted rehabilitation system |
| topic | sequential forward selection skin temperature sensors skin conductance BVP blood volume pulse self-assessment manikin |
| url | https://doi.org/10.1049/iet-cvi.2017.0122 |
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