The future of automated capture of social kinesic signals for psychiatric purposes
This article considers how computer vision can be enlisted for biomedical applications, specifically the measurement, data analytics and treatment of psychiatric disorders. Often, youngsters are too afraid or embarrassed to disclose their emotional and mental problems to human therapists. An AI syst...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-08-01
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| Series: | Frontiers in Computer Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcomp.2023.1168712/full |
| _version_ | 1797756428526551040 |
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| author | Judee K. Burgoon Aaron C. Elkins Douglas Derrick Bradley Walls Dimitris Metaxas |
| author_facet | Judee K. Burgoon Aaron C. Elkins Douglas Derrick Bradley Walls Dimitris Metaxas |
| author_sort | Judee K. Burgoon |
| collection | DOAJ |
| description | This article considers how computer vision can be enlisted for biomedical applications, specifically the measurement, data analytics and treatment of psychiatric disorders. Often, youngsters are too afraid or embarrassed to disclose their emotional and mental problems to human therapists. An AI system can be utilized not only to collect data in a non-threatening ongoing manner and record patient's temporal psychophysiological state but also to analyze and output the periodic results, it may be an efficient and effective means for therapists to plan treatments. We report on various tools for analyzing social kinesic signals for emotional and physiological states. Only one, AVATAR (and its predecessor SPECIES), both records a patient's state and also outputs an analysis that flags problem areas for therapists. In this way, automated tools can augment human observation and judgment. |
| first_indexed | 2024-03-12T18:00:16Z |
| format | Article |
| id | doaj.art-44d8dc1446454556b5d2a58de414ec8e |
| institution | Directory Open Access Journal |
| issn | 2624-9898 |
| language | English |
| last_indexed | 2024-03-12T18:00:16Z |
| publishDate | 2023-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computer Science |
| spelling | doaj.art-44d8dc1446454556b5d2a58de414ec8e2023-08-02T11:20:39ZengFrontiers Media S.A.Frontiers in Computer Science2624-98982023-08-01510.3389/fcomp.2023.11687121168712The future of automated capture of social kinesic signals for psychiatric purposesJudee K. Burgoon0Aaron C. Elkins1Douglas Derrick2Bradley Walls3Dimitris Metaxas4Center for the Management of Information, University of Arizona, Tucson, AZ, United StatesDepartment of Management Information, San Diego State University, San Diego, CA, United StatesCollege of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE, United StatesDiscern Science International, Tucson, AZ, United StatesCenter for Computational Biomedicine Imaging and Modeling (CBIM), Rutgers University, New Brunswick, NJ, United StatesThis article considers how computer vision can be enlisted for biomedical applications, specifically the measurement, data analytics and treatment of psychiatric disorders. Often, youngsters are too afraid or embarrassed to disclose their emotional and mental problems to human therapists. An AI system can be utilized not only to collect data in a non-threatening ongoing manner and record patient's temporal psychophysiological state but also to analyze and output the periodic results, it may be an efficient and effective means for therapists to plan treatments. We report on various tools for analyzing social kinesic signals for emotional and physiological states. Only one, AVATAR (and its predecessor SPECIES), both records a patient's state and also outputs an analysis that flags problem areas for therapists. In this way, automated tools can augment human observation and judgment.https://www.frontiersin.org/articles/10.3389/fcomp.2023.1168712/fullkinesicscomputer visionautomated visual capturepsychiatric disorderssocial signals |
| spellingShingle | Judee K. Burgoon Aaron C. Elkins Douglas Derrick Bradley Walls Dimitris Metaxas The future of automated capture of social kinesic signals for psychiatric purposes Frontiers in Computer Science kinesics computer vision automated visual capture psychiatric disorders social signals |
| title | The future of automated capture of social kinesic signals for psychiatric purposes |
| title_full | The future of automated capture of social kinesic signals for psychiatric purposes |
| title_fullStr | The future of automated capture of social kinesic signals for psychiatric purposes |
| title_full_unstemmed | The future of automated capture of social kinesic signals for psychiatric purposes |
| title_short | The future of automated capture of social kinesic signals for psychiatric purposes |
| title_sort | future of automated capture of social kinesic signals for psychiatric purposes |
| topic | kinesics computer vision automated visual capture psychiatric disorders social signals |
| url | https://www.frontiersin.org/articles/10.3389/fcomp.2023.1168712/full |
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