Through the lens of artificial intelligence: A novel study of spherical video-based virtual reality usage in autism and neurotypical participants
The current study explores the use of computer vision and artificial intelligence (AI) methods for analyzing 360-degree spherical video-based virtual reality (SVVR) data. The study aimed to explore the potential of AI, computer vision, and machine learning methods (including entropy analysis, Markov...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Computers & Education: X Reality |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949678023000351 |
| _version_ | 1797347027417300992 |
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| author | Matthew Schmidt Noah Glaser Heath Palmer Carla Schmidt Wanli Xing |
| author_facet | Matthew Schmidt Noah Glaser Heath Palmer Carla Schmidt Wanli Xing |
| author_sort | Matthew Schmidt |
| collection | DOAJ |
| description | The current study explores the use of computer vision and artificial intelligence (AI) methods for analyzing 360-degree spherical video-based virtual reality (SVVR) data. The study aimed to explore the potential of AI, computer vision, and machine learning methods (including entropy analysis, Markov chain analysis, and sequential pattern mining), in extracting salient information from SVVR video data. The research questions focused on differences and distinguishing characteristics of autistic and neurotypical usage characteristics in terms of behavior sequences, object associations, and common patterns, and the extent to which the predictability and variability of findings might distinguish the two participant groups and provide provisional insights into the dynamics of their usage behaviors. Findings from entropy analysis suggest the neurotypical group showed greater homogeneity and predictability, and the autistic group displayed significant heterogeneity and variability in behavior. Results from the Markov Chains analysis revealed distinct engagement patterns, with autistic participants exhibiting a wide range of transition probabilities, suggesting varied SVVR engagement strategies, and with the neurotypical group demonstrating more predictable behaviors. Sequential pattern mining results indicated that the autistic group engaged with a broader spectrum of classes within the SVVR environment, hinting at their attraction to a diverse set of stimuli. This research provides a preliminary foundation for future studies in this area, as well as practical implications for designing effective SVVR learning interventions for autistic individuals. |
| first_indexed | 2024-03-08T11:41:38Z |
| format | Article |
| id | doaj.art-a41b63ec065d467d93e3eccc3b17f4b3 |
| institution | Directory Open Access Journal |
| issn | 2949-6780 |
| language | English |
| last_indexed | 2024-03-08T11:41:38Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computers & Education: X Reality |
| spelling | doaj.art-a41b63ec065d467d93e3eccc3b17f4b32024-01-25T05:24:55ZengElsevierComputers & Education: X Reality2949-67802023-12-013100041Through the lens of artificial intelligence: A novel study of spherical video-based virtual reality usage in autism and neurotypical participantsMatthew Schmidt0Noah Glaser1Heath Palmer2Carla Schmidt3Wanli Xing4Department of Workforce Education and Instructional Technology, Mary Frances Early College of Education, Department of Clinical and Administrative Pharmacy, College of Pharmacy, University of Georgia, River’s Crossing, 226, Athens, GA, 30602, Georgia; Corresponding author.University of Missouri, United StatesUniversity of Cincinnati, United StatesBayada Home Health Care, United StatesUniversity of Florida, United StatesThe current study explores the use of computer vision and artificial intelligence (AI) methods for analyzing 360-degree spherical video-based virtual reality (SVVR) data. The study aimed to explore the potential of AI, computer vision, and machine learning methods (including entropy analysis, Markov chain analysis, and sequential pattern mining), in extracting salient information from SVVR video data. The research questions focused on differences and distinguishing characteristics of autistic and neurotypical usage characteristics in terms of behavior sequences, object associations, and common patterns, and the extent to which the predictability and variability of findings might distinguish the two participant groups and provide provisional insights into the dynamics of their usage behaviors. Findings from entropy analysis suggest the neurotypical group showed greater homogeneity and predictability, and the autistic group displayed significant heterogeneity and variability in behavior. Results from the Markov Chains analysis revealed distinct engagement patterns, with autistic participants exhibiting a wide range of transition probabilities, suggesting varied SVVR engagement strategies, and with the neurotypical group demonstrating more predictable behaviors. Sequential pattern mining results indicated that the autistic group engaged with a broader spectrum of classes within the SVVR environment, hinting at their attraction to a diverse set of stimuli. This research provides a preliminary foundation for future studies in this area, as well as practical implications for designing effective SVVR learning interventions for autistic individuals.http://www.sciencedirect.com/science/article/pii/S2949678023000351Computer visionSpherical video-based virtual realityArtificial IntelligenceData mining |
| spellingShingle | Matthew Schmidt Noah Glaser Heath Palmer Carla Schmidt Wanli Xing Through the lens of artificial intelligence: A novel study of spherical video-based virtual reality usage in autism and neurotypical participants Computers & Education: X Reality Computer vision Spherical video-based virtual reality Artificial Intelligence Data mining |
| title | Through the lens of artificial intelligence: A novel study of spherical video-based virtual reality usage in autism and neurotypical participants |
| title_full | Through the lens of artificial intelligence: A novel study of spherical video-based virtual reality usage in autism and neurotypical participants |
| title_fullStr | Through the lens of artificial intelligence: A novel study of spherical video-based virtual reality usage in autism and neurotypical participants |
| title_full_unstemmed | Through the lens of artificial intelligence: A novel study of spherical video-based virtual reality usage in autism and neurotypical participants |
| title_short | Through the lens of artificial intelligence: A novel study of spherical video-based virtual reality usage in autism and neurotypical participants |
| title_sort | through the lens of artificial intelligence a novel study of spherical video based virtual reality usage in autism and neurotypical participants |
| topic | Computer vision Spherical video-based virtual reality Artificial Intelligence Data mining |
| url | http://www.sciencedirect.com/science/article/pii/S2949678023000351 |
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