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Design of a Virtual Reality Based Adaptive Response Technology for Children With Autism
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Children with autism spectrum disorder (ASD) demonstrate potent impairments in social communication skills including atypical viewing patterns during social interactions. Recently, several assistive technologies, particularly virtual reality (VR), have been investigated to address specific social deficits in this population. Some studies have coupled eye-gaze monitoring mechanisms to design intervention strategies. However, presently available systems are designed to primarily chain learning via aspects of one's performance only which affords restricted range of individualization. The presented work seeks to bridge this gap by developing a novel VR-based interactive system with Gaze-sensitive adaptive response technology that can seamlessly integrate VR-based tasks with eye-tracking techniques to intelligently facilitate engagement in tasks relevant to advancing social communication skills. Specifically, such a system is capable of objectively identifying and quantifying one's engagement level by measuring real-time viewing patterns, subtle changes in eye physiological responses, as well as performance metrics in order to adaptively respond in an individualized manner to foster improved social communication skills among the participants. The developed system was tested through a usability study with eight adolescents with ASD. The results indicate the potential of the system to promote improved social task performance along with socially-appropriate mechanisms during VR-based social conversation tasks.
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“Numerous studies have been conducted to assess different aspects of using chatbots for mental health, such as effectiveness [15, 16], acceptability [14, 17], usability [18, 19], and adoption [20, 21].”
From An overview of the features of chatbots in mental health: A scoping review (2019) · cites this paper as [18]
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Kim, W., Seong, M., DelPreto, J., Matusik, W., Rus, D. L., & Kim, S. (2024) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/3675094.3678376 · Cited by 6
Artiran, S., Cohen, S., & Cosman, P. C. (2024) · Research in Autism · doi:10.1016/j.rasd.2024.102494 · Cited by 6
Bystrova, T., Tokarskaya-Valerievna, L., & Vukovic, D. B. (2019) · International Journal of Cognitive Research in Science Engineering and Education · doi:10.5937/ijcrsee1901063b · Cited by 6
Augmented/Virtual Reality Technologies and Assistive/Humanoid Robots
Goosen, L. (2022) · Advances in educational technologies and instructional design book series · doi:10.4018/978-1-7998-4736-6.ch012 · Cited by 6
Hughes‐Roberts, T., Cui, V., Mahmud, M., & Brown, D. J. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-05039-8_16 · Cited by 6
Virtual Reality-Based Facial Expressions Understanding for Teenagers with Autism
Bekele, E., Zheng, Z., Swanson, A. R., Davidson, J., Warren, Z. E., & Sarkar, N. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39191-0_50 · Cited by 6
Self-citationSnoezelenCAVE: Virtual Reality CAVE Snoezelen Framework for Autism Spectrum Disorders
Perhakaran, G., Yusof, A. M., Rusli, M. E., Yusoff, M. Z. M., Mahidin, E. M. M., Mahalil, I., & Zainudin, A. R. R. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-25939-0_39 · Cited by 6
Validation of Emotions as a Measure of Selective Attention in Children with Autism Spectrum Disorder
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Metadata
- Authors
- Lahiri, U., Bekele, E., Dohrmann, E., Warren, Z., & Sarkar, N.
- Affiliations
- Indian Institute of Technology Gandhinagar (IN)
- Vanderbilt University (US)
- University of Tennessee Health Science Center (US)
- Venue
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Published
- 2013-01
- Volume
- 21
- Issue
- 1
- Pages
- 55-64
- ISSN
- 1534-4320 (ISSN-L)
- 1558-0210
- PMC
- PMC3867261
- OpenAlex
- W2000191594
- Cited by
- 162
- References
- 26
- Citations by year
- 2026: 9 · 2025: 8 · 2024: 19 · 2023: 14 · 2022: 13 · 2021: 9 · 2020: 21 · 2019: 11 · 2018: 12 · 2017: 12 · 2016: 8 · 2015: 14 · 2014: 9 · 2013: 2
- FWCI
- 4.25
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- IEEE Transactions on Neural Systems and Rehabilitation Engineering (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (R01MH091102)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- autism spectrum disorder, virtual reality, eye tracking, social communication skills, assistive technology, engagement measurement, personalized interventions, autistic adolescents
- MeSH terms
- Adolescent, Autistic Disorder, Biofeedback, Psychology, Equipment Design, Eye Movements, Female, Fixation, Ocular, Humans, Interpersonal Relations, Male, Therapy, Computer-Assisted, User-Computer Interface, Treatment Outcome, Imaging, Three-Dimensional
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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