This paper is in the following e-collection/theme issue:

Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (997) Mobile Health (mhealth) (3464) Autism Spectrum Disorder (ASD) (141) mHealth for Data Collection and Research (1196) Clinical Informatics (1325) New Methods (1134) Research Instruments, Questionnaires, and Tools (738) New Diagnostic Tools and Instruments for Pediatrics (48) Screening and Early Diagnosis in Pediatrics (41)

Published on in Vol 24, No 2 (2022): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31830, first published .
Identification of Social Engagement Indicators Associated With Autism Spectrum Disorder Using a Game-Based Mobile App: Comparative Study of Gaze Fixation and Visual Scanning Methods

Identification of Social Engagement Indicators Associated With Autism Spectrum Disorder Using a Game-Based Mobile App: Comparative Study of Gaze Fixation and Visual Scanning Methods

Identification of Social Engagement Indicators Associated With Autism Spectrum Disorder Using a Game-Based Mobile App: Comparative Study of Gaze Fixation and Visual Scanning Methods

Authors of this article:

Maya Varma1 Author Orcid Image ;   Peter Washington2 Author Orcid Image ;   Brianna Chrisman2 Author Orcid Image ;   Aaron Kline3 Author Orcid Image ;   Emilie Leblanc3 Author Orcid Image ;   Kelley Paskov4 Author Orcid Image ;   Nate Stockham5 Author Orcid Image ;   Jae-Yoon Jung3 Author Orcid Image ;   Min Woo Sun4 Author Orcid Image ;   Dennis P Wall3 Author Orcid Image
Article Authors Cited by (34) Tweetations (3) Metrics

Journals

  1. Chien Y, Lee C, Chiu Y, Tsai W, Min Y, Lin Y, Wong J, Tseng Y. Game-Based Social Interaction Platform for Cognitive Assessment of Autism Using Eye Tracking. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2023;31:749 View
  2. Iao W, Zhang W, Wang X, Wu Y, Lin D, Lin H. Deep Learning Algorithms for Screening and Diagnosis of Systemic Diseases Based on Ophthalmic Manifestations: A Systematic Review. Diagnostics 2023;13(5):900 View
  3. Sleiman E, Mutlu O, Surabhi S, Husic A, Kline A, Washington P, Wall D. Deep Learning-Based Autism Spectrum Disorder Detection Using Emotion Features From Video Recordings (Preprint). JMIR Biomedical Engineering 2022 View
  4. Banerjee A, Mutlu O, Kline A, Surabhi S, Washington P, Wall D. Training and Profiling a Pediatric Facial Expression Classifier for Children on Mobile Devices: Machine Learning Study. JMIR Formative Research 2023;7:e39917 View
  5. Parab S, Boster J, Washington P. Parkinson Disease Recognition Using a Gamified Website: Machine Learning Development and Usability Study. JMIR Formative Research 2023;7:e49898 View
  6. Washington P, Wall D. A Review of and Roadmap for Data Science and Machine Learning for the Neuropsychiatric Phenotype of Autism. Annual Review of Biomedical Data Science 2023;6(1):211 View
  7. Bondioli M, Chessa S, Kocian A, Pelagatti S. A survey on technological tools and systems for diagnosis and therapy of autism spectrum disorder. Human–Computer Interaction 2024;39(3-4):145 View
  8. Liu X, Zhao W, Qi Q, Luo X. A Survey on Autism Care, Diagnosis, and Intervention Based on Mobile Apps: Focusing on Usability and Software Design. Sensors 2023;23(14):6260 View
  9. Germanese D, Colantonio S, Del Coco M, Carcagnì P, Leo M. Computer Vision Tasks for Ambient Intelligence in Children’s Health. Information 2023;14(10):548 View
  10. Sun Y, Kargarandehkordi A, Slade C, Jaiswal A, Busch G, Guerrero A, Phillips K, Washington P. Personalized Deep Learning for Substance Use in Hawaii: Protocol for a Passive Sensing and Ecological Momentary Assessment Study. JMIR Research Protocols 2024;13:e46493 View
  11. Jaiswal A, Washington P. Using #ActuallyAutistic on Twitter for Precision Diagnosis of Autism Spectrum Disorder: Machine Learning Study. JMIR Formative Research 2024;8:e52660 View
  12. Washington P. A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health. Journal of Medical Internet Research 2024;26:e51138 View
  13. Zhao W, Xu S, Zhang Y, Li D, Zhu C, Wang K. The Application of Extended Reality in Treating Children with Autism Spectrum Disorder. Neuroscience Bulletin 2024;40(8):1189 View
  14. Toki E, Pange J, Tatsis G, Plachouras K, Tsoulos I. Utilizing Constructed Neural Networks for Autism Screening. Applied Sciences 2024;14(7):3053 View
  15. Jia S, Jing J, Yang C. A Review on Autism Spectrum Disorder Screening by Artificial Intelligence Methods. Journal of Autism and Developmental Disorders 2025;55(9):3011 View
  16. Mohamed Selim A, Barz M, Bhatti O, Alam H, Sonntag D. A review of machine learning in scanpath analysis for passive gaze-based interaction. Frontiers in Artificial Intelligence 2024;7 View
  17. Sánchez Espinosa K, Saavedra Rubio J. Dispositivos móviles y niños con trastorno del espectro autista: ¿qué dice la literatura?. Revista Salud y Desarrollo 2022;6(2):83 View
  18. Liu M, Wu X, Li Z, Tan D, Huang C. Assessment of Eye Care Apps for Children and Adolescents Based on the Mobile App Rating Scale: Content Analysis and Quality Assessment. JMIR mHealth and uHealth 2024;12:e53805 View
  19. Krishnappa Babu P, Di Martino J, Aiello R, Eichner B, Espinosa S, Green J, Howard J, Perochon S, Spanos M, Vermeer S, Dawson G, Sapiro G. Validation of a Mobile App for Remote Autism Screening in Toddlers. NEJM AI 2024;1(10) View
  20. Jin L, Cui H, Zhang P, Cai C. Early diagnostic value of home video–based machine learning in autism spectrum disorder: a meta-analysis. European Journal of Pediatrics 2024;184(1) View
  21. Guhan P, Awasthi N, McDonald K, Bussell K, Reeves G, Manocha D, Bera A. Developing a Machine Learning–Based Automated Patient Engagement Estimator for Telehealth: Algorithm Development and Validation Study. JMIR Formative Research 2025;9:e46390 View
  22. Shahini A, Kamath A, Sharma E, Salvi M, Tan R, Siuly S, Seoni S, Ganguly R, Devi A, Deo R, Barua P, Acharya U. A systematic review for artificial intelligence-driven assistive technologies to support children with neurodevelopmental disorders. Information Fusion 2025;124:103441 View
  23. Setu D. A Systematic Review of Developments in Eye Tracking and Machine Learning for the Early Detection of Autism Spectrum Disorder. Journal of Technology in Behavioral Science 2025 View
  24. Li X, Huang W, Tan R, Xu C, Chen X, Zhang Q, Li S, Liu Y, Qiu H, Bi C, Cao H. The Current Research Landscape on the Machine Learning Application in Autism Spectrum Disorder: A Bibliometric Analysis From 1999 to 2023. Current Neuropharmacology 2025;23(11):1442 View
  25. Sun C, McEwan A, Boulton K, Demetriou E, Sadozai A, Lampit A, Guastella A. Artificial intelligence for tracking social behaviours and supporting an autism spectrum disorder diagnosis: systematic review and meta-analysis. eBioMedicine 2025;120:105931 View
  26. Rakotomanana H, Rouhafzay G. A Scoping Review of AI-Based Approaches for Detecting Autism Traits Using Voice and Behavioral Data. Bioengineering 2025;12(11):1136 View
  27. Azizian P, Honarmand M, Jaiswal A, Kline A, Dunlap K, Washington P, Wall D. Multimodal LLM vs. Human-Measured Features for AI Predictions of Autism in Home Videos. Algorithms 2025;18(11):687 View
  28. Shilpa R, Vinay B, Rajendra A. A review of emerging non-invasive techniques for early autism spectrum disorder detection: insights from AI and biomarkers. International Journal of Developmental Disabilities 2025:1 View
  29. Huynh M, Kline A, Surabhi S, Dunlap K, Mutlu O, Honarmand M, Azizian P, Washington P, Wall D. Ensemble Modeling of Multiple Physical Indicators to Dynamically Phenotype Autism Spectrum Disorder. Algorithms 2025;18(12):764 View

Books/Policy Documents

  1. Toki E, Zakopoulou V, Tatsis G, Plachouras K, Pange J. Open Science in Engineering. View
  2. Abdelmaksoud E, El-Saba E, Abd El-Maksoud S, Al-Adrousy W, Elmogy M. The Future of Inclusion: Bridging the Digital Divide with Emerging Technologies. View

Conference Proceedings

  1. Kurniawan Y, Christian W, Anwar N. Proceedings of the 2023 4th International Conference on Education Development and Studies. Designing Mobile Applications to Support Learning from Home for Children with Autism Spectrum Disorder View
  2. Kalanadhabhatta M, Mateo Santana A, Mayorga L, Rahman T, Ganesan D, Grabell A. Proceedings of the CHI Conference on Human Factors in Computing Systems. Multi-stakeholder Perspectives on Mental Health Screening Tools for Children View
  3. Dæhlen A, Heldal I, Katona J. Proceedings of the 2024 Symposium on Eye Tracking Research and Applications. Linking Data from Eye-Tracking and Serious Games to NDD Characteristics: A Bibliometric Study View