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

Computer-Aided Diagnosis (255) Autism Spectrum Disorder (ASD) (142) Machine Learning (2095) Diagnostic Tools in Mental Health (328) New Diagnostic Tools and Instruments for Pediatrics (50)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73440, first published .
Deep Learning Approaches for Classifying Children With and Without Autism Spectrum Disorder Using Inertial Measurement Unit Hand Tracking Data: Comparative Study

Deep Learning Approaches for Classifying Children With and Without Autism Spectrum Disorder Using Inertial Measurement Unit Hand Tracking Data: Comparative Study

Deep Learning Approaches for Classifying Children With and Without Autism Spectrum Disorder Using Inertial Measurement Unit Hand Tracking Data: Comparative Study

Authors of this article:

John Mutersbaugh1 Author Orcid Image ;   Wan-Chun Su2 Author Orcid Image ;   Anjana Bhat3, 4 Author Orcid Image ;   Amir Gandjbakhche1 Author Orcid Image
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John Mutersbaugh   1 , BS ;   Wan-Chun Su   2 , PhD ;   Anjana Bhat   3, 4 , PhD ;   Amir Gandjbakhche   1 , PhD

1 NICHD, National Institutes of Health, Bethesda, MD, United States

2 Louisiana State University, Baton Rouge, LA, United States

3 University of Delaware, Newark, DE, United States

4 Biomechanics and Movement Science Program, Physical Therapy Department, University of Delaware, Newark, DE, United States

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