[2409.02274] ADHD diagnosis based on action characteristics recorded in videos using machine learning
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Computer Science > Computer Vision and Pattern Recognition

arXiv:2409.02274 (cs)
[Submitted on 3 Sep 2024]

Title:ADHD diagnosis based on action characteristics recorded in videos using machine learning

Authors:Yichun Li, Syes Mohsen Naqvi, Rajesh Nair
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Abstract:Demand for ADHD diagnosis and treatment is increasing significantly and the existing services are unable to meet the demand in a timely manner. In this work, we introduce a novel action recognition method for ADHD diagnosis by identifying and analysing raw video recordings. Our main contributions include 1) designing and implementing a test focusing on the attention and hyperactivity/impulsivity of participants, recorded through three cameras; 2) implementing a novel machine learning ADHD diagnosis system based on action recognition neural networks for the first time; 3) proposing classification criteria to provide diagnosis results and analysis of ADHD action characteristics.
Comments: Neuroscience Applied
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2409.02274 [cs.CV]
  (or arXiv:2409.02274v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2409.02274
Related DOI: https://doi.org/10.1016/j.nsa.2023.102835

Submission history

From: Yichun Li [view email]
[v1] Tue, 3 Sep 2024 20:16:56 UTC (81 KB)
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