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

Yichun Li, Syes Mohsen Naqvi, Rajesh Nair
9/3/2024
cs.CV

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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.

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Cite this paper

@article{li2024adhd,
  title  = {ADHD diagnosis based on action characteristics recorded in videos using machine learning},
  author = {Yichun Li and Syes Mohsen Naqvi and Rajesh Nair},
  year   = {2024},
  eprint = {2409.02274},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2409.02274v1}
}

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