ADHD diagnosis based on action characteristics recorded in videos using machine learning
<|reference_start|>ADHD diagnosis based on action characteristics recorded in videos using machine learning: 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.<|reference_end|>
@article{li2024adhd,
    title={ADHD diagnosis based on action characteristics recorded in videos using
  machine learning},
    author={Yichun Li, Syes Mohsen Naqvi, Rajesh Nair},
    journal={arXiv preprint arXiv:2409.02274},
    year={2024},
    doi={10.1016/j.nsa.2023.102835},
    archivePrefix={arXiv},
    eprint={2409.02274},
    primaryClass={cs.CV}
}