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arXiv · 2409.02274

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

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.

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Yichun Li, Syes Mohsen Naqvi, Rajesh Nair. 2024-09-03. ADHD diagnosis based on action characteristics recorded in videos using machine learning. https://doi.org/10.1016/j.nsa.2023.102835

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