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

• URL: http://arxiv.org/abs/2409.02274v1
• Date: Tue, 3 Sep 2024 20:16:56 GMT
• Title: ADHD diagnosis based on action characteristics recorded in videos using machine learning
• Authors: Yichun Li, Syes Mohsen Naqvi, Rajesh Nair,
• Abstract summary: 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; and 3) proposing classification criteria to provide diagnosis results and analysis of ADHD action characteristics.
• Score: 0.472457683445805
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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