# The Validity of a Machine Learning-Based Video Game in the Objective Screening of Attention Deficit Hyperactivity Disorder in Children Aged 5 to 12 Years

arXiv: https://arxiv.org/abs/2312.11832 · HTML: https://mlsanity.com/paper/2312.11832/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 47 references that are in the map.
- First posted on arXiv 19 Dec 2023.

## Builds on (most cited first, 1 of 1)

- [A Review on Serious Games for ADHD](https://mlsanity.com/paper/2105.02970/) (2021)

## Abstract (arXiv)

Objective: Early identification of ADHD is necessary to provide the opportunity for timely treatment. However, screening the symptoms of ADHD on a large scale is not easy. This study aimed to validate a video game (FishFinder) for the screening of ADHD using objective measurement of the core symptoms of this disorder. Method: The FishFinder measures attention and impulsivity through in-game performance and evaluates the child's hyperactivity using smartphone motion sensors. This game was tested on 26 children with ADHD and 26 healthy children aged 5 to 12 years. A Support Vector Machine was employed to detect children with ADHD. results: This system showed 92.3% accuracy, 90% sensitivity, and 93.7% specificity using a combination of in-game and movement features. Conclusions: The FishFinder demonstrated a strong ability to identify ADHD in children. So, this game can be used as an affordable, accessible, and enjoyable method for the objective screening of ADHD.