In the first part of the clinical trials, ADHD cohorts are going to undergo a neuropsychological assessement. Moreover, they will interact with the serious game twice (30-45 minutes/each time). In the second part, participants will interact with game two or three times per week (30-45 minutes/each time). Finally, a neuropsychological assessment will be administered following the procedures of the first one.

Non-ADHD group will follow the same procedures as the experimental one.

Clinical trials will include two parts. The first part includes three visits. In the first visit, children and their parents will come to the Laboratory of Medical Physics to be informed regarding the experimental procedures, sign the consent form and familiarize with the scientific staff involved in the project as well as the lab enviroment. In the second visit, children will undergo an neuropsychological assessment delivered by an experienced pscychologist. Afterwards, they will interact with the ADHD360 platfrom for 30-45 minutes. In the third visit, participants will interact with the ADHD360 platfrom for 30-45 minutes. In the second part, participants will use the ADHD360 platfrom two or three times per week for about 30-45 minutes. At the end of the second part, participants will undergo a neuropsychological evalutation following the same procedures as the first one.

After all participants completed the first part of the clinical trials, an analysis of the data collected from the platform will be carried out. This includes processing recorded gameplay scores for the extraction of useful features that, in turn, shall be used for training and evaluating modern Machine Learning methods, such as Neural Networks, Support Vector Machines (SVMs), Random Forests, Decision Trees, and/or k-Nearest Neighbors (kNN), in order to learn the differentiating properties of ADHD cases against non-ADHD cases within the game.

After all participants completed the first part of the clinical trials, an analysis of the data collected from the platform will be carried out. This includes processing recorded data of attention for the extraction of useful features that, in turn, shall be used for training and evaluating modern Machine Learning methods, such as Neural Networks, Support Vector Machines (SVMs), Random Forests, Decision Trees, and/or k-Nearest Neighbors (kNN), in order to learn the differentiating properties of ADHD cases against non-ADHD cases within the game.

After all participants completed the first part of the clinical trials, an analysis of the data collected from the platform will be carried out. This includes processing recorded gameplay time for the extraction of useful features that, in turn, shall be used for training and evaluating modern Machine Learning methods, such as Neural Networks, Support Vector Machines (SVMs), Random Forests, Decision Trees, and/or k-Nearest Neighbors (kNN), in order to learn the differentiating properties of ADHD cases against non-ADHD cases within the game.

Changes in scores of Test of Everyday Attention for Children subtests will be evaluated before and after the intervention.