Αn Information System for Symptom Diagnosis and Improvement of Attention Deficit Hyperactivity Disorder (ADHD360) (ADHD360)

Αn Information System for Symptom Diagnosis and Improvement of Attention Deficit Hyperactivity Disorder (ADHD360)

Αn Information System for Symptom Diagnosis and Improvement of Attention Deficit Hyperactivity Disorder (ADHD360)

ADHD360 will be an innovative integrated platform for early ADHD diagnosis and intervention against its symptoms. In the core of the platform design there will be a serious game along with a mobile application to monitor behavior and to evaluate the intervention.

The ADHD360 project develop an integrated platform having as core elements a serious game along with a mobile application for monitoring of ADHD behaviors in a SMART (Specific, Measurable, Attainable, Realistic and Timely) way. The design of the serious game is based on both Diagnostic and Statistical Manual of Mental Disorders (version V(American Psychiatric Association, 2013)) along with neuropsychological tools, easily transferred to game, on a specific ADHD behavior. The primary objective of the project is to explore whether the game analytics along with the monitoring data could discriminate the ADHD from non-ADHD users. The secondary objective is to use the platform as an intervention. To this scope, a two-phase pilot study will be performed recruiting at least twenty (20) participants (10 ADHD; 10 non-ADHD) with ages ranging from 7 to 16 years. In the first stage, participants will undergo a neuropsychological evaluation as well as interact with the serious game two times (30-45 minutes/each time). After all participants have completed the first part of the pilot tests, a preliminary analysis of the data will be carried out using modern Machine Learning Methods in order to explore the discriminating capacity of the game. In the second stage, participants will interact with the platform for ten (10) weeks in total (2-3 times/30-45 minutes each). At the end of the second stage, the participants will undergo a neuropsychological evaluation following the procedures of the first one. The partners involved in the implementation of the project are the Intelligent Systems Lab (School of Computer Science, AUTH), the MEDPHYS Laboratory (School of Medicine, AUTH) and the Second Method (TSM) company. The partners cover the expertise required in data analysis, machine learning, medical record keeping, software development and game design (gamification). ADHD360 is co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH - CREATE - INNOVATE [Τ1ΕΔΚ-01680].

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.

ADHD360 platform: An intervention intergrating a serious game along with a mobile application for daily behavioral monitoring.

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.

Explore whether the game analytics could discriminate the ADHD from non-ADHD users of the ADHD360 platform.

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.

Explore whether the monitoring data could discriminate the ADHD from non-ADHD users of the ADHD360 platform.

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.

Explore whether the game analytics along with the monitoring data could discriminate the ADHD from non-ADHD users of the ADHD360 platform.

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.

Inclusion Criteria: (1) Participants should be between 7 and 16 years old (2) Diagnosed ADHD by an approved body of Ministry of Health (3) Participants willing to follow the study protocol and procedures (4) Participants with ADHD symptoms that they are not induced by an organic disease (5) Participants' parents voluntarily provided written consent for their children's participation in the study. Exclusion Criteria: (1) Participants in ADHD group having other disorders apart from ADHD (2) Parents who refuse to give written consent for their children's participation in the study.

Pandria N, Petronikolou V, Lazaridis A, Karapiperis C, Kouloumpris E, Spachos D, Fachantidis A, Vasiliou D, Vlahavas I, Bamidis P. Information System for Symptom Diagnosis and Improvement of Attention Deficit Hyperactivity Disorder: Protocol for a Nonrandomized Controlled Pilot Study. JMIR Res Protoc. 2022 Sep 28;11(9):e40189. doi: 10.2196/40189.