Preliminary results of the EPIDIA4Kids study on Brain Functioning in Children: multidimensional ADHD-related symptomatology screening using multimodality biometry

Yanice GUIGOU ¹ Alexandre Hennequin ¹ Theo Marcahnd ^1,2 Mouna Chebli ¹ Lucie Isoline Pisella ¹ Pascal Staccini ^3,4 Vanessa Douet Vannucci ^1,3*

• ¹ O-Kidia, Nice, Provence-Alpes-Côte d'Azur, France
• ² Département Bioélectronique, École des Mines de Saint-Étienne, Gardanne, France
• ³ UPR Risk Epidemiology Territory INformatics Education and Health (UPR RETINES), Université Côte d'Azur, Nice, Provence-Alpes-Côte d'Azur, France
• ⁴ Medical Information Department, Independent researcher, Nice, France

Attention-deficit hyperactivity disorder (ADHD) occurs in 5.9% of youth, impacting their health and social conditions often across lifespan. Currently, early diagnosis is constrained by clinical complexity and limited resources of professionals to conduct evaluations. Scalable methods for ADHD-screening are thus needed.Recently, digital epidemiology and biometry, such as visual-, emotional-, or digit-pathway, has shown reflecting brain dysfunctioning in ADHD-individuals. However, whether biometry can support screening for ADHD-symptoms using a multimodal tech-system is still unknown.The EPIDIA4Kids study aims to create objective measures, i.e. biometrics, that will provide a comprehensive transdiagnostic picture of individuals with ADHD, aligning with current evidence for comorbid presentations.Twenty-four children aged 7 to 12 years performed gamified tasks on an unmodified tablet using the XAI4Kids® multimodal system that allow extraction of biometrics (eye-, digit- and emotion-tracking), from video and touch events using machine learning. Neuropsychological assessments and questionnaires were administered to provide ADHD-related measures. Each ADHD-related measure was evaluated with each biometric using linear mixed-effect models.In contrast to neuro-assessments, only two digit-tracking features had an age- and sex-effect (p<0.001) among biometrics. Biometric constructs were predictors of working memory (p<0.0001) and processing speed (p<0.0001), and to lower extent of visuospatial skills (p=0.003), inattention (p=0.04), or achievement (p=0.04) where multi-modalities being crucial to capture several symptomatology dimensions.These results illustrate the potential of multimodality biometry gathered from a tablet as a viable and scalable transdiagnostic approach for screening ADHD-symptomatology and improve accessibility to specialized professionals. Larger populations including clinically diagnosed ADHD will be needed for further validation.