EPP064 - Development and Feasibility of a Yoga-Based Motor Assessment Tool (Y-MAT) with AI-Enabled Scoring for Children with ADHD

EPP064

Development and Feasibility of a Yoga-Based Motor Assessment Tool (Y-MAT) with AI-Enabled Scoring for Children with ADHD

V. P 1,*, B. Holla 1, H. Bhargav 1, E. Sharma 2, R. Naidu L 3

1Department of Integrative Medicine, 2Department of Child and Adolescent Psychiatry , NIMHANS, 3Centre for Development of Advanced Computing, Bangalore, India

 

Introduction: Motor dysfunction in ADHD is increasingly recognized as a core manifestation of neurodevelopmental disruption rather than an incidental problem. Yet there is no consensus gold-standard motor assessment, and most tools emphasize broad milestones rather than neuromuscular dysregulation.

Objectives: Aim: Develop a Yoga-Based Motor Assessment Tool (Y-MAT) for children with ADHD.

Primary objectives: Develop and validate the tool; pilot test feasibility.

Secondary objective: Explore artificial intelligence and video-analytics for digitizing motor assessment.

Methods: Seven motor domains were identified through review of literature and mapped to Yoga-tasks through expert consensus (n=6). The Y-MAT was administered to 11 children with ADHD and 10 controls by a trained psychiatrist, video-recorded, and scored by 2 blinded human raters. AI-based scoring was also implemented using Google’s MediaPipe and YOLOv8 for pose recognition and movement analysis. All children were also assessed using the ADHD Rating Scale (ADHD-RS) and the Vineland Social Maturity Scale (VSMS) to evaluate symptom severity and social functioning. Feasibility, Inter-rater reliability (Cohen’s kappa) and Concurrent Validity was measured.

Results: The Y-MAT demonstrated high acceptability, engagement and a minimal dropout rate.The ADHD scores show a moderate negative correlation with both ratings, with slightly stronger associations for AI-based scoring, indicating that greater ADHD severity was associated with poorer neuromuscular regulation. Inter-rater reliability ranged from fair to moderate agreement, with Impulse Control of Vrikshasana (p=0.0001) and Motor Sequencing of Surya Namaskar (p=0.0032) exhibiting the strongest and statistically significant agreement. AI-based scores moderately correlated with human ratings. 

 

Table 1 – Selected Yoga-tasks mapped to their corresponding motor domains

 

YOGA TASK

MOTOR DOMAINS

A. Dynamic Trikonasana/ Triangle pose

Body Awareness & Spatial Orientation (A1), Bilateral & Cross Limb Coordination (A2)

B. Vrikshasana/ Tree pose

Static & Dynamic Balance (B1), Impulse Control & Movement Regulation (B2)

C. Surya Namaskar/ Sun Salutation

Motor Sequencing & Rhythm (C1), Bilateral & Cross Limb Coordination (C2), Body Awareness & Spatial Orientation (C3), Static & Dynamic Balance (C4)

D. Alternating Mudras

Fine Motor Dexterity & Control (D1), Bilateral & Cross Limb Coordination (D2)

E. Bhramari

Breath Control (E1), Impulse Control & Movement Regulation (E2)

 

 

Conclusions: The Y-MAT is a feasible and engaging approach to assess motor dysfunction relevant to ADHD. Preliminary evidence supports concurrent validity and the promise of AI-assisted scoring for scalable, real-time, objective evaluation. 

 

Disclosure of Interest: None Declared