Analysis of Motor Signatures of Social Adaptation in Autism for Efficient Human-Centric Systems

2026-08-12

AI Summary

This study addresses the identification of social adaptation differences in individuals with autism spectrum disorder (ASD) through movement behavior characteristics, aiming to inform precision medicine and human-computer interaction design. Using 3D motion capture data collected during a dance imitation task, the research compares movement patterns between autistic and neurotypical adults in both solitary and social contexts. It introduces the Social Context Sensitivity Index (SCSI), which—by quantifying how motor variability is modulated by social framing—proposes a novel potential motor biomarker for ASD. Movement consistency is assessed via dynamic time warping, and machine learning models are employed for group classification. Results reveal that neurotypical participants exhibit significantly increased upper- and lower-limb motor variability in social settings, whereas ASD participants maintain stable variability. The classifier achieves a balanced accuracy of 79.2%.

Abstract

Dance imitation integrates motor planning, sensorimotor integration, and social cognition, offering a sensitive framework to characterize motor behavior in autism. In this work, we explore a computational analysis framework to identify potential biomarkers that allow the design and development of improved medical and human-machine systems. We analyzed 3D motion capture data from autistic and neurotypical adults performing dance imitation under solo and socially-framed duo conditions. Methodologically, using Dynamic Time Warping, we quantified movement consistency and propose the Social Context Sensitivity Index (SCSI) to measure modulation of variability by social framing. These features were then used on a classifier to discriminate subjects into autistic or neurotypical groups. Results show that neurotypical adults exhibited increased movement variability in socially-framed imitation, especially in upper and lower limbs, whereas autistic adults maintained consistent movement across contexts. Classification achieved 79.2% balanced accuracy in distinguishing groups. These findings suggest that social context sensitivity in motor imitation constitutes a robust biomarker of autism-related motor behavior, highlighting the importance of social modulation in motor assessments and informing the development of inclusive human-centric technologies.

Problem

• autism
• motor signatures
• social adaptation
• dance imitation
• biomarkers

Innovation

• Social Context Sensitivity Index
• Dynamic Time Warping
• motor biomarkers
• dance imitation
• human-centric systems