AI RESEARCH
Longitudinal Digital Phenotyping for Early Cognitive-Motor Screening
arXiv CS.LG
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ArXi:2603.25673v1 Announce Type: new Early detection of atypical cognitive-motor development is critical for timely intervention, yet traditional assessments rely heavily on subjective, static evaluations. The integration of digital devices offers an opportunity for continuous, objective monitoring through digital biomarkers. In this work, we propose an AI-driven longitudinal framework to model developmental trajectories in children aged 18 months to 8 years.