Towards an AI-driven soft toy for automatically detecting and classifying infant-toy interactions using optical force sensors.

ABSTRACT: Introduction: It is crucial to identify neurodevelopmental disorders in infants early on for timely intervention to improve their long-term outcomes. Combining natural play with quantitative measurements of developmental milestones can be an effective way to swiftly and efficiently detect infants who are at risk of neurodevelopmental delays. Clinical studies have established differences in toy interaction behaviors between full-term infants and pre-term infants who are at risk for cerebral palsy and other developmental disorders. Methods: The proposed toy aims to improve the quantitative assessment of infant-toy interactions and fully automate the process of detecting those infants at risk of developing motor delays. This paper describes the design and development of a toy th

SUBMITTER: Udayagiri R 

PROVIDER: S-EPMC10963494 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature