Identification of postural control for children with autism using a machine learning approach

The study successfully developed and validated an automated identification of autistic postural control patterns using a machine learning approach. In general, simpler machine learning algorithms displayed higher accuracy rates compared to more complicated ones. The use of machine learning may provide a valid and efficient approach to better understand autistic postural control features and thus, could be beneficial for the early diagnosis and early intervention in children with autism.