Rehabilitation Assessment of Motor Function in Ambulatory Children With Cerebral Palsy Using Explainable Machine Learning
Rehabilitation Assessment of Motor Function in Ambulatory Children With Cerebral Palsy Using Explainable Machine Learning
The goal of this observational study is to develop and validate an AI-based prediction model for functional mobility and gait outcomes in children with cerebral palsy using low-cost clinical and gait data collected in rehabilitation settings in Pakistan.
Children with cerebral palsy (CP) commonly experience limitations in functional independence and mobility, which significantly affect participation and quality of life. Accurate assessment of these functional abilities is essential for rehabilitation planning, prognosis estimation, and monitoring treatment outcomes. However, conventional assessment methods largely depend on therapist observation and standardized clinical scales, which may be subjective, time-consuming, and less sensitive to complex interactions among clinical variables.
Inclusion Criteria:
Exclusion Criteria:
qamar.mehmood@riphah.edu.pk03335151063
Islamabad, Pakistan
sidrahasan1989@gmail.com03224356227
sidrahasan1989@gmail.com
sidrahasan1989@gmail.com03224356227
sidrahasan1989@gmail.com
sidrahasan1989@gmail.com03314140498
sidrahasan1989@gmail.com