Feasibility and Discriminant Validity of Monitoring Movement Behavior of Adolescents With Cerebral Palsy

A new artificial intelligence network has been developed to monitor real-world daytime and nighttime movement behavior of adolescents with cerebral palsy (CP). The network uses seven wearable sensors to recognize lying, sitting, and standing, as well as walking and movements of both arms and legs. This information can be useful for healthcare professionals to understand and influence change in movement behavior, leading to benefits for the health of adolescents with cerebral palsy. This study aims to examine the acceptability and technical dependability of monitoring the movement behavior of adolescents with cerebral palsy for 72 hours using wearable sensors. Additionally, the study aims to evaluate the network's ability to discriminate between control and individuals with CP, different subgroups of individuals with CP, as well as the incidence of sleep disturbance in the entire cohort.