Using Body Sensor Network to Measure the Effect of Rehabilitation Therapy on Improvement of Lower Limb Motor Function in Children With Spastic Diplegia

Abstract

Evaluation of the motor ability of children with cerebral palsy (CP) based on International Classification of Functioning, Disability and Health for Children and Youth (ICF-CY) framework is an effective way to evaluate exercise rehabilitation therapy at present. Spastic diplegia (SD) is a common symptom in children with CP, which can cause movement disorders and physical disability of lower limbs. To rehabilitate these children, it is important to assess their exercise level in different treatment stages. In this study, an effective method of motion measurement based on inertial sensor network is proposed to evaluate the children’s motor ability in the purpose of the therapy effectiveness validation for the CP children. The extended Kalman filter (EKF) is used to fuse the sensor signals to measure the motion of body segments whose accuracy is verified by the OptiTrack optical system. A novel kinetic model based on a skeletal vector is proposed to reconstruct the posture of children in sports training to evaluate the effect of exercise rehabilitation. Statistical analysis is deployed to analyze the rehabilitation of motor function corresponding to SD children. The results are encouraging; some children’s motor functions of lower limbs have been improved postrehabilitation training.