The application of the movement classification system in the diagnosis of children with Cerebral Palsy

Cerebral Palsy is mean damage to the brain, causing non-progressive brain injury, such as hemiplegia, limbs palsy, epilepsy, involuntary movements, poor coordination. This paper proposes a movement evaluation and classification system, in view Cerebral Palsy children hand movement smoothness evaluation. In addition, the application of the movement classification system in the diagnosis of children with cerebral palsy is also discussed. The system contains: image capture, image segmentation, and information classification processing. Momentum analysis parameters and coordination neural network are used to conduct the data classification. The experimental results are shown that the proposed system has the higher accurate diagnostic rate of children are divided into cerebral palsy groups or normal groups.