Application of Fuzzy Logic type 2 in Building a Numerical Index for Evaluating Surgical Intervention for Children with Spastic Cerebral Palsy

Abstract

Gait analysis has many applications in the quantitative assessment of normal or pathological human gait. Many parameters are calculated in gait monitoring, including spatiotemporal, kinematic, and joint kinematic parameters to evaluate the patient's gait numerically or based on a scale. In this research, a Fuzzy logic type-2 system was used To design a smart index (FL2-AKHDI) that evaluates the deviations of the ankle, knee, and hip joints in CP patients before and after surgery compared to children with normal development. The proposed methodology starts by extracting the characteristic features from the angle diagrams of the hip, knee, and ankle joints during the gait cycle. Then it initializes the FL system based on the extracted features. Finally, the performance of the proposed index will be evaluated. The results concluded that it is possible to use Fuzzy logic type-2 to evaluate the effectiveness of surgical operations for patients with cerebral palsy The average value of the index for the patient group decreased by (25%), and this percentage corresponds to the percentage of decrease in the average value of the GPS index, which is equal to (21%). The importance of this research also lies in providing a prototype of a medical decision support system that can quantitatively evaluate disease conditions and evaluate the efficiency of treatment and medical intervention using FL.