Quadriceps muscle models using fuzzy logic and ANFIS

This paper presents a development of quadriceps muscle models using ANFIS and Fuzzy Logic based on Functional Electrical Stimulation (FES). The models inputs parameter consists of stimulation frequency, pulse width, and sampling time are used to predict quadriceps output torque. The muscle models developed are then validate with the clinical data to evaluate the accuracy of the torque output predicted with the identified parameters. In this study, Fuzzy Logic muscle model gives better performance representing quadriceps muscle model.