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 de...

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Bibliographic Details
Main Authors: Salleh, S. M., Jailani, R., Tokhi, M. O.
Format: Conference Proceeding
Language:English
Subjects:
ANFIS
Biological system modeling
Data models
Force
Functional Electrical Stimulation (FES)
Fuzzy logic
Mathematical model
Muscles
Neuromuscular stimulation
Quadriceps Muscle Model
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Summary: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.
DOI:10.1109/ICSEngT.2013.6650209