Intelligent modelling and control with fatigue reduction for fes induced knee joint of hemiplegic for rehabilitation

Functional electrical stimulation (FES) is one of the treatment for the people with stroke such as hemiplegic body (half body paralysed) by applying small charges of electricity to the muscle to induce the movement. FES can be applied during rehabilitation stage to enhance the healing process. The d...

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Main Author:	Mohamed Nasir, Noorhamizah
Format:	Thesis
Language:	English English English
Published:	2017
Subjects:	RD Surgery
Online Access:	http://eprints.uthm.edu.my/351/1/24p%20NOORHAMIZAH%20MOHAMED%20NASIR.pdf http://eprints.uthm.edu.my/351/2/NOORHAMIZAH%20MOHAMED%20NASIR%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/351/3/NOORHAMIZAH%20MOHAMED%20NASIR%20WATERMARK.pdf
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spelling	my-uthm-ep.3512021-07-25T00:56:55Z Intelligent modelling and control with fatigue reduction for fes induced knee joint of hemiplegic for rehabilitation 2017-12 Mohamed Nasir, Noorhamizah RD Surgery Functional electrical stimulation (FES) is one of the treatment for the people with stroke such as hemiplegic body (half body paralysed) by applying small charges of electricity to the muscle to induce the movement. FES can be applied during rehabilitation stage to enhance the healing process. The development of the intelligent hemiplegic model of the knee joint and control strategies with fatigue reduction for the FES control application are the main concern of this thesis. Modelling the musculoskeletal is significantly challenging due to the complexity of the system. Development of the knee joint model that is capable of relating FES parameters is the first aim of this study. The knee joint model comprising of equations of motion to represent the segmental dynamics and PSO optimised Neural Network - ARX to represent quadriceps muscle properties was formulated. The results show that the muscle model developed gives an accurate dynamic characterisation. Development of the FES-induced extension and flexion motions control is the second aim of this study. To control the motor function of muscle by using external devices such as FES is one of the crucial issues. High nonlinearity and rapid change of muscle properties due to fatigue are the major problems of the FES control system. PSO optimised Fuzzy Logic Control (FLC) has been proposed to handle this complex nonlinear system. A natural trajectory control strategy by using the proposed control system has been assessed. There are two control strategies; knee movement control with and without minimised electrical stimulation were developed. The control problem was to design a FLC such that the knee joint track the desired trajectory as closely as possible. Then, both control strategies were investigated in terms of muscle fatigue. Multi objective PSO optimised FLC was used to minimise the amount of electrical stimulation in order to reduce the muscle fatigue. This control strategy has shown up to 32.6% minimisation of the electrical stimulation in the simulation studies and 35.89 % reduction the muscle fatigue in the experimental work. Therefore, this control strategy can be applied as FES control system for the treatment in rehabilitation to enhance the healing process for the stroke subjects such as hemiplegic patients. 2017-12 Thesis http://eprints.uthm.edu.my/351/ http://eprints.uthm.edu.my/351/1/24p%20NOORHAMIZAH%20MOHAMED%20NASIR.pdf text en public http://eprints.uthm.edu.my/351/2/NOORHAMIZAH%20MOHAMED%20NASIR%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/351/3/NOORHAMIZAH%20MOHAMED%20NASIR%20WATERMARK.pdf text en validuser phd doctoral Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	RD Surgery
spellingShingle	RD Surgery Mohamed Nasir, Noorhamizah Intelligent modelling and control with fatigue reduction for fes induced knee joint of hemiplegic for rehabilitation
description	Functional electrical stimulation (FES) is one of the treatment for the people with stroke such as hemiplegic body (half body paralysed) by applying small charges of electricity to the muscle to induce the movement. FES can be applied during rehabilitation stage to enhance the healing process. The development of the intelligent hemiplegic model of the knee joint and control strategies with fatigue reduction for the FES control application are the main concern of this thesis. Modelling the musculoskeletal is significantly challenging due to the complexity of the system. Development of the knee joint model that is capable of relating FES parameters is the first aim of this study. The knee joint model comprising of equations of motion to represent the segmental dynamics and PSO optimised Neural Network - ARX to represent quadriceps muscle properties was formulated. The results show that the muscle model developed gives an accurate dynamic characterisation. Development of the FES-induced extension and flexion motions control is the second aim of this study. To control the motor function of muscle by using external devices such as FES is one of the crucial issues. High nonlinearity and rapid change of muscle properties due to fatigue are the major problems of the FES control system. PSO optimised Fuzzy Logic Control (FLC) has been proposed to handle this complex nonlinear system. A natural trajectory control strategy by using the proposed control system has been assessed. There are two control strategies; knee movement control with and without minimised electrical stimulation were developed. The control problem was to design a FLC such that the knee joint track the desired trajectory as closely as possible. Then, both control strategies were investigated in terms of muscle fatigue. Multi objective PSO optimised FLC was used to minimise the amount of electrical stimulation in order to reduce the muscle fatigue. This control strategy has shown up to 32.6% minimisation of the electrical stimulation in the simulation studies and 35.89 % reduction the muscle fatigue in the experimental work. Therefore, this control strategy can be applied as FES control system for the treatment in rehabilitation to enhance the healing process for the stroke subjects such as hemiplegic patients.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Mohamed Nasir, Noorhamizah
author_facet	Mohamed Nasir, Noorhamizah
author_sort	Mohamed Nasir, Noorhamizah
title	Intelligent modelling and control with fatigue reduction for fes induced knee joint of hemiplegic for rehabilitation
title_short	Intelligent modelling and control with fatigue reduction for fes induced knee joint of hemiplegic for rehabilitation
title_full	Intelligent modelling and control with fatigue reduction for fes induced knee joint of hemiplegic for rehabilitation
title_fullStr	Intelligent modelling and control with fatigue reduction for fes induced knee joint of hemiplegic for rehabilitation
title_full_unstemmed	Intelligent modelling and control with fatigue reduction for fes induced knee joint of hemiplegic for rehabilitation
title_sort	intelligent modelling and control with fatigue reduction for fes induced knee joint of hemiplegic for rehabilitation
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2017
url	http://eprints.uthm.edu.my/351/1/24p%20NOORHAMIZAH%20MOHAMED%20NASIR.pdf http://eprints.uthm.edu.my/351/2/NOORHAMIZAH%20MOHAMED%20NASIR%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/351/3/NOORHAMIZAH%20MOHAMED%20NASIR%20WATERMARK.pdf
_version_	1747830589176676352

Intelligent modelling and control with fatigue reduction for fes induced knee joint of hemiplegic for rehabilitation

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