Performance analysis of an electrooculography-based on intelligent wheelchair motion control

The aim of this study is to analyse the performance of fuzzy logic-based control designed for a wheelchair motion control using the eye movement signals. These signals are acquired through electrooculography (EOG) technique. The EOG is a technique to acquire the eye movement signals from a person,...

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Main Authors:	Mohd. Noor, Nurul Muthmainnah, Ahmad, Salmiah
Format:	Conference or Workshop Item
Language:	English English
Published:	IEEE 2015
Subjects:	TJ212 Control engineering
Online Access:	http://irep.iium.edu.my/45172/ http://irep.iium.edu.my/45172/ http://irep.iium.edu.my/45172/ http://irep.iium.edu.my/45172/4/45172-Performance_Analysis_of_an_Electrooculography-Full_article.pdf http://irep.iium.edu.my/45172/7/ASCC-organizer.pdf

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recordtype	eprints
spelling	iium-451722018-03-06T00:30:29Z http://irep.iium.edu.my/45172/ Performance analysis of an electrooculography-based on intelligent wheelchair motion control Mohd. Noor, Nurul Muthmainnah Ahmad, Salmiah TJ212 Control engineering The aim of this study is to analyse the performance of fuzzy logic-based control designed for a wheelchair motion control using the eye movement signals. These signals are acquired through electrooculography (EOG) technique. The EOG is a technique to acquire the eye movement signals from a person, i.e tetraplegia, which the data obtained can be used as a main communication tool, for example in wheelchair motion control. In this project, the eye movement signals were classified using the fuzzy classifier (FC). Then, the PD-type fuzzy controller was successfully designed and tested on the wheelchair model, for wheelchair motion control. The wheelchair model system was developed using MSC. Visual Nastran. The eye movement signals that acquired through the EOG technique is acted as a motion input references. The simulation results obtained show that the PD-type fuzzy logic controller designed has successfully managed to track the input reference for linear motion set by the EOG signal. In this paper, the simulation results are focused for backward motion only. IEEE 2015 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/45172/4/45172-Performance_Analysis_of_an_Electrooculography-Full_article.pdf application/pdf en http://irep.iium.edu.my/45172/7/ASCC-organizer.pdf Mohd. Noor, Nurul Muthmainnah and Ahmad, Salmiah (2015) Performance analysis of an electrooculography-based on intelligent wheelchair motion control. In: 2015 10th Asian Control Conference (ASCC 2015), 31st May- 3rd June 2015, Kota Kinabalu, Sabah. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7244813 10.1109/ASCC.2015.7244813
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TJ212 Control engineering
spellingShingle	TJ212 Control engineering Mohd. Noor, Nurul Muthmainnah Ahmad, Salmiah Performance analysis of an electrooculography-based on intelligent wheelchair motion control
description	The aim of this study is to analyse the performance of fuzzy logic-based control designed for a wheelchair motion control using the eye movement signals. These signals are acquired through electrooculography (EOG) technique. The EOG is a technique to acquire the eye movement signals from a person, i.e tetraplegia, which the data obtained can be used as a main communication tool, for example in wheelchair motion control. In this project, the eye movement signals were classified using the fuzzy classifier (FC). Then, the PD-type fuzzy controller was successfully designed and tested on the wheelchair model, for wheelchair motion control. The wheelchair model system was developed using MSC. Visual Nastran. The eye movement signals that acquired through the EOG technique is acted as a motion input references. The simulation results obtained show that the PD-type fuzzy logic controller designed has successfully managed to track the input reference for linear motion set by the EOG signal. In this paper, the simulation results are focused for backward motion only.
format	Conference or Workshop Item
author	Mohd. Noor, Nurul Muthmainnah Ahmad, Salmiah
author_facet	Mohd. Noor, Nurul Muthmainnah Ahmad, Salmiah
author_sort	Mohd. Noor, Nurul Muthmainnah
title	Performance analysis of an electrooculography-based on intelligent wheelchair motion control
title_short	Performance analysis of an electrooculography-based on intelligent wheelchair motion control
title_full	Performance analysis of an electrooculography-based on intelligent wheelchair motion control
title_fullStr	Performance analysis of an electrooculography-based on intelligent wheelchair motion control
title_full_unstemmed	Performance analysis of an electrooculography-based on intelligent wheelchair motion control
title_sort	performance analysis of an electrooculography-based on intelligent wheelchair motion control
publisher	IEEE
publishDate	2015
url	http://irep.iium.edu.my/45172/ http://irep.iium.edu.my/45172/ http://irep.iium.edu.my/45172/ http://irep.iium.edu.my/45172/4/45172-Performance_Analysis_of_an_Electrooculography-Full_article.pdf http://irep.iium.edu.my/45172/7/ASCC-organizer.pdf
first_indexed	2023-09-18T21:04:18Z
last_indexed	2023-09-18T21:04:18Z
_version_	1777410830141227008

Performance analysis of an electrooculography-based on intelligent wheelchair motion control

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