Discrimination of healthy controls and selected visually impaired through visually evoked potentials

This thesis presents a digital signal processing based detection of healthy controls and selected visually impaired through visually evoked potentials (VEP). Visual impairment is a term used by ophthalmologist to describe any kind of vision loss, whether it's partial or total vision loss. Some...

Full description

Saved in:

Bibliographic Details
Main Author:	Vikneswaran, Vijean
Format:	Thesis
Language:	English
Subjects:	Digital signal processing Visually evoked potentials (VEP) Healthy controls Detection Visual impairment
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/44135/1/p.%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/44135/2/full%20text.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-unimap-44135
record_format	uketd_dc
spelling	my-unimap-441352016-11-22T10:28:41Z Discrimination of healthy controls and selected visually impaired through visually evoked potentials Vikneswaran, Vijean This thesis presents a digital signal processing based detection of healthy controls and selected visually impaired through visually evoked potentials (VEP). Visual impairment is a term used by ophthalmologist to describe any kind of vision loss, whether it's partial or total vision loss. Some of the conventionally used techniques for the investigation of vision impairments include fundoscopy imaging, ultrasound imaging, and manual inspection of retina. These techniques have several disadvantages such as poor quality of images produced by the ultrasound imaging, require experts, and are prone to error in manual inspection. The VEP provides an objective method for the diagnostics of vision impairments in patients. VEP is an electrical signal generated by the brain (Occipital Cortex) in response to a visual stimulus. By analyzing these responses, the abnormalities in the visual pathways of a person can be detected. The development of feature extraction and classification algorithms for investigation of vision impairments through VEPs however is still at an infancy level. Therefore, this study was carried out to investigate the time, frequency, and time-scale/frequency characteristics of the single trial transient VEPs, and propose an efficient feature extraction and classification algorithm for distinguishing the vision impairments. Four different feature extraction methods based on time, frequency, wavelet, and Stockwell transform were explored and statistical features were proposed for the VEP analysis. A new feature augmentation technique was proposed to enhance the variation of the data prior to the analysis. Three different feature reduction techniques were used to reduce the dimensional space of the features. Extreme learning machine, least square support vector machine and probabilistic neural networks were employed to evaluate the performance of the features in discriminating the vision impairments. Statistical analysis were used to demonstrate the significance of the preprocessed features, while performance measures such as sensitivity, specificity, positive predictivity, negative predictivity, and overall accuracy was considered for the evaluation of the classifiers. The dataset from two different experimental settings were used in the analysis. The first experiment was conducted to investigate the effect of different sizes of checkerboard stimulus to the resulting evoked responses while the second experiment was perpetrated to investigate the performance of the new colour fusioned checkerboard stimulus in elicitating reliable VEP responses. The experimental investigation elucidate that features derived from the VEP elicited by the proposed stimulus performed well in classifying the vision impairments. Promising 100% accuracy was achieved using the combinations of the proposed stimulus and feature extraction methods. Universiti Malaysia Perlis (UniMAP) 2014 Thesis en http://dspace.unimap.edu.my:80/xmlui/handle/123456789/44135 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/44135/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/44135/1/p.%201-24.pdf 0b9dba9b47704f8fe983cac33e499211 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/44135/2/full%20text.pdf 19565ee65cb78648af5072f4099b11a2 Digital signal processing Visually evoked potentials (VEP) Healthy controls Detection Visual impairment School of Mechatronic Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
topic	Digital signal processing Visually evoked potentials (VEP) Healthy controls Detection Visual impairment
spellingShingle	Digital signal processing Visually evoked potentials (VEP) Healthy controls Detection Visual impairment Vikneswaran, Vijean Discrimination of healthy controls and selected visually impaired through visually evoked potentials
description	This thesis presents a digital signal processing based detection of healthy controls and selected visually impaired through visually evoked potentials (VEP). Visual impairment is a term used by ophthalmologist to describe any kind of vision loss, whether it's partial or total vision loss. Some of the conventionally used techniques for the investigation of vision impairments include fundoscopy imaging, ultrasound imaging, and manual inspection of retina. These techniques have several disadvantages such as poor quality of images produced by the ultrasound imaging, require experts, and are prone to error in manual inspection. The VEP provides an objective method for the diagnostics of vision impairments in patients. VEP is an electrical signal generated by the brain (Occipital Cortex) in response to a visual stimulus. By analyzing these responses, the abnormalities in the visual pathways of a person can be detected. The development of feature extraction and classification algorithms for investigation of vision impairments through VEPs however is still at an infancy level. Therefore, this study was carried out to investigate the time, frequency, and time-scale/frequency characteristics of the single trial transient VEPs, and propose an efficient feature extraction and classification algorithm for distinguishing the vision impairments. Four different feature extraction methods based on time, frequency, wavelet, and Stockwell transform were explored and statistical features were proposed for the VEP analysis. A new feature augmentation technique was proposed to enhance the variation of the data prior to the analysis. Three different feature reduction techniques were used to reduce the dimensional space of the features. Extreme learning machine, least square support vector machine and probabilistic neural networks were employed to evaluate the performance of the features in discriminating the vision impairments. Statistical analysis were used to demonstrate the significance of the preprocessed features, while performance measures such as sensitivity, specificity, positive predictivity, negative predictivity, and overall accuracy was considered for the evaluation of the classifiers. The dataset from two different experimental settings were used in the analysis. The first experiment was conducted to investigate the effect of different sizes of checkerboard stimulus to the resulting evoked responses while the second experiment was perpetrated to investigate the performance of the new colour fusioned checkerboard stimulus in elicitating reliable VEP responses. The experimental investigation elucidate that features derived from the VEP elicited by the proposed stimulus performed well in classifying the vision impairments. Promising 100% accuracy was achieved using the combinations of the proposed stimulus and feature extraction methods.
format	Thesis
author	Vikneswaran, Vijean
author_facet	Vikneswaran, Vijean
author_sort	Vikneswaran, Vijean
title	Discrimination of healthy controls and selected visually impaired through visually evoked potentials
title_short	Discrimination of healthy controls and selected visually impaired through visually evoked potentials
title_full	Discrimination of healthy controls and selected visually impaired through visually evoked potentials
title_fullStr	Discrimination of healthy controls and selected visually impaired through visually evoked potentials
title_full_unstemmed	Discrimination of healthy controls and selected visually impaired through visually evoked potentials
title_sort	discrimination of healthy controls and selected visually impaired through visually evoked potentials
granting_institution	Universiti Malaysia Perlis (UniMAP)
granting_department	School of Mechatronic Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/44135/1/p.%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/44135/2/full%20text.pdf
_version_	1747836827690074112

Discrimination of healthy controls and selected visually impaired through visually evoked potentials

Similar Items