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Minimizing Error Rate in Gaze Tracking System based on Electrooculogram using Machine Learning

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Abstract
Electrooculography is considered the most perceived signal processing system for distinguishing distinctive eye movements or eye-tracking. EOG signal is been utilized for extracting features for making reliable assistance for physically impaired patients. Extracting new features has been common and frequent in EOG studies.
EOG system is less expensive than any other signal processing system and it incorporates disadvantages, which is the error rate. In our study, we calculated the Euclidean distance error and we got significantly less error rate, which is 4.02 cm.
The principal objective of our study is to make a minimum error free EOG analysis. It is likewise less expensive than previous studies and this proposed strategy can be applied for continuous client experience for physically impaired patients inside a base expense.
Author(s)
아흐메드 나피즈 이슈티아크
Issued Date
2021
Awarded Date
2021-02
Type
Dissertation
URI
http://oak.ulsan.ac.kr/handle/2021.oak/5792
http://ulsan.dcollection.net/common/orgView/200000368931
Affiliation
울산대학교
Department
일반대학원 의용생체공학과
Advisor
Dr. Jihwan Woo
Degree
Master
Publisher
울산대학교 일반대학원 의용생체공학과
Language
eng
Rights
울산대학교 논문은 저작권에 의해 보호받습니다.
Appears in Collections:
Interdisciplinary Program of Medical & Biological Engineering > 1. Theses(Master)
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