Northampton Electronic Collection of Theses and Research

Eye-Tracking Assistive Technologies for Individuals with Amyotrophic Lateral Sclerosis

Edughele, H., Zhang, Y., Muhammad-Sukki, F., Vien, Q.-T., Morris-Cafiero, H. and Opoku Agyeman, M. (2022) Eye-Tracking Assistive Technologies for Individuals with Amyotrophic Lateral Sclerosis. IEEE Access. 2169-3536.

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Edughele_etal_IEEE_Access_2022_Eye-Tracking_Assistive_Technologies_for_Individuals_with_Amyotrophic_Lateral_Sclerosis_AAM
Edughele_etal_IEEE_Access_2022_Eye_Tracking_Assistive_Technologies_for_Individuals_with_Amyotrophic_Lateral_Sclerosis_AAM.pdf - Accepted Version
Available under License Creative Commons Attribution.
16544:35830
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Edughele_etal_IEEE_Access_2022_Eye-Tracking_Assistive_Technologies_for_Individuals_with_Amyotrophic_Lateral_Sclerosis
Edughele_etal_IEEE_Access_2022_Eye_Tracking_Assistive_Technologies_for_Individuals_with_Amyotrophic_Lateral_Sclerosis.pdf - Published Version
Available under License Creative Commons Attribution.
Information
Abstract:
Amyotrophic lateral sclerosis, also known as ALS, is a progressive nervous system disorder that affects nerve cells in the brain and spinal cord, resulting in the loss of muscle control. For individuals with ALS, where mobility is limited to the movement of the eyes, the use of eye-tracking-based applications can be applied to achieve some basic tasks with certain digital interfaces. This paper presents a review of existing eye-tracking software and hardware through which eye-tracking their application is sketched as an assistive technology to cope with ALS. Eye-tracking also provides a suitable alternative as control of game elements. Furthermore, artificial intelligence has been utilized to improve eye-tracking technology with significant improvement in calibration and accuracy. Gaps in literature are highlighted in the study to offer a direction for future research.
Uncontrolled Keywords:
/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Creators:
Edughele, H., Zhang, Y., Muhammad-Sukki, F., Vien, Q.-T., Morris-Cafiero, H. and Opoku Agyeman, M.
Faculties, Divisions and Institutes:
Faculties > Faculty of Arts, Science & Technology > Computing
?? ASART ??
Faculties > Faculty of Arts, Science & Technology
Date:
29 April 2022
Date Type:
Publication
Journal or Publication Title:
IEEE Access
Language:
English
DOI:
10.1109/ACCESS.2022.3164075
ISSN:
2169-3536
Status:
Published / Disseminated
Refereed:
Yes
Related URLs:
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