Digital eye strain and fatigue recognition using electrooculogram signals and ultrasonic distance measurements
© 2018 IEEE. This paper presents a study of eye fatigue and strain caused by prolonged exposure to digital screens. Electrooculogram (EOG) signals were used to analyze eye movements, particularly saccades. This type of eye movement can be observed when a person is reading or looking out the window o...
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oai:animorepository.dlsu.edu.ph:faculty_research-18972022-11-18T00:48:32Z Digital eye strain and fatigue recognition using electrooculogram signals and ultrasonic distance measurements Billones, Robert Kerwin C. Bedruz, Rhen Anjerome R. Arcega, Madon L. Eustaqio, Gabriela A. Guehring, Diana Tupaz, Ramon P. Valenzuela, Ira C. Dadios, Elmer P. © 2018 IEEE. This paper presents a study of eye fatigue and strain caused by prolonged exposure to digital screens. Electrooculogram (EOG) signals were used to analyze eye movements, particularly saccades. This type of eye movement can be observed when a person is reading or looking out the window of a moving car. On the other hand, ultrasonic signals were used for distance measurement. EOG signals were obtained using the BIOPAC system, while Arduino-based board was used to collect ultrasonic signals. The experimental analysis determined the appropriate ergonomic distance between the computer monitor and the user when reading. The least number of saccades (average of 9.18) can be observed at 20-25 inches. This means there is less muscle movement and less eye strain, thus a lower risk of computer vision syndrome. This work can be used in a development of smart eyeglasses that automatically detects eye fatigue and strain. 2019-03-12T07:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/898 https://animorepository.dlsu.edu.ph/context/faculty_research/article/1897/type/native/viewcontent Faculty Research Work Animo Repository |
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© 2018 IEEE. This paper presents a study of eye fatigue and strain caused by prolonged exposure to digital screens. Electrooculogram (EOG) signals were used to analyze eye movements, particularly saccades. This type of eye movement can be observed when a person is reading or looking out the window of a moving car. On the other hand, ultrasonic signals were used for distance measurement. EOG signals were obtained using the BIOPAC system, while Arduino-based board was used to collect ultrasonic signals. The experimental analysis determined the appropriate ergonomic distance between the computer monitor and the user when reading. The least number of saccades (average of 9.18) can be observed at 20-25 inches. This means there is less muscle movement and less eye strain, thus a lower risk of computer vision syndrome. This work can be used in a development of smart eyeglasses that automatically detects eye fatigue and strain. |
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Billones, Robert Kerwin C. Bedruz, Rhen Anjerome R. Arcega, Madon L. Eustaqio, Gabriela A. Guehring, Diana Tupaz, Ramon P. Valenzuela, Ira C. Dadios, Elmer P. |
spellingShingle |
Billones, Robert Kerwin C. Bedruz, Rhen Anjerome R. Arcega, Madon L. Eustaqio, Gabriela A. Guehring, Diana Tupaz, Ramon P. Valenzuela, Ira C. Dadios, Elmer P. Digital eye strain and fatigue recognition using electrooculogram signals and ultrasonic distance measurements |
author_facet |
Billones, Robert Kerwin C. Bedruz, Rhen Anjerome R. Arcega, Madon L. Eustaqio, Gabriela A. Guehring, Diana Tupaz, Ramon P. Valenzuela, Ira C. Dadios, Elmer P. |
author_sort |
Billones, Robert Kerwin C. |
title |
Digital eye strain and fatigue recognition using electrooculogram signals and ultrasonic distance measurements |
title_short |
Digital eye strain and fatigue recognition using electrooculogram signals and ultrasonic distance measurements |
title_full |
Digital eye strain and fatigue recognition using electrooculogram signals and ultrasonic distance measurements |
title_fullStr |
Digital eye strain and fatigue recognition using electrooculogram signals and ultrasonic distance measurements |
title_full_unstemmed |
Digital eye strain and fatigue recognition using electrooculogram signals and ultrasonic distance measurements |
title_sort |
digital eye strain and fatigue recognition using electrooculogram signals and ultrasonic distance measurements |
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Animo Repository |
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2019 |
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https://animorepository.dlsu.edu.ph/faculty_research/898 https://animorepository.dlsu.edu.ph/context/faculty_research/article/1897/type/native/viewcontent |
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1751550429535141888 |