A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements

Gaze estimation, as a technique that reflects individual attention, can be used for disability assistance and assisting physicians in diagnosing diseases such as autism spectrum disorder (ASD), Parkinson’s disease, and attention deficit hyperactivity disorder (ADHD). Various techniques have been proposed for gaze estimation and achieved high resolution. Among these approaches, electrooculography (EOG)-based gaze estimation, as an economical and effective method, offers a promising solution for practical applications. Objective: In this paper, we systematically investigated the possible EOG electrode locations which are spatially distributed around the orbital cavity. Afterward, quantities of informative features to characterize physiological information of eye movement from the temporal-spectral domain are extracted from the seven differential channels. Methods and procedures: To select the optimum channels and relevant features, and eliminate irrelevant information, a heuristical search algorithm (i.e., forward stepwise strategy) is applied. Subsequently, a comparative analysis of the impacts of electrode placement and feature contributions on gaze estimation is evaluated via 6 classic models with 18 subjects. Results: Experimental results showed that the promising performance was achieved both in the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) within a wide gaze that ranges from −50° to +50°. The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. Compared with the prevailing EOG-based techniques, the performance improvement of MAE and RMSE range from 0.70° to 5.48° and 0.66° to 5.42°, respectively. Conclusion: We proposed a robust EOG-based gaze estimation approach by systematically investigating the optimal channel/feature combination. The experimental results indicated not only the superiority of the proposed approach but also its potential for clinical application. Clinical and translational impact statement: Accurate gaze estimation is a key step for assisting disabilities and accurate diagnosis of various diseases including ASD, Parkinson’s disease, and ADHD. The proposed approach can accurately estimate the points of gaze via EOG signals, and thus has the potential for various related medical applications. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Zheng Zeng [verfasserIn] Linkai Tao [verfasserIn] Hangyu Zhu [verfasserIn] Yunfeng Zhu [verfasserIn] Long Meng [verfasserIn] Jiahao Fan [verfasserIn] Chen Chen [verfasserIn] Wei Chen [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	Channel selection electrooculography (EOG) feature selection gaze estimation saccade

Übergeordnetes Werk:	In: IEEE Journal of Translational Engineering in Health and Medicine - IEEE, 2014, 12(2024), Seite 56-65
Übergeordnetes Werk:	volume:12 ; year:2024 ; pages:56-65

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/JTEHM.2023.3320713

Katalog-ID:	DOAJ099407728

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allfieldsGer	10.1109/JTEHM.2023.3320713 doi (DE-627)DOAJ099407728 (DE-599)DOAJ91d7472b87394a6dae53068bec623eff DE-627 ger DE-627 rakwb eng R858-859.7 R855-855.5 Zheng Zeng verfasserin aut A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gaze estimation, as a technique that reflects individual attention, can be used for disability assistance and assisting physicians in diagnosing diseases such as autism spectrum disorder (ASD), Parkinson’s disease, and attention deficit hyperactivity disorder (ADHD). Various techniques have been proposed for gaze estimation and achieved high resolution. Among these approaches, electrooculography (EOG)-based gaze estimation, as an economical and effective method, offers a promising solution for practical applications. Objective: In this paper, we systematically investigated the possible EOG electrode locations which are spatially distributed around the orbital cavity. Afterward, quantities of informative features to characterize physiological information of eye movement from the temporal-spectral domain are extracted from the seven differential channels. Methods and procedures: To select the optimum channels and relevant features, and eliminate irrelevant information, a heuristical search algorithm (i.e., forward stepwise strategy) is applied. Subsequently, a comparative analysis of the impacts of electrode placement and feature contributions on gaze estimation is evaluated via 6 classic models with 18 subjects. Results: Experimental results showed that the promising performance was achieved both in the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) within a wide gaze that ranges from −50° to +50°. The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. Compared with the prevailing EOG-based techniques, the performance improvement of MAE and RMSE range from 0.70° to 5.48° and 0.66° to 5.42°, respectively. Conclusion: We proposed a robust EOG-based gaze estimation approach by systematically investigating the optimal channel/feature combination. The experimental results indicated not only the superiority of the proposed approach but also its potential for clinical application. Clinical and translational impact statement: Accurate gaze estimation is a key step for assisting disabilities and accurate diagnosis of various diseases including ASD, Parkinson’s disease, and ADHD. The proposed approach can accurately estimate the points of gaze via EOG signals, and thus has the potential for various related medical applications. Channel selection electrooculography (EOG) feature selection gaze estimation saccade Computer applications to medicine. Medical informatics Medical technology Linkai Tao verfasserin aut Hangyu Zhu verfasserin aut Yunfeng Zhu verfasserin aut Long Meng verfasserin aut Jiahao Fan verfasserin aut Chen Chen verfasserin aut Wei Chen verfasserin aut In IEEE Journal of Translational Engineering in Health and Medicine IEEE, 2014 12(2024), Seite 56-65 (DE-627)733363032 (DE-600)2696555-0 21682372 nnns volume:12 year:2024 pages:56-65 https://doi.org/10.1109/JTEHM.2023.3320713 kostenfrei https://doaj.org/article/91d7472b87394a6dae53068bec623eff kostenfrei https://ieeexplore.ieee.org/document/10268026/ kostenfrei https://doaj.org/toc/2168-2372 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2024 56-65
allfieldsSound	10.1109/JTEHM.2023.3320713 doi (DE-627)DOAJ099407728 (DE-599)DOAJ91d7472b87394a6dae53068bec623eff DE-627 ger DE-627 rakwb eng R858-859.7 R855-855.5 Zheng Zeng verfasserin aut A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gaze estimation, as a technique that reflects individual attention, can be used for disability assistance and assisting physicians in diagnosing diseases such as autism spectrum disorder (ASD), Parkinson’s disease, and attention deficit hyperactivity disorder (ADHD). Various techniques have been proposed for gaze estimation and achieved high resolution. Among these approaches, electrooculography (EOG)-based gaze estimation, as an economical and effective method, offers a promising solution for practical applications. Objective: In this paper, we systematically investigated the possible EOG electrode locations which are spatially distributed around the orbital cavity. Afterward, quantities of informative features to characterize physiological information of eye movement from the temporal-spectral domain are extracted from the seven differential channels. Methods and procedures: To select the optimum channels and relevant features, and eliminate irrelevant information, a heuristical search algorithm (i.e., forward stepwise strategy) is applied. Subsequently, a comparative analysis of the impacts of electrode placement and feature contributions on gaze estimation is evaluated via 6 classic models with 18 subjects. Results: Experimental results showed that the promising performance was achieved both in the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) within a wide gaze that ranges from −50° to +50°. The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. Compared with the prevailing EOG-based techniques, the performance improvement of MAE and RMSE range from 0.70° to 5.48° and 0.66° to 5.42°, respectively. Conclusion: We proposed a robust EOG-based gaze estimation approach by systematically investigating the optimal channel/feature combination. The experimental results indicated not only the superiority of the proposed approach but also its potential for clinical application. Clinical and translational impact statement: Accurate gaze estimation is a key step for assisting disabilities and accurate diagnosis of various diseases including ASD, Parkinson’s disease, and ADHD. The proposed approach can accurately estimate the points of gaze via EOG signals, and thus has the potential for various related medical applications. Channel selection electrooculography (EOG) feature selection gaze estimation saccade Computer applications to medicine. Medical informatics Medical technology Linkai Tao verfasserin aut Hangyu Zhu verfasserin aut Yunfeng Zhu verfasserin aut Long Meng verfasserin aut Jiahao Fan verfasserin aut Chen Chen verfasserin aut Wei Chen verfasserin aut In IEEE Journal of Translational Engineering in Health and Medicine IEEE, 2014 12(2024), Seite 56-65 (DE-627)733363032 (DE-600)2696555-0 21682372 nnns volume:12 year:2024 pages:56-65 https://doi.org/10.1109/JTEHM.2023.3320713 kostenfrei https://doaj.org/article/91d7472b87394a6dae53068bec623eff kostenfrei https://ieeexplore.ieee.org/document/10268026/ kostenfrei https://doaj.org/toc/2168-2372 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2024 56-65
language	English
source	In IEEE Journal of Translational Engineering in Health and Medicine 12(2024), Seite 56-65 volume:12 year:2024 pages:56-65
sourceStr	In IEEE Journal of Translational Engineering in Health and Medicine 12(2024), Seite 56-65 volume:12 year:2024 pages:56-65
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topic_facet	Channel selection electrooculography (EOG) feature selection gaze estimation saccade Computer applications to medicine. Medical informatics Medical technology
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container_title	IEEE Journal of Translational Engineering in Health and Medicine
authorswithroles_txt_mv	Zheng Zeng @@aut@@ Linkai Tao @@aut@@ Hangyu Zhu @@aut@@ Yunfeng Zhu @@aut@@ Long Meng @@aut@@ Jiahao Fan @@aut@@ Chen Chen @@aut@@ Wei Chen @@aut@@
publishDateDaySort_date	2024-01-01T00:00:00Z
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callnumber-first	R - Medicine
author	Zheng Zeng
spellingShingle	Zheng Zeng misc R858-859.7 misc R855-855.5 misc Channel selection misc electrooculography (EOG) misc feature selection misc gaze estimation misc saccade misc Computer applications to medicine. Medical informatics misc Medical technology A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements
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issn	21682372
topic_title	R858-859.7 R855-855.5 A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements Channel selection electrooculography (EOG) feature selection gaze estimation saccade
topic	misc R858-859.7 misc R855-855.5 misc Channel selection misc electrooculography (EOG) misc feature selection misc gaze estimation misc saccade misc Computer applications to medicine. Medical informatics misc Medical technology
topic_unstemmed	misc R858-859.7 misc R855-855.5 misc Channel selection misc electrooculography (EOG) misc feature selection misc gaze estimation misc saccade misc Computer applications to medicine. Medical informatics misc Medical technology
topic_browse	misc R858-859.7 misc R855-855.5 misc Channel selection misc electrooculography (EOG) misc feature selection misc gaze estimation misc saccade misc Computer applications to medicine. Medical informatics misc Medical technology
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hierarchy_parent_title	IEEE Journal of Translational Engineering in Health and Medicine
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title	A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements
ctrlnum	(DE-627)DOAJ099407728 (DE-599)DOAJ91d7472b87394a6dae53068bec623eff
title_full	A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements
author_sort	Zheng Zeng
journal	IEEE Journal of Translational Engineering in Health and Medicine
journalStr	IEEE Journal of Translational Engineering in Health and Medicine
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lang_code	eng
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author_browse	Zheng Zeng Linkai Tao Hangyu Zhu Yunfeng Zhu Long Meng Jiahao Fan Chen Chen Wei Chen
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class	R858-859.7 R855-855.5
format_se	Elektronische Aufsätze
author-letter	Zheng Zeng
doi_str_mv	10.1109/JTEHM.2023.3320713
author2-role	verfasserin
title_sort	robust gaze estimation approach via exploring relevant electrooculogram features and optimal electrodes placements
callnumber	R858-859.7
title_auth	A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements
abstract	Gaze estimation, as a technique that reflects individual attention, can be used for disability assistance and assisting physicians in diagnosing diseases such as autism spectrum disorder (ASD), Parkinson’s disease, and attention deficit hyperactivity disorder (ADHD). Various techniques have been proposed for gaze estimation and achieved high resolution. Among these approaches, electrooculography (EOG)-based gaze estimation, as an economical and effective method, offers a promising solution for practical applications. Objective: In this paper, we systematically investigated the possible EOG electrode locations which are spatially distributed around the orbital cavity. Afterward, quantities of informative features to characterize physiological information of eye movement from the temporal-spectral domain are extracted from the seven differential channels. Methods and procedures: To select the optimum channels and relevant features, and eliminate irrelevant information, a heuristical search algorithm (i.e., forward stepwise strategy) is applied. Subsequently, a comparative analysis of the impacts of electrode placement and feature contributions on gaze estimation is evaluated via 6 classic models with 18 subjects. Results: Experimental results showed that the promising performance was achieved both in the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) within a wide gaze that ranges from −50° to +50°. The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. Compared with the prevailing EOG-based techniques, the performance improvement of MAE and RMSE range from 0.70° to 5.48° and 0.66° to 5.42°, respectively. Conclusion: We proposed a robust EOG-based gaze estimation approach by systematically investigating the optimal channel/feature combination. The experimental results indicated not only the superiority of the proposed approach but also its potential for clinical application. Clinical and translational impact statement: Accurate gaze estimation is a key step for assisting disabilities and accurate diagnosis of various diseases including ASD, Parkinson’s disease, and ADHD. The proposed approach can accurately estimate the points of gaze via EOG signals, and thus has the potential for various related medical applications.
abstractGer	Gaze estimation, as a technique that reflects individual attention, can be used for disability assistance and assisting physicians in diagnosing diseases such as autism spectrum disorder (ASD), Parkinson’s disease, and attention deficit hyperactivity disorder (ADHD). Various techniques have been proposed for gaze estimation and achieved high resolution. Among these approaches, electrooculography (EOG)-based gaze estimation, as an economical and effective method, offers a promising solution for practical applications. Objective: In this paper, we systematically investigated the possible EOG electrode locations which are spatially distributed around the orbital cavity. Afterward, quantities of informative features to characterize physiological information of eye movement from the temporal-spectral domain are extracted from the seven differential channels. Methods and procedures: To select the optimum channels and relevant features, and eliminate irrelevant information, a heuristical search algorithm (i.e., forward stepwise strategy) is applied. Subsequently, a comparative analysis of the impacts of electrode placement and feature contributions on gaze estimation is evaluated via 6 classic models with 18 subjects. Results: Experimental results showed that the promising performance was achieved both in the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) within a wide gaze that ranges from −50° to +50°. The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. Compared with the prevailing EOG-based techniques, the performance improvement of MAE and RMSE range from 0.70° to 5.48° and 0.66° to 5.42°, respectively. Conclusion: We proposed a robust EOG-based gaze estimation approach by systematically investigating the optimal channel/feature combination. The experimental results indicated not only the superiority of the proposed approach but also its potential for clinical application. Clinical and translational impact statement: Accurate gaze estimation is a key step for assisting disabilities and accurate diagnosis of various diseases including ASD, Parkinson’s disease, and ADHD. The proposed approach can accurately estimate the points of gaze via EOG signals, and thus has the potential for various related medical applications.
abstract_unstemmed	Gaze estimation, as a technique that reflects individual attention, can be used for disability assistance and assisting physicians in diagnosing diseases such as autism spectrum disorder (ASD), Parkinson’s disease, and attention deficit hyperactivity disorder (ADHD). Various techniques have been proposed for gaze estimation and achieved high resolution. Among these approaches, electrooculography (EOG)-based gaze estimation, as an economical and effective method, offers a promising solution for practical applications. Objective: In this paper, we systematically investigated the possible EOG electrode locations which are spatially distributed around the orbital cavity. Afterward, quantities of informative features to characterize physiological information of eye movement from the temporal-spectral domain are extracted from the seven differential channels. Methods and procedures: To select the optimum channels and relevant features, and eliminate irrelevant information, a heuristical search algorithm (i.e., forward stepwise strategy) is applied. Subsequently, a comparative analysis of the impacts of electrode placement and feature contributions on gaze estimation is evaluated via 6 classic models with 18 subjects. Results: Experimental results showed that the promising performance was achieved both in the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) within a wide gaze that ranges from −50° to +50°. The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. Compared with the prevailing EOG-based techniques, the performance improvement of MAE and RMSE range from 0.70° to 5.48° and 0.66° to 5.42°, respectively. Conclusion: We proposed a robust EOG-based gaze estimation approach by systematically investigating the optimal channel/feature combination. The experimental results indicated not only the superiority of the proposed approach but also its potential for clinical application. Clinical and translational impact statement: Accurate gaze estimation is a key step for assisting disabilities and accurate diagnosis of various diseases including ASD, Parkinson’s disease, and ADHD. The proposed approach can accurately estimate the points of gaze via EOG signals, and thus has the potential for various related medical applications.
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title_short	A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements
url	https://doi.org/10.1109/JTEHM.2023.3320713 https://doaj.org/article/91d7472b87394a6dae53068bec623eff https://ieeexplore.ieee.org/document/10268026/ https://doaj.org/toc/2168-2372
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author2	Linkai Tao Hangyu Zhu Yunfeng Zhu Long Meng Jiahao Fan Chen Chen Wei Chen
author2Str	Linkai Tao Hangyu Zhu Yunfeng Zhu Long Meng Jiahao Fan Chen Chen Wei Chen
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up_date	2024-07-03T22:38:25.318Z
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