EEG, EOG, Likert Scale, and Interview Approaches for Assessing Stressful Hazard Perception Scenarios.
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| Title: | EEG, EOG, Likert Scale, and Interview Approaches for Assessing Stressful Hazard Perception Scenarios. |
|---|---|
| Authors: | Rui, Zhepeng1 (AUTHOR), Li, Yahong1 (AUTHOR), Dong, Zhanxun1 (AUTHOR), Hao, Lingyu1 (AUTHOR), Chen, Bingliang1 (AUTHOR), Chang, Fangyuan1 (AUTHOR), Gu, Zhenyu1 (AUTHOR) zygu@sjtu.edu.cn |
| Source: | International Journal of Human-Computer Interaction. May2025, Vol. 41 Issue 9, p5199-5224. 26p. |
| Subjects: | Risk perception, Likert scale, Electrooculography, Electroencephalography, Automobile driving |
| Abstract: | This study aimed to detect stressful hazard perception scenarios subjectively and objectively when using intelligent driving systems. We used electrooculography (EOG), electroencephalography (EEG), subjective ratings, and interviews to identify potential stressful hazard perceptions and record improvements in an intelligent navigation-guided pilot (NGP) system. Moreover, we analyzed electrophysiological data. Our study contributes to the use of engagement, concentration, and phase locking value connectivity based on EEG to support previous research methodologies using beta power, pupil size, fixation ratio, fixation duration, and subjective evaluations for investigating hazard perception. Our analyses showed that stressful hazard perception scenarios occurred mainly when encountering broken and solid lines, frequent lane changes, cars approaching suddenly, several cars driving in parallel, and the decision to change lanes but immediately pulling back upon using the NPG system. Our findings shed light on obtaining accurate results based on subjective and objective evaluations for developing intelligent driving systems. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 184789239 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: EEG, EOG, Likert Scale, and Interview Approaches for Assessing Stressful Hazard Perception Scenarios. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rui%2C+Zhepeng%22">Rui, Zhepeng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Yahong%22">Li, Yahong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dong%2C+Zhanxun%22">Dong, Zhanxun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hao%2C+Lingyu%22">Hao, Lingyu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Bingliang%22">Chen, Bingliang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chang%2C+Fangyuan%22">Chang, Fangyuan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gu%2C+Zhenyu%22">Gu, Zhenyu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zygu@sjtu.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. May2025, Vol. 41 Issue 9, p5199-5224. 26p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Risk+perception%22">Risk perception</searchLink><br /><searchLink fieldCode="DE" term="%22Likert+scale%22">Likert scale</searchLink><br /><searchLink fieldCode="DE" term="%22Electrooculography%22">Electrooculography</searchLink><br /><searchLink fieldCode="DE" term="%22Electroencephalography%22">Electroencephalography</searchLink><br /><searchLink fieldCode="DE" term="%22Automobile+driving%22">Automobile driving</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study aimed to detect stressful hazard perception scenarios subjectively and objectively when using intelligent driving systems. We used electrooculography (EOG), electroencephalography (EEG), subjective ratings, and interviews to identify potential stressful hazard perceptions and record improvements in an intelligent navigation-guided pilot (NGP) system. Moreover, we analyzed electrophysiological data. Our study contributes to the use of engagement, concentration, and phase locking value connectivity based on EEG to support previous research methodologies using beta power, pupil size, fixation ratio, fixation duration, and subjective evaluations for investigating hazard perception. Our analyses showed that stressful hazard perception scenarios occurred mainly when encountering broken and solid lines, frequent lane changes, cars approaching suddenly, several cars driving in parallel, and the decision to change lanes but immediately pulling back upon using the NPG system. Our findings shed light on obtaining accurate results based on subjective and objective evaluations for developing intelligent driving systems. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=184789239 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/10447318.2024.2358461 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 26 StartPage: 5199 Subjects: – SubjectFull: Risk perception Type: general – SubjectFull: Likert scale Type: general – SubjectFull: Electrooculography Type: general – SubjectFull: Electroencephalography Type: general – SubjectFull: Automobile driving Type: general Titles: – TitleFull: EEG, EOG, Likert Scale, and Interview Approaches for Assessing Stressful Hazard Perception Scenarios. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rui, Zhepeng – PersonEntity: Name: NameFull: Li, Yahong – PersonEntity: Name: NameFull: Dong, Zhanxun – PersonEntity: Name: NameFull: Hao, Lingyu – PersonEntity: Name: NameFull: Chen, Bingliang – PersonEntity: Name: NameFull: Chang, Fangyuan – PersonEntity: Name: NameFull: Gu, Zhenyu IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10447318 Numbering: – Type: volume Value: 41 – Type: issue Value: 9 Titles: – TitleFull: International Journal of Human-Computer Interaction Type: main |
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