Detecting and influencing driver emotions using psycho-physiological sensors and ambient light

Mariam Hassib, Michael Braun, Bastian Pfleging, Florian Alt

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Uittreksel

Driving is a sensitive task that is strongly affected by the driver's emotions. Negative emotions, such as anger, can evidently lead to more driving errors. In this work, we introduce a concept of detecting and influencing driver emotions using psycho-physiological sensing for emotion classification and ambient light for feedback. We detect arousal and valence of emotional responses from wearable bio-electric sensors, namely brain-computer interfaces and heart rate sensors. We evaluated our concept in a static driving simulator with a fully equipped car with 12 participants. Before the rides, we elicit negative emotions and evaluate driving performance and physiological data while driving under stressful conditions. We use three ambient lighting conditions (no light, blue, orange). Using a subject-dependent random forests classifier with 40 features collected from physiological data we achieve an average accuracy of 78.9% for classifying valence and 68.7% for arousal. Driving performance was enhanced in conditions where ambient lighting was introduced. Both blue and orange light helped drivers to improve lane keeping. We discuss insights from our study and provide design recommendations for designing emotion sensing and feedback systems in the car.
TaalEngels
TitelProceedings of the 17th IFIP TC.13 International Conference on Human-Computer Interaction
Plaats van productieCham
UitgeverijSpringer
Aantal pagina's22
StatusGepubliceerd - 2 sep 2019
Evenement17th IFIP TC.13 International Conference on Human-Computer Interaction (INTERACT2019) - Paphos, Cyprus
Duur: 2 sep 20196 sep 2019
https://interact2019.org/

Publicatie series

NaamINTERACT '19
UitgeverijSpringer

Congres

Congres17th IFIP TC.13 International Conference on Human-Computer Interaction (INTERACT2019)
Verkorte titelINTERACT2019
LandCyprus
StadPaphos
Periode2/09/196/09/19
Internet adres

Vingerafdruk

Sensors
Railroad cars
Lighting
Feedback
Brain computer interface
Classifiers
Simulators

Citeer dit

Hassib, M., Braun, M., Pfleging, B., & Alt, F. (2019). Detecting and influencing driver emotions using psycho-physiological sensors and ambient light. In Proceedings of the 17th IFIP TC.13 International Conference on Human-Computer Interaction (INTERACT '19). Cham: Springer.
Hassib, Mariam ; Braun, Michael ; Pfleging, Bastian ; Alt, Florian. / Detecting and influencing driver emotions using psycho-physiological sensors and ambient light. Proceedings of the 17th IFIP TC.13 International Conference on Human-Computer Interaction. Cham : Springer, 2019. (INTERACT '19).
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title = "Detecting and influencing driver emotions using psycho-physiological sensors and ambient light",
abstract = "Driving is a sensitive task that is strongly affected by the driver's emotions. Negative emotions, such as anger, can evidently lead to more driving errors. In this work, we introduce a concept of detecting and influencing driver emotions using psycho-physiological sensing for emotion classification and ambient light for feedback. We detect arousal and valence of emotional responses from wearable bio-electric sensors, namely brain-computer interfaces and heart rate sensors. We evaluated our concept in a static driving simulator with a fully equipped car with 12 participants. Before the rides, we elicit negative emotions and evaluate driving performance and physiological data while driving under stressful conditions. We use three ambient lighting conditions (no light, blue, orange). Using a subject-dependent random forests classifier with 40 features collected from physiological data we achieve an average accuracy of 78.9{\%} for classifying valence and 68.7{\%} for arousal. Driving performance was enhanced in conditions where ambient lighting was introduced. Both blue and orange light helped drivers to improve lane keeping. We discuss insights from our study and provide design recommendations for designing emotion sensing and feedback systems in the car.",
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Hassib, M, Braun, M, Pfleging, B & Alt, F 2019, Detecting and influencing driver emotions using psycho-physiological sensors and ambient light. in Proceedings of the 17th IFIP TC.13 International Conference on Human-Computer Interaction. INTERACT '19, Springer, Cham, Paphos, Cyprus, 2/09/19.

Detecting and influencing driver emotions using psycho-physiological sensors and ambient light. / Hassib, Mariam; Braun, Michael; Pfleging, Bastian; Alt, Florian.

Proceedings of the 17th IFIP TC.13 International Conference on Human-Computer Interaction. Cham : Springer, 2019. (INTERACT '19).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

TY - GEN

T1 - Detecting and influencing driver emotions using psycho-physiological sensors and ambient light

AU - Hassib,Mariam

AU - Braun,Michael

AU - Pfleging,Bastian

AU - Alt,Florian

PY - 2019/9/2

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N2 - Driving is a sensitive task that is strongly affected by the driver's emotions. Negative emotions, such as anger, can evidently lead to more driving errors. In this work, we introduce a concept of detecting and influencing driver emotions using psycho-physiological sensing for emotion classification and ambient light for feedback. We detect arousal and valence of emotional responses from wearable bio-electric sensors, namely brain-computer interfaces and heart rate sensors. We evaluated our concept in a static driving simulator with a fully equipped car with 12 participants. Before the rides, we elicit negative emotions and evaluate driving performance and physiological data while driving under stressful conditions. We use three ambient lighting conditions (no light, blue, orange). Using a subject-dependent random forests classifier with 40 features collected from physiological data we achieve an average accuracy of 78.9% for classifying valence and 68.7% for arousal. Driving performance was enhanced in conditions where ambient lighting was introduced. Both blue and orange light helped drivers to improve lane keeping. We discuss insights from our study and provide design recommendations for designing emotion sensing and feedback systems in the car.

AB - Driving is a sensitive task that is strongly affected by the driver's emotions. Negative emotions, such as anger, can evidently lead to more driving errors. In this work, we introduce a concept of detecting and influencing driver emotions using psycho-physiological sensing for emotion classification and ambient light for feedback. We detect arousal and valence of emotional responses from wearable bio-electric sensors, namely brain-computer interfaces and heart rate sensors. We evaluated our concept in a static driving simulator with a fully equipped car with 12 participants. Before the rides, we elicit negative emotions and evaluate driving performance and physiological data while driving under stressful conditions. We use three ambient lighting conditions (no light, blue, orange). Using a subject-dependent random forests classifier with 40 features collected from physiological data we achieve an average accuracy of 78.9% for classifying valence and 68.7% for arousal. Driving performance was enhanced in conditions where ambient lighting was introduced. Both blue and orange light helped drivers to improve lane keeping. We discuss insights from our study and provide design recommendations for designing emotion sensing and feedback systems in the car.

M3 - Conference contribution

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Hassib M, Braun M, Pfleging B, Alt F. Detecting and influencing driver emotions using psycho-physiological sensors and ambient light. In Proceedings of the 17th IFIP TC.13 International Conference on Human-Computer Interaction. Cham: Springer. 2019. (INTERACT '19).