Comparing Pupil Dilation, Head Movement, and EEG for Distraction Detection of Drivers

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Comparing Pupil Dilation, Head Movement, and EEG for Distraction Detection of Drivers

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Author(s): Gowdham Prabhakar , N Madhu , Pradipta Biswas

Publication date (Print): July 2018

Conference name: Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

Conference theme: Human Computer Interaction Conference

Conference date: 4 - 6 July 2018

Keywords: Cognitive load, distraction, drivers, automotive, pupil dilation, head yaw, EEG, FFT, DWT, CWT

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Abstract

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Author and article information

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Gowdham Prabhakar

N Madhu

Pradipta Biswas

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Publication date: July 2018

Publication date (Print): July 2018

Pages: 1-5

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[0001]Centre for Product Design and Manufacturing

Indian Institute of Science, Bangalore, India

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DOI: 10.14236/ewic/HCI2018.69

SO-VID: 2c92a20a-a456-4ea3-bac5-cf9c5f2588fa

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This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: Proceedings of the 32nd International BCS Human Computer Interaction Conference

Conference acronym: HCI

Conference number: 32

Conference location: Belfast, UK

Conference date: 4 - 6 July 2018

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: Human Computer Interaction Conference

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1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/HCI2018.69

Self URI (journal page): https://ewic.bcs.org/

REFERENCES

S. AfzalP. Robinson 2009 September Natural affect data—Collection & annotation in a learning context In Affective Computing and Intelligent Interaction and Workshops 2009 ACII 2009 3rd International Conference on 1 7 IEEE
O. BasirJ. P. BhavnaniF. KarrayK. Desrochers 2004 Drowsiness detection system, US 6822573 B2
P. BiswasG. Prabhakar 2018 Detecting drivers’ cognitive load from saccadic intrusion Transportation research part F: traffic psychology and behaviour 54 63 78
H. BorilS. O. SadjadiJ. H. L. Hansen 2011 UTDrive: Emotion and cognitive load classification in-vehicle scenarios. In Proceeding of the 5th biennial workshop on DSP for in-vehicle systems
A. T. DuchowskiK. KrejtzI. KrejtzC. BieleA. NiedzielskaP. KieferI. Giannopoulos 2018 April The Index of Pupillary Activity: Measuring Cognitive Load vis-à-vis Task Difficulty with Pupil Oscillation In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems 282 ACM
R. GavasD. ChatterjeeA. Sinha 2017),“Estimation of cognitive load based on the pupil size dilation,” 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Banff, AB 2017 1499 1504
J. A. HealeyR. W. Picard 2011 Detecting stress during real-world driving tasks using physiological sensors IEEE Transactions on Intelligent Transportation Systems 6 2 156 166
E. H. Hess 1975 The tell-tale eye Van Nostrand Reinhold Company
Y. C. LeeJ. D. LeeNg L. Boyle 2007 Visual attention in driving: the effects of cognitive load and visual disruption Human Factors 49 4 721 733
Y. LiangJ. D. Lee 2014 A hybrid bayesian network approach to detect driver cognitive ditraction Transportation Research Part C 38 146 155
S. Marshall 2002 The index of cognitive activity: Measuring cognitive workload In Proc. 7th conference on human factors and power plants 7 5
S. Marshall 2007 Identifying cognitive state from eye metrics Aviation, Space, and Environmental Medicine 78 1 B165 B175
O. PalinkoA. L. KunA. ShyrokovP. Heeman 2010 Estimating cognitive load using remote eye tracking in a driving simulator In Proceedings of the 2010 symposium on eye-tracking research & applications 141 144
G. PrabhakarP. Biswas 2018 Eye Gaze Controlled Projected Display in Automotive and Military Aviation Environments Multimodal Technologies and Interaction 2 1 1
T. A. RanneyG. H. BaldwinL. A. SmithJ. MartinE. N. Mazzae 2013 Driver behavior during visual-manual secondary task performance: occlusion method versus simulated driving No. DOT HS 811 726
E. Redlich 1908 Ueber ein eigenartiges Pupillenphänomen; zugleich ein Beitrag zur Frage der hysterischen Pupillenstarre Deutsche medizinischeWochenschrift 34 313 315
T. M. SezginP. Robinson 2007 September Affective video data collection using an automobile simulator In International Conference on Affective Computing and Intelligent Interaction 770 771 Springer Berlin, Heidelberg
S. TokudaG. ObinataE. PalmerA. Chaparo 2011 Estimation of mental workload using saccadic eye movements in a free-viewing task In 23rd international conference of the IEEE EMBS 4523 4529
A. Westphal 1907 Ueber ein im katatonischen stupor beobachtetes Pupillenphänomen sowie Bemerkungen über die Pupillenstarre bei Hysterie Deutsche medizinische Wochenschrift 33 1080 1084
Y. YoshidaH. OhwadaF. MizoguchiH. Iwasaki 2014 Classifying cognitive load and driving situation with machine learning International Journal of Machine Learning and Computing 4 3 210
Z. ZengM. PanticG.I. RoismanT.S. Huang 2009 “A Survey of Affect Recognition Methods: Audio Visual & Spontaneous Expressions” IEEE Trans. PAMI 31 1 39 58

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Comment on this article

[1] S. AfzalP. Robinson 2009 September Natural affect data—Collection & annotation in a learning context In Affective Computing and Intelligent Interaction and Workshops 2009 ACII 2009 3rd International Conference on 1 7 IEEE

[2] O. BasirJ. P. BhavnaniF. KarrayK. Desrochers 2004 Drowsiness detection system, US 6822573 B2

[3] P. BiswasG. Prabhakar 2018 Detecting drivers’ cognitive load from saccadic intrusion Transportation research part F: traffic psychology and behaviour 54 63 78

[4] H. BorilS. O. SadjadiJ. H. L. Hansen 2011 UTDrive: Emotion and cognitive load classification in-vehicle scenarios. In Proceeding of the 5th biennial workshop on DSP for in-vehicle systems

[5] A. T. DuchowskiK. KrejtzI. KrejtzC. BieleA. NiedzielskaP. KieferI. Giannopoulos 2018 April The Index of Pupillary Activity: Measuring Cognitive Load vis-à-vis Task Difficulty with Pupil Oscillation In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems 282 ACM

[6] R. GavasD. ChatterjeeA. Sinha 2017),“Estimation of cognitive load based on the pupil size dilation,” 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Banff, AB 2017 1499 1504

[7] J. A. HealeyR. W. Picard 2011 Detecting stress during real-world driving tasks using physiological sensors IEEE Transactions on Intelligent Transportation Systems 6 2 156 166

[8] E. H. Hess 1975 The tell-tale eye Van Nostrand Reinhold Company

[9] Y. C. LeeJ. D. LeeNg L. Boyle 2007 Visual attention in driving: the effects of cognitive load and visual disruption Human Factors 49 4 721 733

[10] Y. LiangJ. D. Lee 2014 A hybrid bayesian network approach to detect driver cognitive ditraction Transportation Research Part C 38 146 155

[11] S. Marshall 2002 The index of cognitive activity: Measuring cognitive workload In Proc. 7th conference on human factors and power plants 7 5

[12] S. Marshall 2007 Identifying cognitive state from eye metrics Aviation, Space, and Environmental Medicine 78 1 B165 B175

[13] O. PalinkoA. L. KunA. ShyrokovP. Heeman 2010 Estimating cognitive load using remote eye tracking in a driving simulator In Proceedings of the 2010 symposium on eye-tracking research & applications 141 144

[14] G. PrabhakarP. Biswas 2018 Eye Gaze Controlled Projected Display in Automotive and Military Aviation Environments Multimodal Technologies and Interaction 2 1 1

[15] T. A. RanneyG. H. BaldwinL. A. SmithJ. MartinE. N. Mazzae 2013 Driver behavior during visual-manual secondary task performance: occlusion method versus simulated driving No. DOT HS 811 726

[16] E. Redlich 1908 Ueber ein eigenartiges Pupillenphänomen; zugleich ein Beitrag zur Frage der hysterischen Pupillenstarre Deutsche medizinischeWochenschrift 34 313 315

[17] T. M. SezginP. Robinson 2007 September Affective video data collection using an automobile simulator In International Conference on Affective Computing and Intelligent Interaction 770 771 Springer Berlin, Heidelberg

[18] S. TokudaG. ObinataE. PalmerA. Chaparo 2011 Estimation of mental workload using saccadic eye movements in a free-viewing task In 23rd international conference of the IEEE EMBS 4523 4529

[19] A. Westphal 1907 Ueber ein im katatonischen stupor beobachtetes Pupillenphänomen sowie Bemerkungen über die Pupillenstarre bei Hysterie Deutsche medizinische Wochenschrift 33 1080 1084

[20] Y. YoshidaH. OhwadaF. MizoguchiH. Iwasaki 2014 Classifying cognitive load and driving situation with machine learning International Journal of Machine Learning and Computing 4 3 210

[21] Z. ZengM. PanticG.I. RoismanT.S. Huang 2009 “A Survey of Affect Recognition Methods: Audio Visual & Spontaneous Expressions” IEEE Trans. PAMI 31 1 39 58

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Comparing Pupil Dilation, Head Movement, and EEG for Distraction Detection of Drivers

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