Prabhakar, G and Madhu, N and Biswas, P (2018) Comparing pupil dilation, head movement, and EEG for distraction detection of drivers. In: 32nd International BCS Human Computer Interaction Conference, HCI 2018, 4 - 6 July 2018, Belfast.
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Abstract
This paper investigates the use of pupil dilation, head movement and EEG for detecting distraction and cognitive load of drivers while performing secondary tasks in an automotive environment. We tracked pupil dilation from Tobii Pro Glasses 2, head movement from Kinect and EEG from Emotive Insight system. We have analyzed data using Fast Fourier Transform, Continuous Wavelet Transform, and Discrete Wavelet Transform for the full-length signal as well as in windows of 1 second for real-time implementation. We investigated detection of distraction and cognitive load from three different conditions - free driving, driving with lane change, driving with lane change and operating secondary task for each participant in a driving simulator. Our results show that the pupil dilation, head yaw, and EEG can detect the increase in cognitive load due to operation of secondary task within a time buffer of 1 second which can be adapted for real-time implementation. We have also found that FFT of Pupil dilation shows significant categorization of normal and distracted states than the categorization by DWT which contrasts with state of the art methods. Finally, we have proposed an expert system to alert drivers utilizing the signal processing analysis.
Item Type: | Conference Paper |
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Publication: | Proceedings of the 32nd International BCS Human Computer Interaction Conference, HCI 2018 |
Publisher: | BCS Learning and Development Ltd. |
Additional Information: | The copyright for this article belongs to the Authors. |
Keywords: | Discrete wavelet transforms; Electroencephalography; Expert systems; Fast Fourier transforms; Real time control; Signal reconstruction; Truck drivers, Automotive; Cognitive loads; Distraction; Head yaw; Pupil dilation, Human computer interaction |
Department/Centre: | Division of Mechanical Sciences > Centre for Product Design & Manufacturing |
Date Deposited: | 02 Sep 2022 04:09 |
Last Modified: | 02 Sep 2022 04:09 |
URI: | https://eprints.iisc.ac.in/id/eprint/76355 |
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