Pupil and Electromyography (EMG) Responses to Collision Warning in a Real Driving Environment

Xiaonan Yang*, Jung Hyup Kim

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The purpose of this study is to assess drivers’ upcoming decisions to collision warnings by analyzing their pupil and electromyography (EMG) responses in a real driving environment. Twenty male college students participated in this study. Tobii Glasses2 and electromyography MYO armbands were used to collect the physiological data. Forward collision warning (FCW) and lane departure warning (LDW) were generated from aftermarket CAT devices. According to the results, we found that different fluctuating patterns of pupil and electromyography responses exist when drivers responded to a collision warning. The potential causality between pupil diameter changes and normalized EMG could be applied as a valid indicator of drivers’ different cognitive status to the responded warning and ignored warning, which contains valuable or useless information. Findings from this study will contribute to future algorithm development in a next-generation smart vehicle that can not only identify and predict drivers’ upcoming responses but also customize warning functions based on drivers’ status.

Original languageEnglish
Title of host publicationHuman-Computer Interaction. Technological Innovation - Thematic Area, HCI 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Proceedings
EditorsMasaaki Kurosu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages415-423
Number of pages9
ISBN (Print)9783031054082
DOIs
Publication statusPublished - 2022
EventHuman Computer Interaction thematic area of the 24th International Conference on Human-Computer Interaction, HCII 2022 - Virtual, Online
Duration: 26 Jun 20221 Jul 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13303 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceHuman Computer Interaction thematic area of the 24th International Conference on Human-Computer Interaction, HCII 2022
CityVirtual, Online
Period26/06/221/07/22

Keywords

  • Collision warning
  • Electromyography (EMG)
  • Human cognitive behavior
  • Pupillary response

Fingerprint

Dive into the research topics of 'Pupil and Electromyography (EMG) Responses to Collision Warning in a Real Driving Environment'. Together they form a unique fingerprint.

Cite this