A multimodal psychological, physiological and behavioural dataset for human emotions in driving tasks

Date

2022-08-06

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Nature Publishing Group

Department

Type

Article

ISSN

2052-4463

Format

Free to read from

Citation

Li W, Tan R, Xing Y, et al., (2022) A multimodal psychological, physiological and behavioural dataset for human emotions in driving tasks, Scientific Data, Volume 9, 2022, Article number 481

Abstract

Human emotions are integral to daily tasks, and driving is now a typical daily task. Creating a multi-modal human emotion dataset in driving tasks is an essential step in human emotion studies. we conducted three experiments to collect multimodal psychological, physiological and behavioural dataset for human emotions (PPB-Emo). In Experiment I, 27 participants were recruited, the in-depth interview method was employed to explore the driver’s viewpoints on driving scenarios that induce different emotions. For Experiment II, 409 participants were recruited, a questionnaire survey was conducted to obtain driving scenarios information that induces human drivers to produce specific emotions, and the results were used as the basis for selecting video-audio stimulus materials. In Experiment III, 40 participants were recruited, and the psychological data and physiological data, as well as their behavioural data were collected of all participants in 280 times driving tasks. The PPB-Emo dataset will largely support the analysis of human emotion in driving tasks. Moreover, The PPB-Emo dataset will also benefit human emotion research in other daily tasks.

Description

Software Description

Software Language

Github

Keywords

electroencephalogram measurement, driving behaviour measurement, face expression, body gesture and road scenario measurement, emotion and personality, electroencephalography (EEG), driving simulator, visual observation method, self-reported scale

DOI

Rights

Attribution 4.0 International

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