ArticleScientific data2022
A multimodal psychological, physiological and behavioural dataset for human emotions in driving tasks.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 71 citations in OpenAlex.
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- A VibV Dataset Integrating Vibration and Vision for Enhanced Safety in Self-Driving Tasks.Scientific data · 2025Article
- A Multidimensional Benchmark of Public EEG Datasets for Driver State Monitoring in Brain-Computer Interfaces.Sensors (Basel, Switzerland) · 2025Review
- [Design and validation of a multimodal model integrating text and imaging data for intelligent assessment of psychological stress in college students].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2025Article
- A Review of 25 Spontaneous and Dynamic Facial Expression Databases of Basic Emotions.Affective science · 2025Review
- A Dataset on Takeover during Distracted L2 Automated Driving.Scientific data · 2025Article
- Harnessing Smartphone Sensors for Enhanced Road Safety: A Comprehensive Dataset and Review.Scientific data · 2025Article
- Factors influencing emotional driving: examining the impact of arousal on the interplay between age, personality, and driving behaviors.Frontiers in psychology · 2025Article
- An fNIRS dataset for driving risk cognition of passengers in highly automated driving scenarios.Scientific data · 2024Article
- A multimodal physiological dataset for driving behaviour analysis.Scientific data · 2024Article
- A real-world dataset of group emotion experiences based on physiological data.Scientific data · 2024Article
- A multimodal psychological, physiological and behavioural dataset for human emotions in driving tasks.Scientific data · 2022Article
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Authors and funding
12 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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