Research on auditory and olfactory regulation methods for abnormal driver emotions based on EEG signals

In sudden and dangerous traffic situations, drivers are susceptible to abnormal emotional states, such as tension and anger, which can significantly increase safety risks while driving. Electroencephalography (EEG) signals, being an objective measure of emotional states, offer valuable insights for...

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Published inFrontiers in human neuroscience Vol. 19; p. 1615346
Main Authors Tang, Bangbei, Li, Yan, Wu, Yingzhang, Li, Yilun, Yue, Qizong
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 16.06.2025
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ISSN1662-5161
1662-5161
DOI10.3389/fnhum.2025.1615346

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Abstract In sudden and dangerous traffic situations, drivers are susceptible to abnormal emotional states, such as tension and anger, which can significantly increase safety risks while driving. Electroencephalography (EEG) signals, being an objective measure of emotional states, offer valuable insights for identifying and regulating these emotions. This study collected EEG data from 54 drivers in a simulated driving environment, resulting in a total of 1,260 samples, and developed a recognition model for abnormal emotions-specifically tension and anger-based on the EEG signals. Time-frequency domain features, including mean, variance, skewness, kurtosis, root mean square, and power spectral density, were extracted and analyzed using classification algorithms such as Back Propagation Neural Networks (BPNN), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM), enabling precise identification of varying levels of tension and anger. Furthermore, the study assessed the effects of music, fragrance, and their combined application on alleviating these abnormal emotional states. Results indicated that music, fragrance, and their combination were related to a reduction in stress and anger across different severity levels, with subjective assessments correlating well with the objective EEG data. Notably, music regulation was found to be most effective for mild and moderate tension, reducing tension levels by 63.33% and 68.75%, respectively, whereas fragrance was more efficacious in high tension situations, achieving a 43% reduction. For anger, fragrance regulation proved more beneficial for mild and moderate anger (reducing anger by 66.67 and 73.75%, respectively), while music regulation was most effective in mitigating high anger levels, resulting in a 58% reduction. Additionally, an analysis of time-domain features utilizing Hjorth parameters revealed that the application of a single fragrance was most effective for alleviating tension, while a singular music regulation strategy demonstrated superior performance in calming anger. The reliability of both the abnormal emotion recognition model and the emotion regulation assessment system was validated through the study. These findings contribute valuable scientific evidence for the management of drivers' emotions and suggest promising avenues for optimizing personalized emotional regulation strategies in the future.
AbstractList In sudden and dangerous traffic situations, drivers are susceptible to abnormal emotional states, such as tension and anger, which can significantly increase safety risks while driving. Electroencephalography (EEG) signals, being an objective measure of emotional states, offer valuable insights for identifying and regulating these emotions.IntroductionIn sudden and dangerous traffic situations, drivers are susceptible to abnormal emotional states, such as tension and anger, which can significantly increase safety risks while driving. Electroencephalography (EEG) signals, being an objective measure of emotional states, offer valuable insights for identifying and regulating these emotions.This study collected EEG data from 54 drivers in a simulated driving environment, resulting in a total of 1,260 samples, and developed a recognition model for abnormal emotions-specifically tension and anger-based on the EEG signals. Time-frequency domain features, including mean, variance, skewness, kurtosis, root mean square, and power spectral density, were extracted and analyzed using classification algorithms such as Back Propagation Neural Networks (BPNN), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM), enabling precise identification of varying levels of tension and anger. Furthermore, the study assessed the effects of music, fragrance, and their combined application on alleviating these abnormal emotional states.MethodsThis study collected EEG data from 54 drivers in a simulated driving environment, resulting in a total of 1,260 samples, and developed a recognition model for abnormal emotions-specifically tension and anger-based on the EEG signals. Time-frequency domain features, including mean, variance, skewness, kurtosis, root mean square, and power spectral density, were extracted and analyzed using classification algorithms such as Back Propagation Neural Networks (BPNN), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM), enabling precise identification of varying levels of tension and anger. Furthermore, the study assessed the effects of music, fragrance, and their combined application on alleviating these abnormal emotional states.Results indicated that music, fragrance, and their combination were related to a reduction in stress and anger across different severity levels, with subjective assessments correlating well with the objective EEG data. Notably, music regulation was found to be most effective for mild and moderate tension, reducing tension levels by 63.33% and 68.75%, respectively, whereas fragrance was more efficacious in high tension situations, achieving a 43% reduction. For anger, fragrance regulation proved more beneficial for mild and moderate anger (reducing anger by 66.67 and 73.75%, respectively), while music regulation was most effective in mitigating high anger levels, resulting in a 58% reduction. Additionally, an analysis of time-domain features utilizing Hjorth parameters revealed that the application of a single fragrance was most effective for alleviating tension, while a singular music regulation strategy demonstrated superior performance in calming anger.ResultsResults indicated that music, fragrance, and their combination were related to a reduction in stress and anger across different severity levels, with subjective assessments correlating well with the objective EEG data. Notably, music regulation was found to be most effective for mild and moderate tension, reducing tension levels by 63.33% and 68.75%, respectively, whereas fragrance was more efficacious in high tension situations, achieving a 43% reduction. For anger, fragrance regulation proved more beneficial for mild and moderate anger (reducing anger by 66.67 and 73.75%, respectively), while music regulation was most effective in mitigating high anger levels, resulting in a 58% reduction. Additionally, an analysis of time-domain features utilizing Hjorth parameters revealed that the application of a single fragrance was most effective for alleviating tension, while a singular music regulation strategy demonstrated superior performance in calming anger.The reliability of both the abnormal emotion recognition model and the emotion regulation assessment system was validated through the study. These findings contribute valuable scientific evidence for the management of drivers' emotions and suggest promising avenues for optimizing personalized emotional regulation strategies in the future.DiscussionThe reliability of both the abnormal emotion recognition model and the emotion regulation assessment system was validated through the study. These findings contribute valuable scientific evidence for the management of drivers' emotions and suggest promising avenues for optimizing personalized emotional regulation strategies in the future.
In sudden and dangerous traffic situations, drivers are susceptible to abnormal emotional states, such as tension and anger, which can significantly increase safety risks while driving. Electroencephalography (EEG) signals, being an objective measure of emotional states, offer valuable insights for identifying and regulating these emotions. This study collected EEG data from 54 drivers in a simulated driving environment, resulting in a total of 1,260 samples, and developed a recognition model for abnormal emotions-specifically tension and anger-based on the EEG signals. Time-frequency domain features, including mean, variance, skewness, kurtosis, root mean square, and power spectral density, were extracted and analyzed using classification algorithms such as Back Propagation Neural Networks (BPNN), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM), enabling precise identification of varying levels of tension and anger. Furthermore, the study assessed the effects of music, fragrance, and their combined application on alleviating these abnormal emotional states. Results indicated that music, fragrance, and their combination were related to a reduction in stress and anger across different severity levels, with subjective assessments correlating well with the objective EEG data. Notably, music regulation was found to be most effective for mild and moderate tension, reducing tension levels by 63.33% and 68.75%, respectively, whereas fragrance was more efficacious in high tension situations, achieving a 43% reduction. For anger, fragrance regulation proved more beneficial for mild and moderate anger (reducing anger by 66.67 and 73.75%, respectively), while music regulation was most effective in mitigating high anger levels, resulting in a 58% reduction. Additionally, an analysis of time-domain features utilizing Hjorth parameters revealed that the application of a single fragrance was most effective for alleviating tension, while a singular music regulation strategy demonstrated superior performance in calming anger. The reliability of both the abnormal emotion recognition model and the emotion regulation assessment system was validated through the study. These findings contribute valuable scientific evidence for the management of drivers' emotions and suggest promising avenues for optimizing personalized emotional regulation strategies in the future.
IntroductionIn sudden and dangerous traffic situations, drivers are susceptible to abnormal emotional states, such as tension and anger, which can significantly increase safety risks while driving. Electroencephalography (EEG) signals, being an objective measure of emotional states, offer valuable insights for identifying and regulating these emotions.MethodsThis study collected EEG data from 54 drivers in a simulated driving environment, resulting in a total of 1,260 samples, and developed a recognition model for abnormal emotions—specifically tension and anger—based on the EEG signals. Time-frequency domain features, including mean, variance, skewness, kurtosis, root mean square, and power spectral density, were extracted and analyzed using classification algorithms such as Back Propagation Neural Networks (BPNN), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM), enabling precise identification of varying levels of tension and anger. Furthermore, the study assessed the effects of music, fragrance, and their combined application on alleviating these abnormal emotional states.ResultsResults indicated that music, fragrance, and their combination were related to a reduction in stress and anger across different severity levels, with subjective assessments correlating well with the objective EEG data. Notably, music regulation was found to be most effective for mild and moderate tension, reducing tension levels by 63.33% and 68.75%, respectively, whereas fragrance was more efficacious in high tension situations, achieving a 43% reduction. For anger, fragrance regulation proved more beneficial for mild and moderate anger (reducing anger by 66.67 and 73.75%, respectively), while music regulation was most effective in mitigating high anger levels, resulting in a 58% reduction. Additionally, an analysis of time-domain features utilizing Hjorth parameters revealed that the application of a single fragrance was most effective for alleviating tension, while a singular music regulation strategy demonstrated superior performance in calming anger.DiscussionThe reliability of both the abnormal emotion recognition model and the emotion regulation assessment system was validated through the study. These findings contribute valuable scientific evidence for the management of drivers’ emotions and suggest promising avenues for optimizing personalized emotional regulation strategies in the future.
Author Wu, Yingzhang
Tang, Bangbei
Yue, Qizong
Li, Yilun
Li, Yan
AuthorAffiliation 1 School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences , Chongqing , China
4 School of Music and Dance, Henan Institute of Science and Technology , Xinxiang , China
3 School of Vehicle and Mobility, Tsinghua University , Chongqing , China
2 Department of Physiology, Army Medical University , Chongqing , China
5 China Music Mental Health Institute, Southwest University , Chongqing , China
AuthorAffiliation_xml – name: 4 School of Music and Dance, Henan Institute of Science and Technology , Xinxiang , China
– name: 5 China Music Mental Health Institute, Southwest University , Chongqing , China
– name: 2 Department of Physiology, Army Medical University , Chongqing , China
– name: 3 School of Vehicle and Mobility, Tsinghua University , Chongqing , China
– name: 1 School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences , Chongqing , China
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Cites_doi 10.3390/sci5020023
10.3389/fpsyg.2022.919695
10.1016/j.aap.2020.105516
10.1038/s41598-024-78156-1
10.1063/1.5139383
10.1109/JSEN.2023.3339727
10.1109/ACCESS.2019.2934018
10.3390/brainsci14070721
10.1108/09590550910941535
10.3390/ijerph15040611
10.1109/IJCNN.2009.5178854
10.1177/030573561773462
10.1016/j.neucli.2016.07.002
10.22034/IJHCUM.2024.04.05
10.1016/j.eswa.2021.114952
10.15666/aeer/1704_90839095
10.5117/9789087283209
10.1016/j.heliyon.2024.e38941
10.1109/IES59143.2023.10242538
10.1155/2021/5497081
10.1016/j.aap.2020.105923
10.1016/j.neuroimage.2019.06.046
10.1016/j.bspc.2022.103966
10.1016/j.measurement.2022.111738
10.20982/tqmp.05.2.p068
10.1080/01441647.2022.2100943
10.1109/TITS.2018.2868499
10.1007/s12144-022-03259-9
10.1016/j.bspc.2021.102648
10.3389/fpsyg.2022.1014202
10.1016/j.ijinfomgt.2023.102715
10.1037/bul0000096
10.1016/j.tust.2024.105912
10.3389/fnins.2018.00162
10.1109/TIV.2022.3195635
10.1073/pnas.2308859121
10.20959/wjpr20244-31747
10.1016/j.eswa.2015.10.049
10.3233/FAIA220517
10.3389/fpsyg.2024.1391204
10.3390/app13010100
10.1371/journal.pone.0067347
10.1016/j.trf.2022.01.010
10.1016/j.scitotenv.2023.168785
10.4103/nah.nah_5_24
10.1109/TIV.2023.3339673
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Keywords emotional regulation
music intervention
brain
driving emotions
fragrance intervention
Language English
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References Khalili (B20) 2009
Li (B23) 2023; 42
Mehmood (B27) 2022; 202
Xu (B50) 2024; 75
Verdonschot (B44) 2019
Das (B11) 2023; 5
Atkinson (B3) 2016; 47
Smith (B40) 2024; 13
Putkinen (B34) 2024; 121
Sikander (B39) 2018; 20
Xi (B48) 2022; 13
Laktionova (B21) 2024; 14
Liao (B25) 2024; 15
Wang (B46) 2024; 911
Xiao (B49) 2024; 26
Ning (B29) 2022; 13
Chaichanasittikarn (B8) 2023
Islam (B19) 2016; 46
Li (B22) 2023; 24
Hasan (B17) 2021
Soars (B41) 2009; 37
Bai (B4) 2021; 177
Mukherjee (B28) 2024; 9
Cook (B10) 2019; 47
Sanyal (B36) 2013; 8
Peng (B32) 2022; 13
Âbele (B1) 2020; 140
Conceição (B9) 2023; 43
Son (B42) 2021; 2021
Pedroni (B30) 2019; 200
Subasi (B43) 2021; 68
Alazrai (B2) 2019; 7
Pring (B33) 2024; 14
Barnes (B5) 2018; 15
Richard (B35) 2009; 5
Bobermin (B6) 2021; 150
Li (B24) 2018; 12
Pei (B31) 2024; 10
Habibifar (B15) 2022; 85
Shashidhar (B38) 2023
Sari (B37) 2019
Godfrey (B14) 2018
Dixon (B12) 2017; 143
Fatih (B13) 2023
Celiñski (B7) 2022
Wagh (B45) 2022; 78
Wu (B47) 2023; 9
Lin (B26) 2022
Zhang (B51) 2019; 17
Han (B16) 2024; 152
Hu (B18) 2022; 7
40666273 - Front Hum Neurosci. 2025 Jul 01;19:1647983. doi: 10.3389/fnhum.2025.1647983.
References_xml – start-page: 1
  year: 2023
  ident: B8
  article-title: Wearable EEG-based classification of odor-induced emotion
  publication-title: Proceedings of the 2023 11th international IEEE/EMBS conference on neural engineering (NER)
– volume: 5
  start-page: 23
  year: 2023
  ident: B11
  article-title: A survey on EEG data analysis software.
  publication-title: Science
  doi: 10.3390/sci5020023
– volume: 13
  start-page: 919695
  year: 2022
  ident: B32
  article-title: The application of electroencephalogram in driving safety: Current status and future prospects.
  publication-title: Front. Psychol.
  doi: 10.3389/fpsyg.2022.919695
– volume: 140
  start-page: 105516
  year: 2020
  ident: B1
  article-title: Links between observed and self-reported driving anger, observed and self-reported aggressive driving, and personality traits.
  publication-title: Accid. Anal. Prev.
  doi: 10.1016/j.aap.2020.105516
– volume: 14
  start-page: 27766
  year: 2024
  ident: B33
  article-title: Music communicates social emotions: Evidence from 750 music excerpts.
  publication-title: Sci. Rep.
  doi: 10.1038/s41598-024-78156-1
– year: 2019
  ident: B37
  article-title: Emotion classification system based on non-linear EEG signal using backpropagation neural network
  publication-title: Proceedings of the AIP conference
  doi: 10.1063/1.5139383
– volume: 24
  start-page: 2329
  year: 2023
  ident: B22
  article-title: Driver distraction from the EEG perspective: A review.
  publication-title: IEEE Sens. J.
  doi: 10.1109/JSEN.2023.3339727
– volume: 7
  start-page: 109612
  year: 2019
  ident: B2
  article-title: A deep learning framework for decoding motor imagery tasks of the same hand using EEG signals.
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2934018
– start-page: 1
  year: 2021
  ident: B17
  article-title: Fine-grained emotion recognition from EEG signal using fast Fourier transformation and CNN
  publication-title: Proceedings of the 2021 joint 10th international conference on informatics, electronics & vision (ICIEV) and 2021 5th international conference on imaging, vision & pattern recognition (icIVPR)
– volume: 14
  start-page: 721
  year: 2024
  ident: B21
  article-title: Male body odor affects emotional state, LH, and cortisol secretion in women of different age groups.
  publication-title: Brain Sci.
  doi: 10.3390/brainsci14070721
– volume: 37
  start-page: 286
  year: 2009
  ident: B41
  article-title: Driving sales through shoppers’ sense of sound, sight, smell and touch
  publication-title: Int. J. Retail Distrib. Manage
  doi: 10.1108/09590550910941535
– volume: 15
  start-page: 611
  year: 2018
  ident: B5
  article-title: In-cabin air quality during driving and engine idling in air-conditioned private vehicles in Hong Kong.
  publication-title: Int. J. Environ. Res. Public Health
  doi: 10.3390/ijerph15040611
– start-page: 120
  year: 2022
  ident: B7
  article-title: Problems of studies on emotions in road traffic
  publication-title: Proceedings of the scientific and technical conference transport systems theory and practice
– start-page: 1571
  year: 2009
  ident: B20
  article-title: Emotion recognition system using brain and peripheral signals: Using correlation dimension to improve the results of EEG
  publication-title: Proceedings of the 2009 international joint conference on neural networks
  doi: 10.1109/IJCNN.2009.5178854
– volume: 47
  start-page: 144
  year: 2019
  ident: B10
  article-title: Music as an emotion regulation strategy: An examination of genres of music and their roles in emotion regulation.
  publication-title: Psychol. Music
  doi: 10.1177/030573561773462
– volume: 46
  start-page: 287
  year: 2016
  ident: B19
  article-title: Methods for artifact detection and removal from scalp EEG: A review.
  publication-title: Neurophysiol. Clin.
  doi: 10.1016/j.neucli.2016.07.002
– year: 2018
  ident: B14
  publication-title: Essential oils for mindfulness and meditation: Relax, replenish, and rejuvenate.
– volume: 9
  start-page: 617
  year: 2024
  ident: B28
  article-title: Gridlock gloom: A geographical analysis of commuters’ perceptions on traffic congestion.
  publication-title: Int. J. Hum. Capit. Urban Manag.
  doi: 10.22034/IJHCUM.2024.04.05
– volume: 177
  start-page: 114952
  year: 2021
  ident: B4
  article-title: Reliability prediction-based improved dynamic weight particle swarm optimization and back propagation neural network in engineering systems.
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2021.114952
– volume: 17
  start-page: 23
  year: 2019
  ident: B51
  article-title: A new BP neural network fusion algorithm for multi-source remote sensing data on groundwater.
  publication-title: Appl. Ecol. Environ. Res.
  doi: 10.15666/aeer/1704_90839095
– year: 2019
  ident: B44
  publication-title: The E-primer: An introduction to creating psychological experiments in E-Prime.
  doi: 10.5117/9789087283209
– volume: 10
  start-page: e38941
  year: 2024
  ident: B31
  article-title: Exploring the physiological response differences of β-caryophyllene, linalool and citral inhalation and their anxiolytic potential.
  publication-title: Heliyon
  doi: 10.1016/j.heliyon.2024.e38941
– start-page: 179
  year: 2023
  ident: B13
  article-title: Comparative analysis of EEG-based emotion recognition between male and female participants using Hjorth parameter
  publication-title: Proceedings of the 2023 international electronics symposium (IES)
  doi: 10.1109/IES59143.2023.10242538
– volume: 2021
  start-page: 5497081
  year: 2021
  ident: B42
  article-title: EEG-based emotion classification for verifying the korean emotional movie clips with support vector machine (SVM).
  publication-title: Complexity
  doi: 10.1155/2021/5497081
– volume: 150
  start-page: 105923
  year: 2021
  ident: B6
  article-title: Driving simulators to evaluate road geometric design effects on driver behaviour: A systematic review
  publication-title: Accid. Anal. Prevent
  doi: 10.1016/j.aap.2020.105923
– volume: 200
  start-page: 460
  year: 2019
  ident: B30
  article-title: Automagic: Standardized preprocessing of big EEG data.
  publication-title: Neuroimage
  doi: 10.1016/j.neuroimage.2019.06.046
– volume: 78
  start-page: 103966
  year: 2022
  ident: B45
  article-title: Performance evaluation of multi-channel electroencephalogram signal (EEG) based time frequency analysis for human emotion recognition.
  publication-title: Biomed. Signal Process. Control
  doi: 10.1016/j.bspc.2022.103966
– volume: 202
  start-page: 111738
  year: 2022
  ident: B27
  article-title: EEG-based affective state recognition from human brain signals by using Hjorth-activity.
  publication-title: Measurement
  doi: 10.1016/j.measurement.2022.111738
– volume: 5
  start-page: 68
  year: 2009
  ident: B35
  article-title: An introduction to E-Prime.
  publication-title: Tutor. Q. Methods Psychol.
  doi: 10.20982/tqmp.05.2.p068
– volume: 43
  start-page: 264
  year: 2023
  ident: B9
  article-title: The effect of transport infrastructure, congestion and reliability on mental wellbeing: A systematic review of empirical studies.
  publication-title: Trans. Rev.
  doi: 10.1080/01441647.2022.2100943
– volume: 20
  start-page: 2339
  year: 2018
  ident: B39
  article-title: Driver fatigue detection systems: A review.
  publication-title: IEEE Trans. Intell. Trans. Syst.
  doi: 10.1109/TITS.2018.2868499
– volume: 42
  start-page: 21667
  year: 2023
  ident: B23
  article-title: Social exclusion and dangerous driving behavior: The mediating role of driving anger and moderating role of cognitive reappraisal.
  publication-title: Curr. Psychol.
  doi: 10.1007/s12144-022-03259-9
– volume: 68
  start-page: 102648
  year: 2021
  ident: B43
  article-title: EEG-based emotion recognition using tunable Q wavelet transform and rotation forest ensemble classifier.
  publication-title: Biomed. Signal Process. Control
  doi: 10.1016/j.bspc.2021.102648
– volume: 13
  start-page: 1014202
  year: 2022
  ident: B29
  article-title: Ventral tegmental area dopaminergic action in music therapy for post-traumatic stress disorder: A literature review.
  publication-title: Front. Psychol.
  doi: 10.3389/fpsyg.2022.1014202
– volume: 75
  start-page: 102715
  year: 2024
  ident: B50
  article-title: Musical atmosphere as a (dis)tractive facet of user interfaces: An experiment on sustainable consumption decisions in eCommerce
  publication-title: Int. J. Inform. Manage
  doi: 10.1016/j.ijinfomgt.2023.102715
– volume: 143
  start-page: 1033
  year: 2017
  ident: B12
  article-title: Emotion and the prefrontal cortex: An integrative review.
  publication-title: Psychol. Bull.
  doi: 10.1037/bul0000096
– volume: 152
  start-page: 105912
  year: 2024
  ident: B16
  article-title: The effects of tunnel radius, turn direction, and zone characteristics on drivers’ visual performance.
  publication-title: Tunnell. Underground Space Technol.
  doi: 10.1016/j.tust.2024.105912
– volume: 12
  start-page: 162
  year: 2018
  ident: B24
  article-title: Exploring EEG features in cross-subject emotion recognition.
  publication-title: Front. Neurosci.
  doi: 10.3389/fnins.2018.00162
– volume: 7
  start-page: 417
  year: 2022
  ident: B18
  article-title: Review and perspectives on driver digital twin and its enabling technologies for intelligent vehicles.
  publication-title: IEEE Trans. Intell. Vehicles
  doi: 10.1109/TIV.2022.3195635
– volume: 121
  year: 2024
  ident: B34
  article-title: Bodily maps of musical sensations across cultures.
  publication-title: Proc. Natl. Acad. Sci. U.S.A.
  doi: 10.1073/pnas.2308859121
– volume: 13
  start-page: 840
  year: 2024
  ident: B40
  article-title: Effects of a lemon aroma on attention, reaction time and mood.
  publication-title: World J. Pharm. Res.
  doi: 10.20959/wjpr20244-31747
– volume: 47
  start-page: 35
  year: 2016
  ident: B3
  article-title: Improving BCI-based emotion recognition by combining EEG feature selection and kernel classifiers.
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2015.10.049
– year: 2022
  ident: B26
  article-title: Warning of dangerous driving behavior caused by drivers and road environmental factors
  publication-title: Proceedings of CECNet 2022
  doi: 10.3233/FAIA220517
– volume: 15
  start-page: 1391204
  year: 2024
  ident: B25
  article-title: Analysis of the causes, psychological mechanisms, and coping strategies of short video addiction in China
  publication-title: Front. Psychol
  doi: 10.3389/fpsyg.2024.1391204
– volume: 13
  start-page: 100
  year: 2022
  ident: B48
  article-title: Mental health and safety assessment methods of bus drivers.
  publication-title: Appl. Sci.
  doi: 10.3390/app13010100
– volume: 8
  start-page: e67347
  year: 2013
  ident: B36
  article-title: Prenatal loud music and noise: Differential impact on physiological arousal, hippocampal synaptogenesis and spatial behavior in one day-old chicks.
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0067347
– volume: 85
  start-page: 245
  year: 2022
  ident: B15
  article-title: Relationship between driving styles and biological behavior of drivers in negative emotional state.
  publication-title: Trans. Res. F Traffic Psychol. Behav.
  doi: 10.1016/j.trf.2022.01.010
– start-page: 1
  year: 2023
  ident: B38
  article-title: EEG data analysis for stress detection using k-nearest neighbor
  publication-title: Proceedings of the 2023 international conference on integrated intelligence and communication systems (ICIICS)
– volume: 911
  start-page: 168785
  year: 2024
  ident: B46
  article-title: Air quality in the car: How CO2 and body odor affect drivers’ cognition and driving performance?
  publication-title: Sci. Total Environ.
  doi: 10.1016/j.scitotenv.2023.168785
– volume: 26
  start-page: 198
  year: 2024
  ident: B49
  article-title: Effects of soothing music on the intraoperative management of patients undergoing tension-free herniorrhaphy: A retrospective study.
  publication-title: Noise Health
  doi: 10.4103/nah.nah_5_24
– volume: 9
  start-page: 3493
  year: 2023
  ident: B47
  article-title: Driver’s hand-foot coordination and global-regional brain functional connectivity under fatigue: Via graph theory and explainable artificial intelligence
  publication-title: IEEE Trans. Intell. Veh
  doi: 10.1109/TIV.2023.3339673
– reference: 40666273 - Front Hum Neurosci. 2025 Jul 01;19:1647983. doi: 10.3389/fnhum.2025.1647983.
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Snippet In sudden and dangerous traffic situations, drivers are susceptible to abnormal emotional states, such as tension and anger, which can significantly increase...
IntroductionIn sudden and dangerous traffic situations, drivers are susceptible to abnormal emotional states, such as tension and anger, which can...
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SubjectTerms brain
driving emotions
emotional regulation
fragrance intervention
music intervention
Neuroscience
Title Research on auditory and olfactory regulation methods for abnormal driver emotions based on EEG signals
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