EEG data of drivers exposed to noise

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README.md

EEG_Driving

Introduction

In order to investigate the changes in physiological characteristics and behavioural performance of train drivers under different noise exposures, simulated driving experiments at 50, 60, 70 and 80 dB were designed in this study.

Data description

All EEG data were collected using the NeuSen W-series wireless EEG acquisition system from neuracle.

Experimental process:Experimental preparation(Familiarisation Drive、EEG Device Fitting)--->Selective reaction time test--->5 minutes of resting--->90 minutes driving simulation(50/60/70/80dB)---> Selective reaction time test--->EEG Device Removal

The EEG signals were recorded for a duration of 95 minutes, from the start of the resting period until the end of the driving period. Where sub-01 to sub-04 are driving under 50dB noise exposure, sub-05 to sub-08 are driving under 60dB noise exposure, sub-09 to sub-12 are driving under 70dB noise exposure and sub-13 to sub-16 are driving under 80dB noise exposure.

datacite.yml
Title The architecture of functional brain network modulated by driving under train running noise exposure
Authors Zhao,Yashuai;School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai, P.R.China.;ORCID:0009-0000-5827-8118
Huang,Yuanchun;School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai, P.R.China.;ORCID:0000-0003-0895-5891
Liu,Zhigang;School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai, P.R.China.
Zhou,Yifan;School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai, P.R.China.
Description In order to investigate the changes in physiological characteristics and behavioural performance of train drivers under different noise exposures, simulated driving experiments at 50, 60, 70 and 80 dB were designed in this study.
License Creative Commons CC0 1.0 Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/)
References
Funding
Keywords Driving tasks
EEG
Resource Type Dataset