Data · dataset · 2026
EEG dataset for motion-sickness assessment in electric-vehicle passengers
Listed in ScienceDB
Description
EEG dataset for motion-sickness assessment in electric-vehicle passengers==========================================================================Dataset description-------------------This dataset contains 32-channel EEG recordings collected from 15 healthyparticipants during real electric-vehicle rides on a controlled L-shapedtrack. Each participant was scheduled for normal-driving and fast-drivingsessions, together with resting recordings before and after the drivingsessions.
EEG was recorded at 1000 Hz. Synchronized event markers identify thedriving laps. Lap-level Motion Sickness Intensity Scale (MISC) scores andMotion Sickness Susceptibility Questionnaire Short-form (MSSQ-Short) scoresare provided with the recordings.The release contains 29 valid driving sessions, 174 usable driving laps (84normal-driving and 90 fast-driving laps), and 60 resting recordings.
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Participantfolders and manifest subject_id values use study codes 25009--25023.The data remain human-participant data and are subject to the repository accessconditions and Data Usage Agreement (DUA). Users must obtain the data directlythrough the Science Data Bank and accept the DUA. The DUA permits internalresearch, analysis, method development, education, validation, and lawfulresearch and development, including commercial R&D, but prohibitsre-identification, participant contact, redistribution of controlled files, andinsecure handling.
Aggregate results and non-reconstructive derived works maybe shared.Directory structure-------------------EEG_data/|-- README.txt|-- dataset_manifest.csv|-- data_dictionary.csv|-- group_divide.txt|-- MISC_score.xlsx|-- MSSQ_score.xlsx|-- 25009/ # representative participant| |-- normal_driving/| | |-- data.bdf # raw continuous EEG| | |-- evt.bdf # synchronized event markers| | |-- recordInformation.json # acquisition metadata| | `-- final/| | |-- final1.edf| | |-- final2.edf| | |-- final3.edf| | |-- final4.edf| | |-- final5.edf| | `-- final6.edf| |-- fast_driving/| | |-- data.bdf| | |-- evt.bdf| | |-- recordInformation.json| | `-- final/| | |-- final1.edf| | |-- ...| | `-- final6.edf| |-- resting_before_normal_driving/| | |-- data.bdf| | |-- evt.bdf| | `-- recordInformation.json| |-- resting_after_normal_driving/| | |-- data.bdf| | |-- evt.bdf| | `-- recordInformation.json| |-- resting_before_fast_driving/| | |-- data.bdf| | |-- evt.bdf| | `-- recordInformation.json| `-- resting_after_fast_driving/| |-- data.bdf| |-- evt.bdf| `-- recordInformation.json|-- 25010/ ... 25023/ # same nominal structure|-- 25013/| `-- normal_driving/| `-- data_broken.txt # no valid raw EEG; missing_raw`-- 25019/ `-- fast_driving/ |-- note.txt |-- data segment 1/ # laps 1-4 | |-- data.bdf | |-- evt.bdf | `-- recordInformation.json |-- data segment 2/ # laps 5-6 | |-- data.bdf | |-- evt.bdf | `-- recordInformation.json `-- final/ |-- final1.edf |-- ... `-- final6.edfFile descriptions------------------ README.txt: this dataset overview, directory tree, file descriptions, and basic reuse guidance.- dataset_manifest.csv: the machine-readable inventory of driving laps, resting recordings, and missing sessions.
It records the study code, condition, session, lap index, source paths, event-sample bounds, duration, MISC score, susceptibility group, and status.- data_dictionary.csv: definitions of the released file types and manifest fields, including allowed values and notes.- group_divide.txt: MSSQ-Short-based susceptible and non-susceptible group labels.- MISC_score.xlsx: lap-level Motion Sickness Intensity Scale scores.- MSSQ_score.xlsx: MSSQ-Short scores and selected demographic fields (age, sex, religion and ethnicity) released for analysis.
All column names and categorical response labels are in English; the religion field is recorded as “Atheist” and the ethnicity field as “Han Chinese” for all participants.Participant and session files------------------------------ data.bdf is the raw continuous EEG recording for a session.- evt.bdf contains synchronized event markers. For standard driving sessions, nine consecutive markers define one driving lap; the exact sample bounds are listed in dataset_manifest.csv.- recordInformation.json contains acquisition metadata without direct identifiers.- final/final1.edf through final/final6.edf are lap-level EDF convenience files included with driving sessions.
They are derived files; users who need to reproduce a crop should begin with data.bdf, evt.bdf, and the manifest.- Resting-session folders contain data.bdf, evt.bdf, and recordInformation.json and do not contain a final directory.Data availability notes------------------------ Participant 25013 has no valid normal-driving raw EEG. Its data_broken.txt file documents the missing session, and the manifest uses the status missing_raw.- Participant 25019 fast_driving is split across two source folders because the recording was stored in two segments.
Segment 1 contains laps 1--4 and segment 2 contains laps 5--6. The manifest identifies the retained fourth lap and its status.Acquisition electrode information----------------------------------AFz was the hardware ground electrode and FCz was the hardware referenceelectrode during acquisition. The released files retain the recorded EEGchannels and acquisition metadata; AFz and FCz describe acquisition positionsand were not treated as additional EEG signal channels in the released featurematrix.Suggested use-------------The dataset supports research on EEG correlates of motion sickness, effects ofnormal versus fast vehicle motion, lap-level symptom modelling, EEG signalquality and artifact handling in real-vehicle recordings, and reproducibleEEG feature or machine-learning method development.
Use the manifest andsynchronized event files to relate recordings to participants, sessions, anddriving laps.
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Where it is published
- DOI doi.org/10.57760/sciencedb.32147 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
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Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Electronics, sensors and digital hardware 69%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.32147 | 11 d ago | JSON v1 |
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|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:4009 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (69%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |