ArticleData in brief2023
Chronic neuropathic pain: EEG data in eyes open and eyes closed with painDETECT and brief pain inventory reports.
Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Efficient Blended Models for Analysis and Detection of Neuropathic Pain from EEG Signals Using Machine Learning.Bioengineering (Basel, Switzerland) · 2026Article
- Pain and the Brain: A Systematic Review of Methods, EEG Biomarkers, Limitations, and Future Directions.Neurology international · 2025Review
- Black-white hole pattern: an investigation on the automated chronic neuropathic pain detection using EEG signals.Cognitive neurodynamics · 2024Article
- Resting-state electroencephalography delta and theta bands as compensatory oscillations in chronic neuropathic pain: a secondary data analysis.Brain network and modulationArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Thirty-six chronic neuropathic pain patients (8 men and 28 women) of Mexican nationality with a mean age of 44±13.98 were recruited for EEG signal recording in eyes open and eyes closed resting state condition. Each condition was recorded for 5 min, with a total recording session time of 10 min. An ID number was given to each patient after signing up for the study, with which they answered the painDETECT questionnaire as a screening process for neuropathic pain alongside their clinical history. The day of the recording, the patients answered the Brief Pain Inventory, as an evaluation questionnaire for the interference of the pain with their daily life. Twenty-two EEG channels positioned in accordance with the 10/20 international system were registered with Smarting mBrain device. EEG signals were sampled at 250 Hz with a bandwidth between 0.1 and 100 Hz. The article provides two types of data: (1) raw EEG data in resting state and (2) the report of patients for two validated pain questionnaires. The data described in this article can be used for classifier algorithms considering stratifying chronic neuropathic pain patients with EEG data alongside their pain scores. In sum, this data is of extreme relevance for the pain field, where researchers have been seeking to integrate the pain experience with objective physiological data, such as the EEG.
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Registered trials
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