Chronic neuropathic pain: EEG data in eyes open and eyes closed with painDETECT and brief pain inventory reports

Daniela M Zolezzi; Norberto E Naal-Ruiz; Luz María Alonso-Valerdi; David I Ibarra-Zarate

doi:10.1016/j.dib.2023.109060

Chronic neuropathic pain: EEG data in eyes open and eyes closed with painDETECT and brief pain inventory reports

Data Brief. 2023 Mar 16:48:109060. doi: 10.1016/j.dib.2023.109060. eCollection 2023 Jun.

Authors

Daniela M Zolezzi^{1

2}, Norberto E Naal-Ruiz³, Luz María Alonso-Valerdi¹, David I Ibarra-Zarate³

Affiliations

¹ Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Monterrey 64849, Nuevo León, México.
² Center for Neuroplasticity and Pain, Department of Health Science and Technology, Aalborg University, Aalborg 9220, Denmark.
³ Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Vía Atlixcáyotl 2301, Puebla 72453, México.

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.

Keywords: Brief Pain Inventory; EEG raw data; EEG resting state; chronic neuropathic pain; pain classification; pain scores; pain severity; painDETECT.