Multimodal Pain Dataset

Published: 18 November 2024| Version 2 | DOI: 10.17632/mf2cgph9cy.2
Contributors:
, Boran Toktay, İkbal Işık Orhan, Elif Yıldırım

Description

Pain is considered subjective since it is based on personal experience; however, it may be possible to objectively analyze pain through a self-reporting system supported by bio-signals. Based on this hypothesis, a multimodal dataset is created, combining EEG and wristband signals (including EDA, BVP, temperature, accelerometer data) along with participants' responses to a survey, including the McGill Pain Questionnaire. This dataset, collected from 99 participants, allows for the analysis of three different types of pain: headache, back pain, and menstrual pain. E4 Empatica wristband and Mindwave Mobile 2 EEG device are used to collect the data. Both raw and processed data of the devices with survey answers are stored in the dataset by participants' unique IDs.

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Institutions

  • Istanbul Kultur Universitesi

Categories

Signal Processing, Headache, Back Pain, Pain Assessment, Acute Pain, Menstrual Cycle Pain, Physiological Signal Processing

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