Multimodal Insights Into Diverse Pain Experiences: Physiopain Dataset - TOKTAY, BORAN; ORHAN, İKBAL IŞIK; Yıldırım, Elif; AKBULUT, FATMA PATLAR; Çatal, Cağatay (Elsevier Inc., 2025)
PhysioPain dataset comprises several physiological data of different kinds of pain: no pain, headache, menstrual cycle pain and back/neck/waist pain in search of a sophisticated and complete approach to pain representation. The study comprised 99 individuals, of whom 93 participants contributed real-time physiological data. These participants underwent experiment process to gather real-time physiological data including electroencephalogram (EEG), skin temperature, electrodermal activity (EDA), blood volume pulse (BVP), and accelerometer data. Combining objective physiological data with subjective information acquired by the survey using the McGill questionnaire and customized questions produces a complete dataset fit for the tasks related to pain estimate, pain classification, and other approaches to pain observation. This method seeks to offer a fresh viewpoint on pain intensity and catch a more complete knowledge of the intricate character of pain experiences.
Keywords: Biosignals; Multimodal Pain Assessment; Pain Classification; Pain Intensity Estimation; Physiological Signal Analysis