Pain Prediction in Humans using Human Brain Activity Data

This research article focuses on the analysis of electroencephalography (EEG) signals of the brain during pain perception. The proposed system is based on the hypothesis that a noticeable change occurs in mental conditions while experiencing pain. When the human body is injured, sensory receptors in the brain enter a stimulated state. The injury may be the result of attention or an accident. Pain warnings are natural in humans and protect the body from further negative effects. In this article, an innovative and robust system based on prominent features extracted from the brain activity recorded using EEG, is proposed to predict the state of pain perception. The brain signals of subjects are observed using two low-cost EEG headsets including neurosky mindwave mobile and emotiv insight. Time and frequency domain features are selected to represent the observed signals. The results show that a combination of time and frequency domain features is the most informative approach for pain prediction using the observed brain activity.

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