EEG-based pain estimation via fuzzy logic and polynomial kernel support vector machine

Abstract

A pain is a human phenomenon when sensory receptors are stimulated by the injury. It can be caused from accident or intention. Everybody have this kind of sensation because the pain is a natural warning for react in order to protect a whole body. However, the reaction from the pain sometimes have to be avoid because the overreaction causes some damages to near-by tissue. An acute thermal pain is one of the most severe pain for patient which has also difficulty treatment for therapist. Consequently, the system that can be indicate pain level need to be achieve. This study purposed a use of intelligent system which is fuzzy logic algorithm and kernel support vector machine (SVM) in order to estimate pain level and classifies a state of pain. Accordingly, the results of pain estimation via fuzzy logic can be roughly indicate the pain state of EEG. The polynomial kernel support vector machine classifier for pain classification has high accuracy. © 2013 IEEE.