Electroencephalogram based quantitative estimation of pain for balanced anaesthesia

• Electroencephalogram based expert system for the post-surgical pain estimation.
• EEG of parietal region of the brain was recorded and processed.
• ‘Hjorth Activity’ and ‘Spectral Entropy’ were identified as pain estimator.
• Fuzzy system was developed for pain quantification.
• Pain index is a numerical number in the range of 0–10 as in standard VAS.

The purpose of this study was to quantify the pain experienced by the patients in the Post Anaesthetic Care Unit (PACU) and to design an Electroencephalogram (EEG) based system which could monitor the pain in real time and display the quantified value as pain index. Research has established that the EEG from different lobes of brain can be used to find out individual indices for different components of balanced anaesthesia. In the present study, the focus was on analgesia. During the study, EEG of 31 patients was recorded from different regions of brain in the pre-operative (normal) and post-operative (painful) state. After analysis, it was observed that EEG parameters ‘Hjorth Activity’ and ‘Spectral Entropy’ from parietal region reflect the pain experienced by the patient during post-operative recovery period. Based on these parameters, a pain estimation system was developed which gave a numerical graded output between 0 and 10. This developed pain scale by analyzing EEG signals of the patients in the post operative period was correlated with Visual Analogue Scale (VAS) and was found to be accurate to estimate the level of pain, when compared with the pain experienced by the patient.

Figure optionsDownload as PowerPoint slide