An Innovative EEG-Based Pain Identification and Quantification: A Pilot Study.

OBJECTIVE

The present pilot study aimed to propose an innovative scale-independent measure based on electroencephalographic (EEG) signals for the identification and quantification of the magnitude of chronic pain.

METHODS

EEG data were collected from three groups of participants at rest: seven healthy participants with pain, 15 healthy participants submitted to thermal pain, and 66 participants living with chronic pain. Every 30 s, the pain intensity score felt by the participant was also recorded. Electrodes positioned in the contralateral motor region were of interest. After EEG preprocessing, a complex analytical signal was obtained using Hilbert transform, and the upper envelope of the EEG signal was extracted. The average coefficient of variation of the upper envelope of the signal was then calculated for the beta (13-30 Hz) band and proposed as a new EEG-based indicator, namely Piq, to identify and quantify pain.

MAIN RESULTS

The main results are as follows: (1) A Piq threshold at 10%, that is, Piq ≥ 10%, indicates the presence of pain, and (2) the higher the Piq (%), the higher the extent of pain.

CONCLUSIONS

This finding indicates that Piq can objectively identify and quantify pain in a population living with chronic pain. This new EEG-based indicator can be used for objective pain assessment based on the neurophysiological body response to pain.

SIGNIFICANCE

Objective pain assessment is a valuable decision-making aid and an important contribution to pain management and monitoring.