Towards the Objective Identification of the Presence of Pain Based on Electroencephalography Signals' Analysis: A Proof-of-Concept

Sensors (Basel). 2022 Aug 20;22(16):6272. doi: 10.3390/s22166272.

Abstract

This proof-of-concept study explores the potential of developing objective pain identification based on the analysis of electroencephalography (EEG) signals. Data were collected from participants living with chronic fibromyalgia pain (n = 4) and from healthy volunteers (n = 7) submitted to experimental pain by the application of capsaicin cream (1%) on the right upper trapezius. This data collection was conducted in two parts: (1) baseline measures including pain intensity and EEG signals, with the participant at rest; (2) active measures collected under the execution of a visuo-motor task, including EEG signals and the task performance index. The main measure for the objective identification of the presence of pain was the coefficient of variation of the upper envelope (CVUE) of the EEG signal from left fronto-central (FC5) and left temporal (T7) electrodes, in alpha (8-12 Hz), beta (12-30 Hz) and gamma (30-43 Hz) frequency bands. The task performance index was also calculated. CVUE (%) was compared between groups: those with chronic fibromyalgia pain, healthy volunteers with "No pain" and healthy volunteers with experimentally-induced pain. The identification of the presence of pain was determined by an increased CVUE in beta (CVUEβ) from the EEG signals captured at the left FC5 electrode. More specifically, CVUEβ increased up to 20% in the pain condition at rest. In addition, no correlation was found between CVUEβ and pain intensity or the task performance index. These results support the objective identification of the presence of pain based on the quantification of the coefficient of variation of the upper envelope of the EEG signal.

Keywords: EEG signal; beta EEG frequency band; coefficient of variation of the upper envelope (CVUE); pain.

MeSH terms

  • Electrodes
  • Electroencephalography / methods
  • Fibromyalgia* / diagnosis
  • Humans
  • Pain / diagnosis
  • Task Performance and Analysis

Grants and funding

This research was supported by l’Université du Québec à Chicoutimi (UQAC).