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. 2016 Jun;30(3):248-56.
doi: 10.1007/s00482-016-0105-x.

[Mimic activity of differentiated pain intensities : Correlation of characteristics of Facial Action Coding System and electromyography]

[Article in German]
K Limbrecht-Ecklundt  1 , P Werner  2 , H C Traue  3 , A Al-Hamadi  2 , S Walter  3
Affiliations

[Mimic activity of differentiated pain intensities : Correlation of characteristics of Facial Action Coding System and electromyography]

[Article in German]
K Limbrecht-Ecklundt et al. Schmerz. 2016 Jun.

Erratum in

Abstract

Background: The monitoring of facial expressions to assess pain intensity provides a way to determine the need for pain medication in patients who are not able to do so verbally.

Objectives: In this study two methods for facial expression analysis - Facial Action Coding System (FACS) and electromyography (EMG) of the zygomaticus muscle and corrugator supercilii - were compared to verify the possibility of using EMG for pain monitoring.

Material and methods: Eighty-seven subjects received painful heat stimuli via a thermode on the right forearm in two identical experimental sequences - with and without EMG recording.

Results: With FACS, pain threshold and pain tolerance could be distinguished reliably. Multiple regression analyses indicated that some facial expressions had a predictive value. Correlations between FACS and pain intensity and EMG and pain intensity were high, indicating a closer relationship for EMG and increasing pain intensity. For EMG and FACS, a low correlation was observed, whereas EMG correlates much better with pain intensity.

Conclusions: Results show that the facial expression analysis based on FACS represents a credible method to detect pain. Because of the expenditure of time and personal costs, FACS cannot be used properly until automatic systems work accurately. The use of EMG seems to be helpful in the meantime to enable continuous pain monitoring for patients with acute post-operative pain.

Keywords: EMG; FACS; Facial expression; Pain measurement; Pain monitoring.

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