Reliability of surface facial electromyography

Abstract

Data from two studies were used to estimate the reliability of facial EMG when used to index facial mimicry (Study 1) or affective reactions to pictorial stimuli (Study 2). Results for individual muscle sites varied between muscles and depending on data treatment. For difference scores, acceptable internal consistencies were found only for corrugator supercilii, and test-retest reliabilities were low. For contrast measures describing patterns of reactions to stimuli, such as high zygomaticus major combined with low corrugator supercilii, acceptable internal consistencies were found for facial reactions to smiling faces and positive affective reactions to affiliative images (Study 2). Facial reactions to negative emotions (Study 1) and facial reactions to power and somewhat less to achievement imagery (Study 2) showed unsatisfactory internal consistencies. For contrast measures, good temporal stability over 24 months (Study 1) and 15 months (Study 2), respectively, was obtained. In Study 1, the effect of method factors such as mode of presentation was more reliable than the emotion effect. Overall, people's facial reactions to affective stimuli seem to be influenced by a variety of factors other than the emotion-eliciting element per se, which resulted in biased internal consistency estimates. However, the influence of these factors in turn seemed to be stable over time.

Facial responsiveness of psychopaths to the emotional expressions of others

“…Similarly, we focused on the activity of the corrugator muscle, because it is a reliable index of facial mimicry for happy, angry, and sad expressions [ 50 ], in contrast to the zygomaticus, the muscle pulling up the cheeks in smiling. Concerning the zygomaticus, Künecke et al [ 30 ], for example, found no significant differences in activity when participants viewed faces expressing different emotions.…”

Emotion processing in female youth: Testing the stability of the late positive potential

“…In line with the Precision Medicine Initiative (Insel, Amara, & Baschke, 2015), identifying biological indicators that predict treatment response is critical. Prior to testing predictors, research must first examine core psychometric properties, including test-retest stability (i.e., invariance over time) and internal consistency (i.e., odd/even reliability; see Auerbach et al, 2016;Cassidy, Robertson, & O'Connell, 2012;Hess et al, 2017;Olvet & Hajcak, 2009;Tenke et al, 2017;Weinberg & Hajcak, 2011b). In research testing the EIT, Kujawa and colleagues (2013) showed 2-year stability of LPP amplitude in children 8 to 13 years old.…”

Development of a methodology to combine fMRI and EMG to measure emotional responses in patients with anorexia nervosa

“…Facial EMG is used to quantify and identify emotions often characterizing positive and negative valence (as opposed to specific emotions). Consequently, many studies focus on the acquisition of Corrugator and Zygomaticus (negative vs.positive valence respectively; see (Larsen & Fredrickson, 1999), in part due to increased reliability of these signals when compared with emotion specific signals (Hess et al, 2017). The results indicated that…”

“…Facial EMG is used to quantify and identify emotions often characterizing positive and negative valence (as opposed to specific emotions). Consequently, many studies focus on the acquisition of Corrugator and Zygomaticus (negative vs.positive valence respectively; see (Larsen & Fredrickson, ), in part due to increased reliability of these signals when compared with emotion specific signals (Hess et al, ). The results indicated that Corrugator response discriminates negative facial stimuli (i.e., ‘Yuck’ face) from happy stimuli (i.e., ‘Smile’ face), an approach that could be leveraged for studying valence in addition to emotion‐specific responses.…”