Facial electromyography (fEMG) activities in response to affective visual stimulation

Abstract

Recently, affective computing findings demonstrated that emotion processing and recognition is important in improving the quality of human computer interaction (HCI). In the present study, new data for a robust discrimination of three emotional states (negative, neutral and positive) employing two-channel facial electromyography (EMG) over zygomaticus major and corrugator supercilii will be presented. The facial EMG activities evoked upon viewing a standard set of pictures selected from the International Affective Picture System (IAPS) and additional self selected pictures revealed that positive pictures led to increased facial EMG activities over zygomaticus major (F (2, 471) = 4.23, p < 0.05), whereas negative pictures elicited greater facial EMG activities over corrugator supercilii (F (2, 476) = 3.06, p < 0.05). In addition, the correlation between facial EMG activities over these two sites and participants' ratings of stimuli pictures in dimension of valence measured by Self-Assessment Manikin (SAM) was significant (r = −0.63, p < 0.001, corrugator supercilii, r = 0.51, p < 0.05, zygomaticus major, respectively). Our results suggest that emotion inducing pictures elicit the intended emotions and that corrugator and zygomaticus EMG can effectively and reliably differentiate negative and positive emotions, respectively.