Facial expression recognition through pattern analysis of facial muscle movements utilizing electromyogram sensors

• Main Authors: Ang, Lou Benedict P., Belen, Erwin F., Bernardo, Ramon A., Jr., Boongaling, Eleazar R., Briones, Grace H., Coronel, Jonathan B.
• Format: text
• Published: Animo Repository 2004
• Subjects: Emotion recognition; Face perception; Electromyography; Electrical and Computer Engineering; Electrical and Electronics
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1463
• Institution: De La Salle University

Emotion recognition is one of the important highlights of human emotional intelligence and has long been studied to be incorporated with machine intelligence argued to make machines even more intelligent. This paper aims to contribute to this field of study by enabling machines to recognize emotion from facial Electromyogram (EMG) signals. This includes a compilation of the groups attempt to recognize basic facial expressions namely happy, angry, and sad through the use of EMG signals from facial muscles. The group extracted features from the three EMG signals from the face of two human subjects, a male and a female, and analyzed these features to serve as feature templates. Using a minimum-distance classifier, recognition rates exceeded the target accuracy - 85 percent - reaching 94.44 percent for both the male and female subjects.