title: Feasibility of facial EMG in gender classification during speech production.
abstract: Gender identification has its unique importance in sports and forensic sciences. However, the social issues are major constraints to identify the gender of a human being. A novel approach for gender classification using facial EMG is presented. The time domain features of facial EMGs are explored towards their robustness in gender identification. A Davies-Bouldin index is calculated to evaluate the features. Anterior belly of digastrics along with Orbicularis Oris Inferior showed the promising classification accuracy of 80% with the reported features. A possible enhancement in accuracy could be possible by a larger dataset.
authors.affiliation: Department of Electrical and Electronics Engineering, Graphic Era University, Dehradun, India.
authors.forename: Anoop Kant
authors.initials: AK
authors.lastname: Godiyal
authors.forename: Richa
authors.initials: R
authors.lastname: Sharma
authors.forename: Deepak
authors.initials: D
authors.lastname: Joshi
authors.forename: Dinesh
authors.initials: D
authors.lastname: Bhatia
mesh_terms: D000293:Adolescent; D000328:Adult; D004576:Electromyography; D005152:Facial Muscles / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D012727:Sex Characteristics; D013060:Speech / Q000502:physiology*; D055815:Young Adult