title: Human facial neural activities and gesture recognition for machine-interfacing applications.
abstract: The authors present a new method of recognizing different human facial gestures through their neural activities and muscle movements, which can be used in machine-interfacing applications. Human-machine interface (HMI) technology utilizes human neural activities as input controllers for the machine. Recently, much work has been done on the specific application of facial electromyography (EMG)-based HMI, which have used limited and fixed numbers of facial gestures. In this work, a multipurpose interface is suggested that can support 2-11 control commands that can be applied to various HMI systems. The significance of this work is finding the most accurate facial gestures for any application with a maximum of eleven control commands. Eleven facial gesture EMGs are recorded from ten volunteers. Detected EMGs are passed through a band-pass filter and root mean square features are extracted. Various combinations of gestures with a different number of gestures in each group are made from the existing facial gestures. Finally, all combinations are trained and classified by a Fuzzy c-means classifier. In conclusion, combinations with the highest recognition accuracy in each group are chosen. An average accuracy >90% of chosen combinations proved their ability to be used as command controllers.
authors.affiliation: Faculty of Biomedical and Health Science Engineering, Department of Biomedical Instrumentation and Signal Processing, University of Technology Malaysia, Skudai, Malaysia.
authors.forename: M
authors.initials: M
authors.lastname: Hamedi
authors.forename: Sh-Hussain
authors.initials: ShH
authors.lastname: Salleh
authors.forename: T S
authors.initials: TS
authors.lastname: Tan
authors.forename: K
authors.initials: K
authors.lastname: Ismail
authors.forename: J
authors.initials: J
authors.lastname: Ali
authors.forename: C
authors.initials: C
authors.lastname: Dee-Uam
authors.forename: C
authors.initials: C
authors.lastname: Pavaganun
authors.forename: P P
authors.initials: PP
authors.lastname: Yupapin
mesh_terms: D001185:Artificial Intelligence; D001698:Biomedical Engineering; D004576:Electromyography / Q000379:methods*; D005145:Face / Q000502:physiology*; D005149:Facial Expression; D017143:Fuzzy Logic; D006801:Humans; D008328:Man-Machine Systems; D010363:Pattern Recognition, Automated / Q000379:methods; D012656:Self-Help Devices; D012815:Signal Processing, Computer-Assisted; D014584:User-Computer Interface