Journal of Robotics Networking and Artificial Life · 2015 · 13 citations · 0 references
ComputingComputer EngineeringElectrical EngineeringAuthenticationHuman-computer InteractionMovement AnalysisBiometric AuthenticationElectromyogram AnalysisGesture AnalysisMobile Human-computer InteractionMuscle Signal ProcessingPassword AuthenticationBiometric Device AuthenticationElectromyography-based Gesture RecognitionElectromyography-based Human-computer InteractionMobile AuthenticationMotion Pattern GenerationMotion Pattern RecognitionSurface ElectromyographyUser Authentication
At the present time, mobile devices such as tablet-type PCs and smart phones have widely penetrated into our daily lives. Therefore, an authentication method that prevents shoulder surfing is needed. We are investigating a new user authentication method for mobile devices that uses surface electromyogram (s-EMG) signals, not screen touching. The s-EMG signals, which are generated by the electrical activity of muscle fibers during contraction, are detected over the skin surface. Muscle movement can be differentiated by analyzing the s-EMG. In this paper, a series of experiments was carried out to investigate the prospect of an authentication method using s-EMGs. Specifically, several gestures of the wrist were introduced, and the s-EMGs generated for each motion pattern were measured. We compared the s-EMG patterns generated by each subject with the patterns generated by other subjects. As a result, it was found that each subject has similar patterns that are different from those of other subjects. Thus, s-EMGs can be used to confirm one's identification for authenticating passwords on touchscreen devices.