Evaluation of feature values of surface electromyograms for user authentication on mobile devices

Abstract

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 use 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 method that uses a list of gestures as a password is proposed. And also, results of experiments are presented that was carried out to investigate the performance of the method extracting feature values from s-EMG signals (using the Fourier transform) adopted in this research. $Myo^{TM}$, which is the candidate of s-EMG measurement device used in a prototype system for future substantiative experiments, was used in the experiment together with the s-EMG measuring device used in the previous research to investigate its performance.