Biometric Authentication of Individual using SEMG Signals
Samer Chantaf1, Amine Naït Ali2, Mohamad Khalil3, Mahmoud Abbas4
1Dr. Samer Chantaf, Department of Computer Communication and Networks Engineering, Lebanese Institute of Technology of University, Saida, Lebanon.
2Prof. Amine Nait Ali, Laboratoire Images Signaux Systèmes Intelligents LISSI, EA, Université Paris Est Créteil UPEC, Créteil France.
3Prof. Mohamad Khalil, Lebanese Doctoral, Department of Sciences and Technology, Tripoli Lebanon.
4Dr. Mahmoud Abbas, Department of Computer Communication and Networks Engineering, Lebanese Institute of Technology of University, Saida Lebanon.
Manuscript received on 9 May 2015 | Revised Manuscript received on 25 May 2015 | Manuscript Published on 30 May 2015 | PP: 69-72 | Volume-4 Issue-12, May 2015 | Retrieval Number: L20650541215/15©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this study, a new biometric method based on surface EMG (SEMG) signals in response to a fixed force is developed. The main goal is to study the possibility of a contactless verification of individuals by using SEMG signals. This method based on estimating the power spectral density (PSD) of the SEMG signals, and then extracting frequency parameters that will be used in radial basis function (RBF) to classify individuals. At fixed intensity of Maximum Voluntary Contraction (MVC), SEMG signals have shown good performance and high specify regardless of fatigue or electrode displacement. This role may have vital impact on the biometric field.
Keywords: SEMG, Biometrics, PSD, RBF, MVC, Classification.
Scope of the Article: Authentication, Authorization, Accounting