Study of Identify Authentication Based on Wavelet Decomposition

Article Preview

Abstract:

the identity authentication is the information society to a commonly used means of information protection, with what kind of identity certification tool is to determine the success or failure of the key authentication, studies show that EEG signal is difficult to counterfeit, therefore the EEG signal is one of the identity certification tool selection. This article uses the wavelet decomposition as data analysis tools, analysis of the EEG signals under normal collected, results show that the acquisition in normal EEG signal, using this method can well identify subjects.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1449-1452

Citation:

Online since:

September 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Zeng F, Tseng K K, Huang H N, et al. A new statistical-based algorithm for ECG identification, Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2012 Eighth International Conference on. IEEE, 2012: 301-304.

DOI: 10.1109/iih-msp.2012.79

Google Scholar

[2] Zhao Z, Yang L, Chen D, et al. A Human ECG Identification System Based on Ensemble Empirical Mode Decomposition. Sensors, 2013, 13(5): 6832-6864.

DOI: 10.3390/s130506832

Google Scholar

[3] Bhalla M C, Mencl F, Gist M A, et al. Prehospital electrocardiographic computer identification of ST-segment elevation myocardial infarction. Prehospital Emergency Care, 2013, 17(2): 211-216.

DOI: 10.3109/10903127.2012.722176

Google Scholar

[4] Malakhov A I, Schookin S I, Ivancov V I, et al. A Combined Algorithm for Identification and Differentiation of Atrial Flutter and Atrial Fibrillation Based on ECG Analysis. Biomedical Engineering, 2013: 1-4.

DOI: 10.1007/s10527-013-9324-y

Google Scholar

[5] Wijnmaalen A P, Stevenson W G, Schalij M J, et al. ECG identification of scar-related ventricular tachycardia with a left bundle-branch block configuration. Circulation: Arrhythmia and Electrophysiology, 2011, 4(4): 486-493.

DOI: 10.1161/circep.110.959338

Google Scholar

[6] Sufi F, Khalil I, Mahmood A. Compressed ECG biometric: a fast, secured and efficient method for identification of CVD patient. Journal of medical systems, 2011, 35(6): 1349-1358.

DOI: 10.1007/s10916-009-9412-4

Google Scholar

[7] Daudelin D H, Sayah A J, Kwong M, et al. Improving use of prehospital 12-lead ECG for early identification and treatment of acute coronary syndrome and ST-elevation myocardial infarction. Circulation: Cardiovascular Quality and Outcomes, 2010, 3(3): 316-323.

DOI: 10.1161/circoutcomes.109.895045

Google Scholar

[8] Mu Z, Hu J. Research of EEG identification computing based on AR model, BioMedical Information Engineering, 2009. FBIE 2009. International Conference on Future. IEEE, 2009: 366-368.

DOI: 10.1109/fbie.2009.5405847

Google Scholar