Title :
Cardiovascular Biometrics: Combining Mechanical and Electrical Signals
Author :
Odinaka, Ikenna ; O´Sullivan, James A. ; Sirevaag, Erik J. ; Rohrbaugh, John W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC, USA
Abstract :
The electrical signal originating from the heart, the electrocardiogram (ECG), has been examined for its potential use as a biometric. Recent ECG studies have shown that an intersession authentication performance <;6% equal error rate (EER) can be achieved using training data from two days while testing with data from a third day. More recently, a mechanical measurement of cardiovascular activity, the laser Doppler vibrometry (LDV) signal, was proposed by our group as a biometric trait. The intersession authentication performance of the LDV biometric system is comparable to that of the ECG biometric system. Combining both the electrical and mechanical aspects of the cardiovascular system, an overall improvement in authentication performance can be attained. In particular, the multibiometric system achieves ~2% EER. Moreover, in the identification mode, with a testing database containing 200 individuals, the rank-1 accuracy improves from ~80% for each individual biometric system, to ~92% for the multibiometric system. Although there are implementation issues that would need to be resolved before this combined method could be applied in the field, this report establishes the basis and utility of the method in principle, and it identifies effective signal analysis approaches.
Keywords :
Doppler measurement; biometrics (access control); cardiovascular system; cryptographic protocols; electrocardiography; laser applications in medicine; medical signal processing; ECG biometric system; EER; LDV biometric system; biometric trait; cardiovascular activity; cardiovascular biometrics; cardiovascular system; effective signal analysis; electrical aspects; electrical signals; electrocardiogram; equal error rate; heart; identification mode; individual biometric system; intersession authentication performance; laser Doppler vibrometry signal; mechanical aspects; mechanical measurement; mechanical signals; multibiometric system; rank-1 accuracy; testing database; training data; Authentication; Biometrics (access control); Electrocardiography; Feature extraction; Heart beat; Testing; Training; Authentication; Electrocardiogram; Emerging Biometrics; Identification; Laser Doppler Vibrometry (LDV); Multibiometrics; Time-frequency decomposition.; electrocardiogram; emerging biometrics; identification; laser Doppler vibrometry (LDV); multibiometrics; time-frequency decomposition;
Journal_Title :
Information Forensics and Security, IEEE Transactions on
DOI :
10.1109/TIFS.2014.2361261