Cardiovascular Biometrics: Combining Mechanical and Electrical Signals

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 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 2$ </tex-math></inline-formula> % EER. Moreover, in the identification mode, with a testing database containing 200 individuals, the rank-1 accuracy improves from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 80$ </tex-math></inline-formula> % for each individual biometric system, to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 92$ </tex-math></inline-formula> % 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.