On Real Time ECG Algorithms for Biometric Applications
Canento, F. A. L.
Fred, A. L. N.
On Real Time ECG Algorithms for Biometric Applications, Proc International Conf. on Bio-inspired Systems and Signal Processing - Biosignals - INSTICC, Barcelona, Spain, Vol. ?, pp. ? - ?, February, 2013.
Digital Object Identifier:
Recognizing an individual's identity through the use of characteristics intrinsic to that subject is a biometric recognition problem with increasingly number of modalities and applications. Recently, the electrical activity of the heart (the Electrocardiogram or ECG) has been explored as an additional modality to recognize individuals. The ECG signal contains several features, which are unique to each individual. The preprocessing of the ECG signal and the feature extraction steps are crucial for biometric recognition to be successful. In fiducial approaches, this last step is accomplished by correctly detecting the heart beats, and performing their segmentation to extract the biometric templates afterwards. In this work, we present an overview of the different steps of an ECG biometric system, focusing on the evaluation and comparison of multiple real-time heart beat detection and ECG segmentation algorithms, and their application to biometric systems. An evaluation and comparison of the algorithms with annotated datasets (MITDB, NSTDB) is presented, and methods to combine them in order to improve performance are discussed.