Real Time Electrocardiogram Segmentation for Finger Based Ecg Biometrics (original) (raw)
Related papers
2012
Recognizing an individual’s identity through the use of characteristics intrin sic 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 a dditional 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 biometr ic r cognition 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 pres nt an overview of the different steps of an ECG biometric system, focusing on the evaluation and comp arison of multiple real-time heart beat detection and ECG segmentation algorithms, and their application to biome tric systems. An evaluation and compar...
Unveiling the Biometric Potential of Finger-Based ECG Signals
Computational Intelligence and Neuroscience, 2011
The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollmen...
Biometric personal identification system using the ECG signal
The electrocardiogram has unique cardiac features to each individual, which motivated us to use it as a biometric, hence, its robust nature against falsification makes it rather reliable for security systems, as it offers ultimate security in all situations. This paper presents a new approach applying this ECG particularity. A robust ECG Biometrics based on the features extraction with fiducial detection in the time domain is proposed.