Paper Info
Title
A Unifying Approach To Ecg Biometric Recognition Using The Wavelet Transform
Abstract
Biometric recognition systems use measures from the body itself to determine the identity of an individual. The electrocardiogram (ECG) has been increasingly used as a biometric measure for person identification, as it is an easily measurable characteristic of all individuals. Our method for ECG acquisition follows an off-the-person approach, using a single ECG lead with non-gelled electrodes placed at the hands. However, this signal is noisier than typical ECG signals acquired on the chest, making subsequent processing more difficult. Therefore, we investigate the applicability of the Wavelet Transform (WT), which decomposes a signal into a time-scale representation according to a given mother wavelet. We use this representation to both segment the R wave of the ECG signal, and as the features for the classification step, defining an appropriate distance measure. We test this framework with real data, using various mother wavelets. Our experimental results show the potential of this framework, and that the best mother wavelet for the evaluated context is the rbio5.5.
Year
DOI
Venue
2013
10.1007/978-3-642-39094-4_7
IMAGE ANALYSIS AND RECOGNITION
Keywords
Field
DocType
Biometrics, ECG, Wavelet Transform, QRS detection, Wavelet Distance
Computer vision,Signature recognition,Pattern recognition,Computer science,Measure (mathematics),QRS complex,Artificial intelligence,Biometrics,Wavelet,Wavelet transform
Conference
Volume
ISSN
Citations 
7950
0302-9743
5
PageRank 
References 
Authors
0.47
14
4
Name
Order
Citations
PageRank
Carlos Carreiras1416.96
André Lourenço231245.33
Hugo Silva322730.18
Ana L. N. Fred41317195.30