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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Odinaka, I. Po-Hsiang Lai Kaplan, A.D. O'Sullivan, J.A. Sirevaag, E.J. Rohrbaugh, J.W. |
| Copyright Year | 2005 |
| Abstract | The electrocardiogram (ECG) is an emerging biometric modality that has seen about 13 years of development in peer-reviewed literature, and as such deserves a systematic review and discussion of the associated methods and findings. In this paper, we review most of the techniques that have been applied to the use of the electrocardiogram for biometric recognition. In particular, we categorize the methodologies based on the features and the classification schemes. Finally, a comparative analysis of the authentication performance of a few of the ECG biometric systems is presented, using our inhouse database. The comparative study includes the cases where training and testing data come from the same and different sessions (days). The authentication results show that most of the algorithms that have been proposed for ECG-based biometrics perform well when the training and testing data come from the same session. However, when training and testing data come from different sessions, a performance degradation occurs. Multiple training sessions were incorporated to diminish the loss in performance. That notwithstanding, only a few of the proposed ECG recognition algorithms appear to be able to support performance improvement due to multiple training sessions. Only three of these algorithms produced equal error rates (EERs) in the single digits, including an EER of 5.5% using a method proposed by us. |
| Sponsorship | IEEE Signal Processing Society |
| Starting Page | 1812 |
| Ending Page | 1824 |
| Page Count | 13 |
| File Size | 3176516 |
| File Format | |
| ISSN | 15566013 |
| Volume Number | 7 |
| Issue Number | 6 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-12-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Electrocardiography Feature extraction Authentication Training Heart beat Databases verification biometrics classification ECG EKG electrocardiogram fusion identification recognition |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Networks and Communications Safety, Risk, Reliability and Quality |
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