Publication
ECG-based biometrics: A real time classification approach
| dc.contributor.author | Lourenço, André Ribeiro | |
| dc.contributor.author | Silva, Hugo | |
| dc.contributor.author | Fred, Ana | |
| dc.date.accessioned | 2015-09-07T13:23:33Z | |
| dc.date.available | 2015-09-07T13:23:33Z | |
| dc.date.issued | 2012-11-12 | |
| dc.description.abstract | Behavioral biometrics is one of the areas with growing interest within the biosignal research community. A recent trend in the field is ECG-based biometrics, where electrocardiographic (ECG) signals are used as input to the biometric system. Previous work has shown this to be a promising trait, with the potential to serve as a good complement to other existing, and already more established modalities, due to its intrinsic characteristics. In this paper, we propose a system for ECG biometrics centered on signals acquired at the subject's hand. Our work is based on a previously developed custom, non-intrusive sensing apparatus for data acquisition at the hands, and involved the pre-processing of the ECG signals, and evaluation of two classification approaches targeted at real-time or near real-time applications. Preliminary results show that this system leads to competitive results both for authentication and identification, and further validate the potential of ECG signals as a complementary modality in the toolbox of the biometric system designer. | por |
| dc.identifier.citation | LOURENÇO, André; SILVA, Hugo; FRED, Ana – ECG-based biometrics: A real time classification approach. In 2012 IEEE International Workshop on Machine Learning for Signal Processing. Santander, Spain: IEEE, 2012. ISBN: 978-1-4673-1026-0. Pp. 1-6. | por |
| dc.identifier.doi | 10.1109/MLSP.2012.6349735 | |
| dc.identifier.eissn | 2378-928X | |
| dc.identifier.isbn | 978-1-4673-1026-0 | |
| dc.identifier.isbn | 978-1-4673-1024-6 | |
| dc.identifier.isbn | 978-1-4673-1025-3 | |
| dc.identifier.issn | 1551-2541 | |
| dc.identifier.uri | http://hdl.handle.net/10400.21/5080 | |
| dc.language.iso | eng | por |
| dc.peerreviewed | yes | por |
| dc.publisher | IEEE | por |
| dc.relation.publisherversion | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6349735 | |
| dc.subject | Biometric systems | por |
| dc.subject | ECG signal | por |
| dc.subject | Real time recognition systems | por |
| dc.subject | SVM classifiers | por |
| dc.title | ECG-based biometrics: A real time classification approach | por |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | New York | |
| oaire.citation.endPage | 6 | |
| oaire.citation.startPage | 1 | |
| oaire.citation.title | 2012 IEEE International Workshop on Machine Learning for Signal Processing | por |
| person.familyName | Silva | |
| person.givenName | Hugo | |
| person.identifier.orcid | 0000-0003-1585-9099 | |
| rcaap.rights | closedAccess | por |
| rcaap.type | conferenceObject | por |
| relation.isAuthorOfPublication | 8eb55ac9-195d-4a2e-aa62-eb6e004d5cd1 | |
| relation.isAuthorOfPublication.latestForDiscovery | 8eb55ac9-195d-4a2e-aa62-eb6e004d5cd1 |
Files
Original bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- ECG-BASED BIOMETRICS_ A REAL TIME CLASSIFICATION APPROACH.pdf
- Size:
- 1.91 MB
- Format:
- Adobe Portable Document Format
License bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- license.txt
- Size:
- 1.71 KB
- Format:
- Item-specific license agreed upon to submission
- Description: