Logo des Repositoriums
 

Explaining ECG Biometrics: Is It All In The QRS?

Kurzanzeige
dc.contributor.authorPinto, João Ribeiro
dc.contributor.authorCardoso, Jaime S.
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorDantcheva, Antitza
dc.contributor.editorRaja, Kiran
dc.contributor.editorRathgeb, Christian
dc.contributor.editorUhl, Andreas
dc.date.accessioned2020-09-16T08:25:43Z
dc.date.available2020-09-16T08:25:43Z
dc.date.issued2020
dc.description.abstractThe literature seems to indicate that the QRS complex is the most important component of the electrocardiogram (ECG) for biometrics. To verify this claim, we use interpretability tools to explain how a convolutional neural network uses ECG signals to identify people, using on-theperson (PTB) and off-the-person (UofTDB) signals. While the QRS complex appears indeed to be a key feature on ECG biometrics, especially with cleaner signals, results indicate that, for larger populations in off-the-person settings, the QRS shares relevance with other heartbeat components, which it is essential to locate. These insights indicate that avoiding excessive focus on the QRS complex, using decision explanations during training, could be useful for model regularisation.en
dc.identifier.isbn978-3-88579-700-5
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34321
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-306
dc.subjectBiometrics
dc.subjectElectrocardiogram
dc.subjectExplainability
dc.subjectIdentification
dc.subjectInterpretability
dc.titleExplaining ECG Biometrics: Is It All In The QRS?en
dc.typeText/Conference Paper
gi.citation.endPage150
gi.citation.publisherPlaceBonn
gi.citation.startPage139
gi.conference.date16.-18. September 2020
gi.conference.locationInternational Digital Conference
gi.conference.sessiontitleRegular Research Papers

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
Name:
BIOSIG_2020_paper_23_update.pdf
Größe:
2.18 MB
Format:
Adobe Portable Document Format
Herunterladen

Sammlungen

P306 - BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group