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Advisor(s)
Abstract(s)
Biosignals analysis has become widespread, upstaging their typical use in clinical settings. Electrocardiography (ECG) plays a central role in patient monitoring as a diagnosis tool in today's medicine and as an emerging biometric trait. In this paper we adopt a consensus clustering approach for the unsupervised analysis of an ECG-based biometric records. This type of analysis highlights natural groups within the population under investigation, which can be correlated with ground truth information in order to gain more insights about the data. Preliminary results are promising, for meaningful clusters are extracted from the population under analysis. © 2014 EURASIP.
Description
Keywords
Consensus Clustering ECG Analysis ECG-Based Biometrics Evidence Accumulation
Citation
LOURENÇO, André Ribeiro; [et al] – ECG analysis using consensus clustering. In European Signal Processing Conference. EUSIPCO - European Signal Processing Conference, 2014. ISSN: 2219-5491. Art. nr. 6952141, p. 511-515.
Publisher
European Signal Processing Conference, EUSIPCO