Paper Details: Downloads: 472
Serial Number: P1120836330
Title: Hidden Conditional Random Fields for ECG Classification
Authors: Reda A. El-Khoribi
Abstract: In this paper a novel approach to ECG signal classification is proposed. The approach is based on using hidden conditional random fields (HCRF) to model the ECG signal. Features used in training and testing the HCRF are based on time-frequency analysis of the ECG waveforms. Experimental results show that the HCRF model is promising and gives higher accuracy compared to maximum-likelihood (ML) trained hidden Markov models (HMM).
Keywords: ECG classification, hidden conditional random fields, hidden Markov models
Journal/Conference: International Journal of Artificial Intelligence and Machine Learning
Volume:
Issue:
Submission Date: 8/30/2008 12:00:00 AM
Review Date: 9/13/2008 12:00:00 AM
Publishing Date: 9/19/2008 12:00:00 AM
Article Downloads: 472
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