nips nips2003 nips2003-123 nips2003-123-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Nicholas P. Hughes, Lionel Tarassenko, Stephen J. Roberts
Abstract: We examine the use of hidden Markov and hidden semi-Markov models for automatically segmenting an electrocardiogram waveform into its constituent waveform features. An undecimated wavelet transform is used to generate an overcomplete representation of the signal that is more appropriate for subsequent modelling. We show that the state durations implicit in a standard hidden Markov model are ill-suited to those of real ECG features, and we investigate the use of hidden semi-Markov models for improved state duration modelling. 1
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