Markov models for automated ECG interval analysis
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 subseque...
| Egile Nagusiak: | , , |
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| Formatua: | Conference item |
| Argitaratua: |
Neural information processing systems foundation
2004
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