Modeling Waveform Shapes with Random Effects Segmental Hidden Markov Models

@inproceedings{Kim2004ModelingWS,
  title={Modeling Waveform Shapes with Random Effects Segmental Hidden Markov Models},
  author={Seyoung Kim and Padhraic Smyth},
  year={2004}
}
In this paper we describe a general probabilistic framework for modeling waveforms such as heartbeats from ECG data. The model is based on segmental hidden Markov models (as used in speech recognition) with the addition of random effects to the generative model. The random effects component of the model handles shape variability across different waveforms within a general class of waveforms of similar shape. We show that this probabilistic model provides a unified framework for learning these… CONTINUE READING
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