A novel Modified Continuous Variable Duration HMM approach improves ECG wave recognition performance over classical HMMs.
May enhance algorithmic ECG recognition; leaves open clinical validation and generalizability.
Wave recognition in ECG signals by Hidden Markov Models (HMMs) relies on the stationary assumption for the set of parameters used to describe ECG waves. This approach seems unnatural and consequently generates severe errors in practice. A new class of HMMs called Modified Continuous Variable Duration HMMs is proposed to account for the specific properties of the ECG signal. An application of the latter, coupled with a multiresolution front-end analysis of the ECG is presented. Results show these methods can increase the performance of ECG recognition compared to classical HMMs.
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Thoraval et al. (1994) studied this question.
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