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Methods Inf Med 1994; 33(01): 10-14
DOI: 10.1055/s-0038-1634971
DOI: 10.1055/s-0038-1634971
Original Article
Heart Signal Recognition by Hidden Markov Models: The ECG Case
Further Information
Publication History
Publication Date:
08 February 2018 (online)
Abstract:
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 perfomance of ECG recognition compared to classical HMMs.
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