Publication detail

Detection of Myocardial Ischemia Using Hidden Markov Models

BARDOŇOVÁ, J., PROVAZNÍK, I., NOVÁKOVÁ, M.

Original Title

Detection of Myocardial Ischemia Using Hidden Markov Models

English Title

Detection of Myocardial Ischemia Using Hidden Markov Models

Type

conference paper

Language

en

Original Abstract

The paper deals with detection of myocardial ischemia by analysis of electrophysiological changes within QRS complexes of electrocardiograms (ECG). ECG signals were analysed by continuous wavelet transform (CWT). Time frequency spectra of QRS complexes were used as an input of a detection system based on hidden Markov models (HMMs). Parameters of the used HMMs were assessed to recommend their optimal values. The presented results show that HMM analysis of ECGs preprocessed by CWT can be used for early detection of myocardial ischemia. Eleven Langendorff perfused rabbit hearts were used to record training and test data to learn Markov models. An average value of resulting sensitivity and specificity of detection system was around 0.9 depending on parameter setting of the models.

English abstract

The paper deals with detection of myocardial ischemia by analysis of electrophysiological changes within QRS complexes of electrocardiograms (ECG). ECG signals were analysed by continuous wavelet transform (CWT). Time frequency spectra of QRS complexes were used as an input of a detection system based on hidden Markov models (HMMs). Parameters of the used HMMs were assessed to recommend their optimal values. The presented results show that HMM analysis of ECGs preprocessed by CWT can be used for early detection of myocardial ischemia. Eleven Langendorff perfused rabbit hearts were used to record training and test data to learn Markov models. An average value of resulting sensitivity and specificity of detection system was around 0.9 depending on parameter setting of the models.

Keywords

Myocardial ischemia, ECG signal, QRS complex, Wavelet transform, hidden Markov models

RIV year

2003

Released

01.09.2003

Publisher

IEEE

Location

Cancun

Pages from

1

Pages to

4

Pages count

4

Documents

BibTex


@inproceedings{BUT7870,
  author="Jana {Kolářová} and Ivo {Provazník} and Marie {Nováková}",
  title="Detection of Myocardial Ischemia Using Hidden Markov Models",
  annote="The paper deals with detection of myocardial ischemia by analysis of electrophysiological changes within QRS complexes of electrocardiograms (ECG). ECG signals were analysed by continuous wavelet transform (CWT). Time frequency spectra of QRS complexes were used as an input of a detection system based on hidden Markov models (HMMs). Parameters of the used HMMs were assessed to recommend their optimal values. The presented results show that HMM analysis of ECGs preprocessed by CWT can be used for early detection of myocardial ischemia. Eleven Langendorff perfused rabbit hearts were used to record training and test data to learn Markov models. An average value of resulting sensitivity and specificity of detection system was around 0.9 depending on parameter setting of the models.",
  address="IEEE",
  booktitle="Proceedings of Annual International Conference IEEE EMBS 2003",
  chapter="7870",
  institution="IEEE",
  year="2003",
  month="september",
  pages="1",
  publisher="IEEE",
  type="conference paper"
}