Segmentation of electrocardiograms using a hidden Markov model

Segmentation of electrocardiograms using a hidden Markov model

The purpose of this study is to segment electrocardiograms (ECG) and detect accurately the P-wave onset and offset in order to be able to discriminate some cardiac arrhythmias. A hidden Markov model is used to perform this segmentation. The model includes the amplitude and the slope of the samples....

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Clavier, L., Boucher, J.M.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Electrocardiography
Engineering in Medicine and Biology Society
Evolution (biology)
Hidden Markov models
Monitoring
Robustness
Shape measurement
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Beschreibung
Zusammenfassung:The purpose of this study is to segment electrocardiograms (ECG) and detect accurately the P-wave onset and offset in order to be able to discriminate some cardiac arrhythmias. A hidden Markov model is used to perform this segmentation. The model includes the amplitude and the slope of the samples. It segments the beats of the ECGs in twelve parts. The results are good and can be applied to most of the ECGs encountered.
DOI:10.1109/IEMBS.1996.647479