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Communication Dans Un Congrès Année : 2018

R-peak detection in holter ECG signals using non-negative matrix factorization

Résumé

Holter monitoring is mainly used for medical follow- up and diagnosis of patients with suspected cardiac ar- rhythmia such as heart rhythm irregularities that can be missed during classical electrocardiogram recording (ECG). However, these long-term continuous recordings represent a large amount of data that cannot be processed by hand. In this article, we present a new method based on Non-negative Matrix Factorization (NMF) to detect R- peaks in Holter signals. The approach consists in two stages: source separation based on the different time- frequency patterns of the QRS complexes and the other waves of the signal (P and T waves) and R-peak detection using Automatic Objective Thresholding (AOT). The pro- posed approach is validated on the MIT-BIH Arrhythmia database and achieves an average sensitivity of 99.59% and a precision of 99.69%. Using the MIT-BIH Noise Stress Test database, we also show the ability of our ap- proach to discriminate R-peaks in signals contaminated with different noises.
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Dates et versions

hal-01925853 , version 1 (17-11-2018)

Identifiants

  • HAL Id : hal-01925853 , version 1

Citer

Pauline Guyot, Pascal Voiriot, El-Hadi Djermoune, Stéphane Papelier, Céline Lessard, et al.. R-peak detection in holter ECG signals using non-negative matrix factorization. 45th Computing in Cardiology Conference, CinC 2018, Sep 2018, Maastricht, Netherlands. ⟨hal-01925853⟩
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