Literature DB >> 17945967

ECG denoising based on the empirical mode decomposition.

Binwei Weng1, Manuel Blanco-Velasco, Kenneth E Barner.   

Abstract

The electrocardiogram (ECG) has been widely used for diagnosis purposes of heart diseases. Good quality ECG are utilized by the physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts. One prominent artifact is the high frequency noise caused by electromyogram induced noise, power line interferences, or mechanical forces acting on the electrodes. Noise severely limits the utility of the recorded ECG and thus need to be removed for better clinical evaluation. Several methods have been developed for ECG denoising. In this paper, we proposed a new ECG denoising method based on the recently developed Empirical Mode Decomposition (EMD). The proposed EMD-based method is able to remove high frequency noise with minimum signal distortion. The method is validated through experiments on the MIT-BIH database. Both quantitative and qualitative results are given. The results show that the proposed method provides very good results for denoising.

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Year:  2006        PMID: 17945967     DOI: 10.1109/IEMBS.2006.259340

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

1.  Arrhythmia ECG noise reduction by ensemble empirical mode decomposition.

Authors:  Kang-Ming Chang
Journal:  Sensors (Basel)       Date:  2010-06-17       Impact factor: 3.576

2.  Reconfigurable Architectures with High-Frequency Noise Suppression for Wearable ECG Devices.

Authors:  V Joseph Michael Jerard; M Thilagaraj; K Pandiaraj; M Easwaran; Petchinathan Govindan; V Elamaran
Journal:  J Healthc Eng       Date:  2021-12-22       Impact factor: 2.682

3.  A Hybrid Method of Covid-19 Patient Detection from Modified CT-Scan/Chest-X-Ray Images Combining Deep Convolutional Neural Network And Two- Dimensional Empirical Mode Decomposition.

Authors:  Nahian Ibn Hasan
Journal:  Comput Methods Programs Biomed Update       Date:  2021-07-23
  3 in total

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