ECG Artifact Removal from Surface EMG Signal Using an Automated Method Based on Wavelet-ICA.

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ID: 55828
2015
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Ranked #114 of 170 articles by views in Studies in health technology and informatics

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Abstract
This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact components from the original EMG signal. Components that correspond to the ECG artifact are then identified by an automated detection algorithm and are subsequently removed using a conventional high pass filter. Finally, the results of the proposed method are compared with wavelet transform, ICA, adaptive filter and empirical mode decomposition-ICA methods. The automated artifact removal method proposed in this study successfully removes the ECG artifacts from EMG signals with a signal to noise ratio value of 9.38 while keeping the distortion of original EMG to a minimum.
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abbaspour2015ecgstudies Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Abbaspour, Sara;Lindén, Maria;Gholamhosseini, Hamid;
Journal Studies in health technology and informatics
Year 2015
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