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    A Machine Learning Approach for Artifact Removal from Brain Signal

    Sandhyalati Behera, Mihir Narayan Mohanty*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1455-1467, 2023, DOI:10.32604/csse.2023.029649

    Abstract Electroencephalography (EEG), helps to analyze the neuronal activity of a human brain in the form of electrical signals with high temporal resolution in the millisecond range. To extract clean clinical information from EEG signals, it is essential to remove unwanted artifacts that are due to different causes including at the time of acquisition. In this piece of work, the authors considered the EEG signal contaminated with Electrocardiogram (ECG) artifacts that occurs mostly in cardiac patients. The clean EEG is taken from the openly available Mendeley database whereas the ECG signal is collected from the Physionet database to create artifacts in… More >

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