Artifacts Removal of EEG Signals By the Application of ICA and Double Density DWT Algorithm
Автор: Vandana Roy, Shailja Shukla
Журнал: International Journal of Engineering and Manufacturing(IJEM) @ijem
Статья в выпуске: 2 vol.4, 2014 года.
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Independent Component Analysis is used for the automation and detection of brain artifacts. The Independent Component Analysis (ICA) here is used for the segmentation of artifact peaks in the signal. Then the Discrete Wavelet Transform is applied for multi-level transfer of signal data until the reception of significant result. We have extended our search and applied the Double Density Algorithm for the multi-level transfer. The results obtained were analyzed from the data set of EEG signals taken with a outsource reference. Since the method is parameter free implementations in clinical settings are imaginable.
Artifacts, EEG Signals, Double Density, Wavelet Denoising
Короткий адрес: https://sciup.org/15014361
IDR: 15014361
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