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- W2977996046 abstract "A new algorithm of electroencephalograph(EEG)source localization based on wavelet packet transform is proposed to obtain the neural electrical activity distribution of brain.Conducting wavelet packet decomposition for neural electrical signals,subspace component selection and signal reconstruction,an inverse problem with a MRI-based three-layer head model is solved.A comparative investigation includes signal-to-noise ratio(SNR),dipole source depth and electrode number.The results indicate that in different circumstances,the average distances between the reconstructed sources of the proposed algorithm and the setting sources get less than3mm,and the standard deviations about 1 mm,while the average distances and the standard deviations of the existing algorithm achieve up to 9.4mm and 4.5mm,respectively;in the same circumstances,the means and standard deviations of the proposed algorithm get less than that of the algorithm,and can be reduced by up to 6.6mm and 3.5mm,respectively.The proposed algorithm is endowed with better localization accuracy and enhanced robustness than the existing algorithm(P0.05)to show the clinical significance." @default.
- W2977996046 created "2019-10-10" @default.
- W2977996046 creator A5032108395 @default.
- W2977996046 date "2013-01-01" @default.
- W2977996046 modified "2023-09-27" @default.
- W2977996046 title "An Electroencephalograph Source Localization Algorithm Based on Wavelet Packet Transform with Simulation" @default.
- W2977996046 hasPublicationYear "2013" @default.
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