Spatially revolved high density electroencephalography

Jerry Wu; Harold Szu; Yuechen Chen; Ran Guo; Xixi Gu

doi:10.1117/12.2184655

3 June 2015 Spatially revolved high density electroencephalography

Jerry Wu, Harold Szu, Yuechen Chen, Ran Guo, Xixi Gu

Proceedings Volume 9496, Independent Component Analyses, Compressive Sampling, Large Data Analyses (LDA), Neural Networks, Biosystems, and Nanoengineering XIII; 94960S (2015) https://doi.org/10.1117/12.2184655
Event: SPIE Sensing Technology + Applications, 2015, Baltimore, MD, United States

Abstract

Electroencephalography (EEG) measures voltage fluctuations resulting from ionic current flows within the neurons of the brain. In practice, EEG refers to the recording of the brain's spontaneous electrical activity over a short period of time, several tens of minutes, as recorded from multiple electrodes placed on the scalp. In order to improve the resolution and the distortion cause by the hair and scalp, large array magnetoencephalography (MEG) systems are introduced. The major challenge is to systematically compare the accuracy of epileptic source localization with high electrode density to that obtained with sparser electrode setups. In this report, we demonstrate a two dimension (2D) image Fast Fourier Transform (FFT) analysis along with utilization of Peano (space-filling) curve to further reduce the hardware requirement for high density EEG and improve the accuracy and performance of the high density EEG analysis. The brain–computer interfaces (BCIs) in this work is enhanced by A field-programmable gate array (FPGA) board with optimized two dimension (2D) image Fast Fourier Transform (FFT) analysis.

Citation Download Citation

Jerry Wu, Harold Szu, Yuechen Chen, Ran Guo, and Xixi Gu "Spatially revolved high density electroencephalography", Proc. SPIE 9496, Independent Component Analyses, Compressive Sampling, Large Data Analyses (LDA), Neural Networks, Biosystems, and Nanoengineering XIII, 94960S (3 June 2015); https://doi.org/10.1117/12.2184655

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