Paper
13 February 2018 Use of parallel computing for analyzing big data in EEG studies of ambiguous perception
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Abstract
Problem of interaction between human and machine systems through the neuro-interfaces (or brain-computer interfaces) is an urgent task which requires analysis of large amount of neurophysiological EEG data. In present paper we consider the methods of parallel computing as one of the most powerful tools for processing experimental data in real-time with respect to multichannel structure of EEG. In this context we demonstrate the application of parallel computing for the estimation of the spectral properties of multichannel EEG signals, associated with the visual perception. Using CUDA C library we run wavelet-based algorithm on GPUs and show possibility for detection of specific patterns in multichannel set of EEG data in real-time.
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Vladimir A. Maksimenko, Vadim V. Grubov, and Daniil V. Kirsanov "Use of parallel computing for analyzing big data in EEG studies of ambiguous perception", Proc. SPIE 10493, Dynamics and Fluctuations in Biomedical Photonics XV, 104931H (13 February 2018); https://doi.org/10.1117/12.2291697
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Electroencephalography

Brain-machine interfaces

Wavelets

Brain

Parallel computing

Continuous wavelet transforms

Analytical research

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