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Abstrakty
Determining the characteristic values of disorders in EEG signal may be helpful in diagnostics in the same way as searching for charcateristic patterns of disorders in tested signal. The co-ordinate method used to definie characteristics values of the signal works well with decision methods such as decision trees, neural networks etc. Thus, it can be used in automated screening diagnostics and automated disorder diagnostics.
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Tom
Strony
123--128
Opis fizyczny
Bibliogr. 14 poz., rys., tab.
Twórcy
autor
- Faculty of Electrical Engineering, Automatic Control and Informatics Institute of Computer Science
Bibliografia
- [1] WALKER J.: Fast Fourier Transformation, second edition, CRC Press Taylor & Francis Group, 1996
- [2] NIEDBALSKI P., et al.: The neurofeedback methodology to train the brain, Przeglad Elektrotechniczny, Vol. 90(4), pp. 249–251, 2014
- [3] MOSKWA K., REJER I.: How human perceive an application error? Error potential study, Przeglad Elektrotechniczny, Vol. 93(1), pp. 100–104, 2017
- [4] BLACKBURN D., et al.: QEEG can distinguish patients with ad and volunteers, Neurol neurosurg psychiatry, 2016
- [5] COCHIN S., BARTHELEMY C., LEJEUNE B., ROUX S., MARTINEAU J.: Perception of motion and qEEG activity in human adults. Electroencephalography and clinical neurophysiology, vol. 107(4), pp. 287–295, 1998
- [6] SCHUSTER A.: On the investigation of hidden periodicities with application to a supposed 26 day period of meteorological phenomena, Terrestrial Magnetism, Vol. 3(1), pp. 13–41, 1898
- [7] WELCH P.: The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms, IEEE Transactions on audio and electroacoustics, Vol. 15(2), pp. 70–73, 1967
- [8] The MathWorks, Inc.: Welch Method, available on-line: https://uk.mathworks.com/ help/signal/ref/pwelch.html, 2015
- [9] ZHOU Y., FANG K., ZHAO K.: A Novel Credibility Quantification Method for Welch’s Periodogram Analysis Result in Model Validation, Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, Vol. 142, pp. 783–788, 2016
- [10] BAKHSHI A.D., AHMED A., GULFARM S.M., et al.: Estimation of Baseline Wander Characteristics in ECG Signals Using Adaptive Transversal Filter and Lomb’s Periodogram Analysis,Przegląd Elektrotechniczny, vol. 89(5), pp. 107–110, 2013
- [11] KUBACKI A., SAWICKI L., OWCZAREK P.:Detection of facial gestures artefacts created during an EEG research using artificial neural networks,21st International Conference on Methods and Models in Automation and Robotics (MMAR), 2016
- [12] The MathWorks, Inc.: Periodogram, https://uk.mathworks.com/help/signal/ref/ periodogram.html, 2015
- [13] PELC M.: Policy – based reconfiguration of the computer control system, Studies and Monographs, Vol. 335, Opole, 2013
- [14] WALLISCH P.: MATLAB for Neuroscientists, An Introduction to Scientific Computing in MATLAB, 2nd Edition, pp. 287–296 and 237–243, 2014
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
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Bibliografia
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bwmeta1.element.baztech-4895d5c7-cb15-4c92-b883-16d8ceb36045