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Analysis of beta frequency spectrum for detect disparities using spectral analysis based on fir filter with chebyshev algorithm

Autorzy
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Beta waves is a frequency which can be split into three sections. In-formation about individual frequency gives more accurate diagnostic. FIR filter used to analysis recording EEG signal supports isolation Beta waves and analy-sis full spectrum. Analysis of this spectrum provide information that for example high Beta2 is connecting witch more stress, less SMR correlate witch attention deficit and cognitive function.
Słowa kluczowe
Rocznik
Tom
Strony
127--130
Opis fizyczny
Bibliogr. 12 poz., rys., tab.
Twórcy
autor
  • Faculty of Electrical Engineering, Automatic Control and Informatics Institute of Drive Systems and Robotics
Bibliografia
  • [1] ROMERO M., DE MADRID A.P., MANOSO C., VINAGRE B.M.: IIR approximations to the fractional differentiator/integrator using Chebyshev polynomials theory, Elsevier, 2013
  • [2] PAVLOVIĆ V., STANOJKO N., GRADIMIR D.: 1D and 2D economical FIR filters generated by Chebyshev polynomials of the first kind, International Journal of Electronics, 2013
  • [3] DINIZ P.S.R., DA SILVA E.A.B., NETTO S.L.: Digital Signal Processing System Analysis and Design, 2nd Edition, Cambridge, 2010
  • [4] ZANDI A.S., DUMONT G.A., YEDLIN M.J., LAPEYRIE P., SUDRE C., GAFFET S.: Scalp EEG Acquisition in a Low-Noise Environment: A Quantitative Assessment, IEEE Transactions on Biomedical Engineering, Vol. 58, No. 8, 2011
  • [5] MURALI L., CHITRA D., MANIGANDAN T., SHARANYA B.: An Efficient Adaptive Filter Architecture for Improving the Seizure Detection in EEG Signal, Springer Science+Business Media, New York, 2015
  • [6] HOMAN R.W., HERMAN J., PURDY P.: Cerebral location of international 10–20 system electrode placement; Electroencephalography and clinical neurophysiology, vol. 66, pp. 376–382 1987
  • [7] BLACKBURN D., YIFAN Z., BELL S., DE MARCO M., HE F., WILKINSON I., FARROW T., VENNERI A.: Ptolemaios Sarrigiannis; QEEG can distinguish patients with ad and volountrees, Neurol. Neurosurg. Psychiatry, 2016
  • [8] CHABOT R.J., MERKIN H., WOOD L.M., DAVENPORT T.L., SERFONTEIN G.: Sensitivity and specificity of QEEG in children with attention deficit or specific developmental learning disorders. Clinical Electroencephalography, Vol. 27, Issue 1, pp. 26–34, 1996
  • [9] 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
  • [10] Neurofeedback in ADHD, Forties 2016
  • [11] HERRMANN CH.S., STRUBER D., HELFRICH R.F., ENGEL A.K.: EEG oscillations: From correlation to causality, Int. Journal of Psychophysiology, 2015
  • [12] MORILLAS-ROMERO A., TORTELLA-FELIU M., BORNAS X., PUTMAN P.: Spontaneous EEG theta/beta ratio and delta-beta coupling in relation to attentional network functioning and self-reported attentional control, Cognitive Affective & Behavioral Neuroscience, Vol. 15, Issue 3, pp. 598–606, 2015
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-38d166f0-1e0f-4b48-9af3-314095c485c1
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