Quantitative analysis of EEG signals: Time-frequency methods and ...

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Aus dem Institut fur Physiologie vertreten in der Technisch-Naturwissenschaftlichen Fakultat der Medizinischen Universitat zu Lubeck durch das Institut fur Signalverarbeitung und Prozessrechentechnik Direktoren: Prof. Dr. med. Wolfgang Jelkmann (Institut fur Physiologie) Prof. Dr.-Ing. Til Aach (Institut fur Signalverarbeitung und Prozessrechentechnik) Quantitative Analyse von EEG-Signalen: Zeit-Frequenz-Methoden und Chaos-Theorie Inauguraldissertation zur Erlangung der Doktorwurde der Medizinischen Universitat zu Lubeck -Ausder Technisch-Naturwissenschaftlichen Fakultat - Vorgelegt von Rodrigo Quian Quiroga aus Buenos Aires, Argentinien Lubeck, 1998
1. Berichterstatter: Prof. Dr.-Ing. Til Aach 2. Berichterstatter: Prof. Dr.-Ing Erol Basar Tag der mundlichen Prufung: 04.12.98 Zum Druck genehmigt, Lubeck, den 18.05.1999 gez. Prof. Dr.-Ing. Erik Maehle. - Dekan der Technisch-Naturwissenschaftlichen Fakultat - ii
Page 1: Quantitative analysis of EEG signal
Page 5 and 6: an okzipitalen Positionen und (c) d
Page 8 and 9: To my family: Mama, Consuelo, Hugui
Page 10 and 11: Preface In this work, I will descri
Page 12 and 13: I would certainly like to remember
Page 14 and 15: Contents Zusammenfassung Preface Ac
Page 16 and 17: 5.2.6 Calculating Lyapunov Exponent
Page 18 and 19: Summary Since the rsts recordings i
Page 20 and 21: 1 Outline of Neurophysiology: Brain
Page 22 and 23: Figure 2: Normal 20 channels (10-20
Page 24 and 25: 1.1.2 EEG in Epilepsy One important
Page 26 and 27: Figure 3: Scalp EEG of 18 channels
Page 28 and 29: Figure 4: Averaged responses upon N
Page 30 and 31: 2 Fourier Transform 2.1 Introductio
Page 32 and 33: I xx (k) =jX(k)j 2 = X(k) X (k) (
Page 34 and 35: 17 Figure 5: Topographical mapping
Page 36 and 37: 1987) is that coherence gives the c
Page 38 and 39: 3 Gabor Transform (Short Time Fouri
Page 40 and 41: where k g D k= R 1 ;1 jg D(t 0 )j 2
Page 42 and 43: and the band maximum peak frequency
Page 44 and 45: Figure 7: Intracraneal seizure reco
Page 46 and 47: Figure 10: Mean (soft line) and max
Page 48 and 49: EEG as the one with least amount of
Page 50 and 51: Figure 11: Scalp EEG of the right c
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3.5 Conclusion In this chapter I de
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Original signal FOURIER TRANSFORM G
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4.2.3 Multiresolution Analysis Cont
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Original signal -15 0 15 -1sec 0 1s
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4.2.5 Wavelet Packets In the approa
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marked decrease in computational ti
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ain activity during an epileptic se
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3 2 3 3 3 3.2 Hz 3.6 Hz 4.0 Hz 4.4
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Silva et al.,1973a,1973b Lopes da S
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sweep #1 sweep #2 sweep #3 sweep #4
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VEP non-target target F3 F4 F3 F4 F
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VEP non-target target F3 F4 F3 F4 F
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Electrode F3 F4 Cz P3 P4 O1 O2 Dela
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In conclusion, our results point to
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63 Figure 22: Gamma responses for a
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Figure 24: T-test comparison of the
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wavelet coecients allowed an easy d
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the position vs. the linear momentu
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unknown topology it is necessary to
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the sum of the positive exponents (
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performed. On one hand, must be lar
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Duke (1992) and Elbert et al. (1994
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agation time. They applied this pro
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Figure 28: Histogram for the EEG da
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Figure 29: Attractors corresponding
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able for automatic detection proces
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ENTROPY Thermodynamics Signal analy
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6.3 Application to visual event-rel
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VEP Non Target Target F3 -20 -10 0
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1 VEP NON-TARGET TARGET 1 1 F3 F3 0
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1 VEP NON-TARGET TARGET 1 1 F3 F3 0
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and the Lorenz equations (a model o
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P300 deection. Due to the relation
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7 General Discussion In this chapte
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Wavelet analysis was also applied t
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aect the whole spectrum and for thi
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peaks. 7.2.3 Wavelet Transform vs.
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the ones having wide peaks (being t
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A Time-frequency resolution and the
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Z 1 ;1 tx(t) d dt x(t) dt = 1 2 Z 1
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Figure 37: Time-frequency resolutio
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References Abarbanel HDI, Brown R,
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Berger, H. Uber das Elektrenkephalo
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Gastaut H and Broughton R. Epilepti
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Lopes da Silva FH, van Lierop THMT,
Page 142 and 143:
Pradhan N, Sadasivan P, Chatterji S
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Serrano E, Ph.D. Thesis, Department
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Biographical sketch 21.03.1967 born
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