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

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Figure 7: Intracraneal seizure recording. Seizure starts at about second 10 and ends at about second 54. 27
Figure 8: Spectrogram of the previous EEG recording. Figure 9: RIR of the previous seizure recording. 28
Page 1 and 2: Quantitative analysis of EEG signal
Page 3 and 4: 1. Berichterstatter: Prof. Dr.-Ing.
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 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
Page 52 and 53: 3.5 Conclusion In this chapter I de
Page 54 and 55: Original signal FOURIER TRANSFORM G
Page 56 and 57: 4.2.3 Multiresolution Analysis Cont
Page 58 and 59: Original signal -15 0 15 -1sec 0 1s
Page 60 and 61: 4.2.5 Wavelet Packets In the approa
Page 62 and 63: marked decrease in computational ti
Page 64 and 65: ain activity during an epileptic se
Page 66 and 67: 3 2 3 3 3 3.2 Hz 3.6 Hz 4.0 Hz 4.4
Page 68 and 69: Silva et al.,1973a,1973b Lopes da S
Page 70 and 71: sweep #1 sweep #2 sweep #3 sweep #4
Page 72 and 73: VEP non-target target F3 F4 F3 F4 F
Page 74 and 75: VEP non-target target F3 F4 F3 F4 F
Page 76 and 77: Electrode F3 F4 Cz P3 P4 O1 O2 Dela
Page 78 and 79: In conclusion, our results point to
Page 80 and 81: 63 Figure 22: Gamma responses for a
Page 82 and 83: Figure 24: T-test comparison of the
Page 84 and 85: wavelet coecients allowed an easy d
Page 86 and 87: the position vs. the linear momentu
Page 88 and 89: unknown topology it is necessary to
Page 90 and 91: the sum of the positive exponents (
Page 92 and 93: performed. On one hand, must be lar
Page 94 and 95:
Duke (1992) and Elbert et al. (1994
Page 96 and 97:
agation time. They applied this pro
Page 98 and 99:
Figure 28: Histogram for the EEG da
Page 100 and 101:
Figure 29: Attractors corresponding
Page 102 and 103:
able for automatic detection proces
Page 104 and 105:
ENTROPY Thermodynamics Signal analy
Page 106 and 107:
6.3 Application to visual event-rel
Page 108 and 109:
VEP Non Target Target F3 -20 -10 0
Page 110 and 111:
1 VEP NON-TARGET TARGET 1 1 F3 F3 0
Page 112 and 113:
1 VEP NON-TARGET TARGET 1 1 F3 F3 0
Page 114 and 115:
and the Lorenz equations (a model o
Page 116 and 117:
P300 deection. Due to the relation
Page 118 and 119:
7 General Discussion In this chapte
Page 120 and 121:
Wavelet analysis was also applied t
Page 122 and 123:
aect the whole spectrum and for thi
Page 124 and 125:
peaks. 7.2.3 Wavelet Transform vs.
Page 126 and 127:
the ones having wide peaks (being t
Page 128 and 129:
A Time-frequency resolution and the
Page 130 and 131:
Z 1 ;1 tx(t) d dt x(t) dt = 1 2 Z 1
Page 132 and 133:
Figure 37: Time-frequency resolutio
Page 134 and 135:
References Abarbanel HDI, Brown R,
Page 136 and 137:
Berger, H. Uber das Elektrenkephalo
Page 138 and 139:
Gastaut H and Broughton R. Epilepti
Page 140 and 141:
Lopes da Silva FH, van Lierop THMT,
Page 142 and 143:
Pradhan N, Sadasivan P, Chatterji S
Page 144 and 145:
Serrano E, Ph.D. Thesis, Department
Page 146:
Biographical sketch 21.03.1967 born
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