- 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 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
- 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 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