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

criterion (see sec. x5.2.4). D 2 varied between 4:5 ; 6 without a clear dierence between
normal and pathological EEG recordings. Maximum Lyapunov exponents were positive
in all the cases giving an evidence of chaotic activity (in the case of signals having a
deterministic origin).
5.6 Application to intracranially recorded tonic-clonic seizures
5.6.1 Material and Methods
The subject and data analyzed was described in sec. x3.3. The EEG corresponds to a
9-hour intracranial recording from a 21 years old patient with tonic-clonic seizures.
5.6.2 Results and Discussion
Figure 7 shows the EEG signal corresponding to a segment of 64 sec from one depth
electrode in the left hippocampus. As seen in the gure, the epileptic seizure starts
about second 10 and nishes about second 54.
In order to study changes in the EEG behavior the signal was divided in intervals of
8 sec as follows: ( i ) pre-seizure (0 ; 8sec) ( ii ) starting of the seizure (10 ; 18sec) (
iii ) full development of the seizure (21 ; 29sec) and (29 ; 37sec) ( iv ) ending of the
seizure (37 ; 44sec) and (44 ; 52sec).
For these intervals, stationaritywas tested following the criterion described in sec. x5.3.
The length of the bins used was of 512 data. In the second interval (10 ; 18sec) the
criterion of stationarity was not satised due to the fast changes in the EEG morphology.
The time delay and the minimum embedding dimension were estimated with the
geometrical method introduced by Rosestein and the False Nearest Neighbor method,
respectively (see sect. x5.2.4).
Fig. 29 displays the two dimensional projection of the phase portraits for the selected
intervals. Each EEG segment was characterized by its Correlation Dimensions and
maximum Lyapunov exponents.
Table 5 shows the stationary zones, optimal time lags , minimum embedding dimensions,
Correlation Dimension and maximum Lyapunov exponent for the dierent
EEG intervals. These last two parameters were obtained as an average among the corresponding
values obtained for all the considered embedding dimensions. These values
are in good agreement with those given in the literature in background activity and in
epileptic seizures (see sec. x5.4).
The seizure is characterized by a drop in the value of the maximum Lyapunov exponent.
A similar situation is observed for the Correlation Dimension. From the values
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