6.1 Signals of the Brain

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Fig. 6.4: Electrode arrangement on the skull for EEG measurement in the 10-20 system in side view

(left) and top view (right).

With a continuous EEG measurement throughout the night, different sleep stages and,

if necessary, sleep disorders can be identified. During falling asleep, the EEG rhythm

changes from alpha to theta waves and with increasing sleep depth to delta waves. In

particular, sufficiently long deep sleep phases are important for the regeneration of

the body. Abrupt disturbances of the deep sleep phases for example by noise or acute

oxygen deficiency due to sleep apnea lead to jumps from delta waves to alpha or theta

waves in the EEG signal. In REM sleep⁴, also called dream sleep, which accounts for

about 20 % of the sleep time in adult humans, the brain is very active, which is ex-

pressed by a higher frequency position of the EEG signal. For sleep analysis, plotting

the dominant EEG frequency as a function of time is particularly useful. The dom-

inant EEG frequency can be determined from a maximum value analysis of the EEG

spectrum.

In section 3.3 the Berger experiment was already mentioned, here now an EEG sig-

nal is to be evaluated with the help of Matlab with respect to alpha waves. The simplest

way to analyze a time signal for its changes in frequency content, is the time-frequency

analysis as already presented in subsection 5.3.3. The time-frequency analysis works

with a time window which is slid over the signal and in which the frequency spectrum

is calculated. The length of this window defines on the one hand the time resolution

4 REM: rapid eye movement; a special characteristic of this sleep phase is the rapid eye movement.

Brain activity is particularly high and is perceived as a dream. The musculature, on the other hand, is

largely relaxed.