**3.1. Continuous EEG monitoring**

(**Figure 2**). Long bursts start with high-frequency high-amplitude waves, followed by lowfrequency high-amplitude waves, while short bursts present low-frequency high-amplitude

**Figure 2.** Burst aspects according to its length (local-field potential—LFP—recording). The first burst lasts almost 4 seconds and presents high-frequency waves at the beginning followed by slow waves. The second burst is short

Even though a BS presenting coma state is considered deep, BS is deemed a state of hyperexcitability, as bursts can be evoked by subliminal stimuli [14] and BS electrical activity is

The mechanism supporting this phenomenon remains incompletely explained. We have two theories attempting an explanation at the moment. The metabolic theory of Emery Brown [11]

**Figure 3.** Power spectral density during the long burst versus the short burst. Two peaks of frequencies can be observed

waves as it is seen on power spectral density graphics (**Figure 3**).

correlated with cerebral blood flow changes as well [15].

(almost 1 second) and presents slow waves.

84 Current Topics in Intensive Care Medicine

in the long burst.

Continuous EEG monitoring is the most used and, perhaps, the most efficient method of evaluating coma patients in the ICU. The advantage is the electrode placing: it is noninvasive (or minimally invasive), can be easily applied on the scalp of the patient and requires a minimal qualification of the ICU staff. Most EEG recording devices include software for mathematically processing the signal, and generating scores or frequencies.

The acquisition system 10–20, that is classically used, provides an overview of the main cortical areas. Placing the electrodes and fastening them with a specialized helmet may facilitate CT or MRI transportation, in order to obtain a complex imagistic and electroencephalographic representation. Standard EEG monitoring provides information on the onset of epileptic seizures, is useful in detecting nonconvulsive status and in detecting early and late ischemia, secondary to subarachnoid hemorrhage. Furthermore, it provides useful information (based on prevailing EEG patterns and reactivity) for the prognostic of the coma patient [19].

The following chapter will describe the main mathematical algorithms that are used in analyzing EEG signal, as well as the devices used for monitoring coma and anesthesia depth.
