*Electroencephalography - From Basic Research to Clinical Applications*

#### **Figure 6.**

*Box plots showing a comparison of EEG structure for different bands: (a) raw recording during a complete event during sleep. The images under the recordings correspond to the periods indicated by arrows. (b) Lobar dynamics of EEG bands during the entire event (vertical red lines). Blue = left hemisphere; red = right hemisphere.*

robust with respect to physiological assumptions [2]. Then, some procedures require relatively simple and involve straightforward methods as FFT [26, 34, 64–66] and synchronicity measurements [67, 68], approaches that clinicians are familiar with. In contrast, other numerical methods are more complex, or the mathematical approach deviates from physiological assumptions [69–74], and this probably takes neurophysiologists out of their comfort zone.

We have developed a robust method that is physiologically founded and easy to use in daily clinical practice. The tools selected are neither unique nor are they necessarily the best. Other tools (e.g., coherence) can be implemented. A careful comparison between these methods will decide the fitted procedure for each

**Figure 7.**

*Psychogenic non epileptic seizure (a) raw recordings (in transverse and double banana differential montages) during the event. (b) Lobar dynamics of EEG bands during the entire event (vertical red lines). Blue = left hemisphere; red = right hemisphere.*

pathology. From the beginning of 2016, we have performed more than 4100 analyses and used this toolbox in most patients, even those with EEG apparently evident. We did not use qEEG only when the record included so many artifacts (e.g., in agitated patients) that the results would not be reliable.

The method described can be implemented to automatically differentiate between paroxysmal events and ES during the long-term monitoring of ICU patients. This feature is very relevant for clinicians because it can shorten the review time, particularly during long cEEG, and can help apply adequate therapeutic measures, avoiding pharmacological blind trials that only delay correct treatment, increasing the inefficacy of treatment and diminishing the probability of recuperation. Therefore, considering that "time is brain", a fast and accurate treatment is mandatory to increase the probability of a good outcome.

Finally, it is extremely important to keep in mind that qEEG is only a tool to help better understand and diagnose brain pathophysiology; therefore, it should not be thought that numerical analysis (at least as we use it today) is enough, without evaluation by an expert, to make an automatic diagnosis. Not all brain pathologies

are likely to benefit to the same degree from analysis. For example, the method described in this chapter is not well fitted to detect low-frequency transitory waves as medium/small focal epileptiform discharges, although visual inspection can identify them very well. However, patterns that are not readily visible in *de visu* analysis (e.g., asymmetries in power spectra compositions) are easily detected.
