Juniper Publishers - Monitoring the Depth of Anesthesia and Current Technology - - Journal of Anesthesia & Intensive Care Medicine (JAICM)
Juniper Publishers - Open Access Journal of Journal of Anesthesia & Intensive Care Medicine
Monitoring the Depth of Anesthesia and Current Technology
Authored by Daniel Alfonso Botero-Rosas
General anesthesia (GA) is defined as a drug-induced 
loss of consciousness during which patients are not arousable, even by 
painful stimulation [1].
 GA takes an important role in surgical procedures where an anesthetic 
overdose may lead to drug-associated toxicities, coma and even death; on
 the other hand a light anesthetic dose may lead to the well-known event
 of intraoperative awareness, which can cause sleep disorders, 
depression, night terrors, hospitals fears and post-traumatic stress 
disorder [2-4]. In this context, monitoring depth of anesthesia has become an important issue in anesthesiology.
Electroencephalographic signal (EEG) reflects the 
activity of the central nervous system and it has been widely used for 
monitoring depth of anesthesia. In general terms, the EEG of an 
anesthetized patient changes from high frequency, low amplitude when 
awake to low frequency, high amplitude when anesthetized; it is also 
noted that, during the anesthesia procedure the degree of EEG disorder 
is reduced. Therefore, the concept of entropy was introduced in EEG 
signal processing. Entropy is related to the complexity of a signal, and
 has been considered a promising measure of states of consciousness [5]. State Entropy (SE) and Response Entropy (RE) are indices provided by Datex-Ohmeda S/5TM entropy module (General Electric, Finland), which is currently a reference in EEG monitoring during general anesthesia [6,7].
 SE and RE are based on spectral entropy computation over the Fourier 
spectrum; a description of the algorithm applied is available elsewhere [8].
 The M-Entropy module is considered a reference in monitoring the depth 
of anesthesia based on EEG analysis, particularly the Response Entropy 
(RE) index, was considered a better predictor of patient response to 
painful stimuli than the Bispectral index (BIS) [9] .
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