Concept for an intelligent anaesthesia EEG monitor.
Considering the fundamental difficulties to define the term 'depth of anaesthesia', a more feasible concept for assessment of 'adequacy of anaesthesia' will be explained. The basic requirements for a monitoring index are definite response, gradual scaling and independence from the anaesthetic technique used. Additionally the index should be predictive for appearance of clinical signs of an inadequate anaesthesia. Different signal-processing methods will be discussed to extract the relevant information from both the spontaneous and the evoked brain electrical activity. In this context well established methods like spectral analysis are investigated in combination with new and more sophisticated methods like bispectral analysis or wavelet decomposition. Since no single-parameter index has been defined for monitoring depth of anaesthesia, a set of EEG parameters may be more useful to take into account intra- and interindividual variability. In parallel to the description of the monitor concept, the investigation of neural nets and fuzzy techniques, in addition to or in substitution of conventional statistical methods, will be introduced. Examples are given for data quality assessment, parameter extraction and re-classification.
Nahm
W
W
Institute of Biomedical Technology, Medical University of Lübeck, Institute für Medizintechnik, Germany.
Stockmanns
G
G
Petersen
J
J
Gehring
H
H
Konecny
E
E
Kochs
H D
HD
Kochs
E
E
D000465:Algorithms; D000758:Anesthesia; D001185:Artificial Intelligence; D016002:Discriminant Analysis; D004569:Electroencephalography; D005072:Evoked Potentials, Auditory / Q000502:physiology; D006801:Humans; D016015:Logistic Models; D008991:Monitoring, Physiologic / Q000295:instrumentation / Q000379:methods*; D012815:Signal Processing, Computer-Assisted