title: [Automatic artefact detection in intraoperative EEG monitoring].
abstract: The quality of intraoperative EEG monitoring is decisively influenced by automatic detection of artefacts. Undetected artefacts can mimic non-existing trends thus leading to misinterpretations of the EEG. Methods of computer-assisted artefact detection are developed and described: On the one hand the algorithms include simple threshold values of atypical parameters, on the other, they rely on situation-dependent smoothing of the EEG signal. Too strong a deviation of an artefact-relevant parameter from its smoothed value results in exclusion of the EEG segment (epoch) from further computation trends. The algorithms can clearly reduce the misclassification of highly artefact-contaminated epochs in the awake patient, without allowing anaesthesia-relevant changes to escape notice.
authors.affiliation: Abt. Abdominal- und Transplantationschirurgie, Medizinische Hochschule Hannover. eckert@tx-amb.mh-hannover.de
authors.forename: O
authors.initials: O
authors.lastname: Eckert
mesh_terms: D000465:Algorithms; D016477:Artifacts; D004569:Electroencephalography / Q000295:instrumentation*; D006801:Humans; D016343:Monitoring, Intraoperative / Q000295:instrumentation*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*