BJA Advance Access originally published online on September 17, 2004
British Journal of Anaesthesia 2004 93(6):806-809; doi:10.1093/bja/aeh270
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© The Board of Management and Trustees of the British Journal of Anaesthesia 2004
Awareness and the EEG power spectrum: analysis of frequencies
Department of Anaesthesiology, Technische Universität München, Klinikum rechts der Isar, Ismaningerstr. 22, 81675 Munich, Germany
* Corresponding author. E-mail: Gerhard.Schneider{at}lrz.tum.de
Background. Power spectral analysis is a well-established method for the analysis of EEG signals. Spectral parameters can be used to quantify pharmacological effects of anaesthetics on the brain and the level of sedation. This method, in numerous variations, has been applied to depth of anaesthesia monitoring and has been incorporated into several commercially available EEG monitors. Because of the importance of EEG spectral analysis, we evaluated the performance of each frequency in the power spectrum regarding detection of awareness.
Methods. Ninety artefact-free EEG segments of length 8 s were obtained from a database that contains perioperatively recorded EEG data. For the present analysis, EEG data were selected from 39 patients with propofolremifentanil or sevofluraneremifentanil anaesthesia with a period of awareness. Half of the EEG segments were recorded during periods of awareness as defined by an adequate response to the command squeeze my hand. The other half were from unresponsive patients. The power spectral density was calculated for each segment. The performance of each frequency bin of the power spectrum as a detector of awareness was assessed with a remapped prediction probability rPK, i.e. the prediction probability PK mapped to a range of 0.51.
Results. The remapped prediction probability was high (rPK>0.8) for low frequencies (<15 Hz) and for high frequencies (>26 Hz), with a minimum (rPK<0.55) at 21 Hz. Indentations in the performance spectrum occur at the power-line frequency (50 Hz) and its harmonics and at 78 Hz, probably caused by the continuous impedance measurement of another device used in parallel. With the exception of the indentations, the remapped prediction probability of the high frequencies (>35 Hz) was >0.95.
Conclusions. The best performance for the detection of awareness was achieved by EEG power spectral frequencies from >35 Hz up to 127 Hz. This frequency band may be dominated by muscle activity. The frequency band between 15 and 26 Hz may be of limited value, as reflected by lower rPK values.
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