Title :
The use of parametric models in the detection of awareness during general anaesthesia [EEG processing]
Author :
Holt, M. ; Tarassenko, L.
Author_Institution :
Dept. of Eng. Sci., Oxford Univ., UK
Abstract :
The aim is to construct a method, based upon statistical pattern recognition techniques, including neural networks, whereby awareness during general anaesthesia may be detected. The data source for this system would be a single channel of the electroencephalogram (EEG). Pre-processing of data prior to input into the network is a critical component of the work, and it is here that parametric models have been utilised. A spectral representation has been extracted from the EEG based upon 1 second of data, using a lattice filter as the primary model; and a bispectral representation based upon 5 seconds of data has also been constructed, this time using a transversal filter as the underlying model
Keywords :
pattern recognition; 1 s; 5 s; EEG processing; awareness detection; bispectral representation; general anaesthesia; lattice filter; parametric models; primary model; spectral representation; statistical pattern recognition; transversal filter;
Conference_Titel :
Model Based Digital Signal Processing Techniques in the Analysis of Biomedical Signals (Digest No. 1997/009), IEE Colloquium on the Use of
Conference_Location :
London
DOI :
10.1049/ic:19970063
