%0 Conference Proceedings
%T Autoregressive Model Order Estimation Criteria for Monitoring Awareness during Anaesthesia
%+ University of Cyprus [Nicosia] (UCY)
%A Nicolaou, Nicoletta
%A Georgiou, Julius
%Z Part 3: Medical Informatics and Biomedical Engineering
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 9th Artificial Intelligence Applications and Innovations (AIAI)
%C Paphos, Greece
%Y Harris Papadopoulos
%Y Andreas S. Andreou
%Y Lazaros Iliadis
%Y Ilias Maglogiannis
%I Springer
%3 Artificial Intelligence Applications and Innovations
%V AICT-412
%P 71-80
%8 2013-09-30
%D 2013
%R 10.1007/978-3-642-41142-7_8
%K anaesthesia
%K AR model order estimation
%K awareness
%K EEG
%Z Computer Science [cs]Conference papers
%X This paper investigates the use of autoregressive (AR) model order estimation criteria for monitoring awareness during anaesthesia. The Bayesian Information Criterion (BIC) and the Akaike Information Criterion (AIC) were applied to electroencephalogram (EEG) data from 29 patients, obtained during surgery, to estimate the optimum multivariate AR model order. Maintenance of anaesthesia was achieved with propofol, desflurane or sevoflurane. The optimum orders estimated from the BIC reliably decreased during anaesthetic-induced unconsciousness, as opposed to AIC estimates, and, thus, successfully tracked the loss of awareness. This likely reflects the decrease in the complexity of the brain activity during anaesthesia. In addition, AR order estimates sharply increased for diathermy-contaminated EEG segments. Thus, the BIC could provide a simple and reliable means of identifying awareness during surgery, as well as automatic exclusion of diathermy-contaminated EEG segments.
%G English
%Z TC 12
%Z WG 12.5
%2 https://inria.hal.science/hal-01459666/document
%2 https://inria.hal.science/hal-01459666/file/978-3-642-41142-7_8_Chapter.pdf
%L hal-01459666
%U https://inria.hal.science/hal-01459666
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC12
%~ IFIP-AIAI
%~ IFIP-WG12-5
%~ IFIP-AICT-412