British Journal of Anaesthesia, 2002, Vol. 88, No. 5 644-648
© 2002 The Board of Management and Trustees of the British Journal of Anaesthesia
Clinical Investigations |
EEG signal processing in anaesthesia. Use of a neural network technique for monitoring depth of anaesthesia
1Dipartimento Area Critica Medico Chirurgica, Sez. di Anestesiologia e Rianimazione, Università di Firenze, Italy. 2Dipartimento Di Patologia e Biologia Molecolare e Cellulare, Universita’ Federico II, Napoli, Italy. 3Dipartimento di Sistemi e Informatica, Universita’ di Firenze, Italy. 4Dipartimento di Ingegneria dell’Informazione, Universita’ di Siena, Italy. 5Department of Engineering Science, University of Oxford, Oxford, UK*Corresponding author: Via Carducci 42, I-80121 Naples, Italy
Background. The Bispectral Index (BIS) is a proprietary index of anaesthesia depth, which is correlated with the level of consciousness and probability of intraoperative recall. The present study investigates the use of a neural network technique to obtain a non-proprietary index of the depth of anaesthesia from the processed EEG data.
Methods. Two hundred patients, who underwent general abdominal surgery, were recruited for our trial. For anaesthesia we used a total i.v. technique, tracheal intubation, and artificial ventilation. Fourteen EEG variables, including the BIS, were extracted from the EEG, monitored with an EEG computerized monitor, and then stored on a computer. Data from 150 patients were used to train the neural network. All the variables, excluding the BIS, were used as input data in the neural network. The output targets of the network were provided by anaesthesia scores ranging from 10 to 100 assigned by the anaesthesiologist according to the observer’s assessment of alertness and sedation (OAA/S) and other clinical means of assessing depth of anaesthesia. Data from the other 50 patients were used to test the model and for statistical analysis.
Results. The artificial neural network was successfully trained to predict an anaesthesia depth index, the NED (neural network evaluated depth), ranging from 0 to 100. The correlation coefficient between the NED and the BIS over the test set was 0.94 (P<0.0001).
Conclusion. We have developed a neural network model, which evaluates 13 processed EEG parameters to produce an index of anaesthesia depth, which correlates very well with the BIS during total i.v. anaesthesia with propofol.
Br J Anaesth 2002; 88: 644–8
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  D. K. Tempe and L. Satyanarayana Editorial I: Is there any alternative to the Bispectral Index Monitor? Br. J. Anaesth., January 1, 2004; 92(1): 1 - 3. [Full Text] [PDF]
|
|