DocumentCode :
3241109
Title :
Neurometric assessment of adequacy of intraoperative anesthetic
Author :
Kangas, Lars J. ; Keller, Paul E. ; Cadwell, Carlton M. ; Webber, Rick ; Pierce, Polly ; Edmonds, Harvey L.
Author_Institution :
Pacific Northwest Lab., Richland, WA, USA
Volume :
4
fYear :
1997
fDate :
9-12 Jun 1997
Firstpage :
2475
Abstract :
A method is described to assess depth and trend of anesthesia from EEG signals during general anesthesia by using supervised artificial neural networks. An artificial neural network is trained to recognize the spectral differences in the EEG signals between an awake and an anesthetized patient
Keywords :
electroencephalography; medical signal processing; neural nets; pattern recognition; spectral analysis; surgery; EEG signals; intraoperative anesthetic; neural networks; neurometric assessment; pattern recognition; spectral analysis; surgery; Anesthesia; Anesthetic drugs; Artificial neural networks; Biomedical monitoring; Blood pressure; Electroencephalography; Heart rate; Laboratories; Pulse measurements; Signal resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
Type :
conf
DOI :
10.1109/ICNN.1997.614550
Filename :
614550
Link To Document :
بازگشت