Title :
Depth of anesthesia estimation by adaptive-network-based fuzzy inference system
Author :
Zhang, Xu-Sheng ; Roy, Rob J.
Author_Institution :
Dept. of Biomed. Eng., Rensselaer Polytech. Inst., Troy, NY, USA
Abstract :
One effective way to estimate the depth of anesthesia (DOA) from EEG is proposed. The scheme applies an adaptive-network-based fuzzy inference system (ANFIS) to integrate the extracted EEG characteristics such as complexity measure, approximate entropy, and spectral edge frequency for decision-making. The system was trained and tested using EEG data collected from three dog experiments under propofol anesthesia. The accuracy of the system attains 89.5%. Comparison with artificial neural networks was made
Keywords :
adaptive signal processing; electroencephalography; entropy; medical signal processing; patient monitoring; surgery; adaptive-network-based fuzzy inference system; approximate entropy; artificial neural networks; dog experiments; propofol anesthesia; spectral edge frequency; system accuracy; Anesthesia; Artificial neural networks; Data mining; Decision making; Direction of arrival estimation; Electroencephalography; Entropy; Frequency measurement; Fuzzy systems; System testing;
Conference_Titel :
[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-5674-8
DOI :
10.1109/IEMBS.1999.802468
