Designing a fuzzy rule based system to estimate depth of anesthesia

Esmaeili, V ; Sharif University of Technology | 2007

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  1. Type of Document: Article
  2. DOI: 10.1109/CIDM.2007.368942
  3. Publisher: 2007
  4. Abstract:
  5. Estimating the depth of anesthesia (DOA) is still a challenging area in anesthesia research. The objective of this study was to design a fuzzy rule based system which integrates electroencephalogram (EEG) features to quantitatively estimate the DOA. The proposed method is based on the analysis of single-channel EEG using frequency and time domain features as well as Shannon entropy measure. The fuzzy classifier is trained with features obtained from four subsets of data comprising well-defined anesthesia states: awake, moderate, general anesthesia, and isoelectric. The classifier extracts efficient fuzzy if-then rules and the DOA index is derived between 100 (full awake) to 0 (isoelectric) using fuzzy inference engine. To validate the proposed method, a clinical study has conducted on 22 patients to construct 4 subsets of reference states and also to compare the results with CSM monitor (Danmeter, Denmark), which has revealed satisfactory correlation with clinical assessments. © 2007 IEEE
  6. Keywords:
  7. Electroencephalography ; Entropy ; Frequency domain analysis ; Fuzzy rules ; Time domain analysis ; Clinical assessments ; CSM monitor ; Depth of anesthesia (DOA) ; General anesthesia ; Biomedical engineering
  8. Source: 1st IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007, Honolulu, HI, 1 April 2007 through 5 April 2007 ; 2007 , Pages 681-687 ; 1424407052 (ISBN); 9781424407057 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4221366