Contributions to an Advisory System for Changes Detection in Depth of Anesthesia Signals

Learning from Medical Data Streams 2011.

医药卫生;计算机科学

Raquel Sebastia˜o ; Margarida M. Silva ; Joa˜o Gama ; Teresa Mendonc¸a ; 2 Div. Systems and Control ; Dep. Information Technology ; Uppsala University ; Box 337 ; SE-751 05 Uppsala ; Sweden ; and FCUP ; and Center for Research and Development in Mathematics and Applications (CIDMA) ; Dep. Matema´tica ; Campus ; 3 LIAAD-INESC Porto ; L.A. ; and Faculdade de Economia da Universidade do Porto ; Rua Dr. Roberto Frias ; 4200-464 Porto ; Portugal. ; 4 FCUP ; ; CIDMA.

Others  :  http://ceur-ws.org/Vol-765/paper6.pdf
PID  :  41156

来源: CEUR

【 摘 要 】

In the clinical practice the concerns about the administra-tion of hypnotics and analgesics for minimally invasive diagnostics and therapeutic procedures have enormously increased in recent years. The automatic detection of changes in the signals used to evaluate the depth of anesthesia is hence of foremost importance in order to decide how to adapt administered doses to patients undergoing surgical procedures. The aim of this work is to online detect changes in depth of anesthesia signals of patients undergoing general anesthesia. The performance of the proposed method is evaluated using bispectral index records. The results show that the changes detected by the proposed method are in accordance with the actions of the clinicians. This fact and the good results that were obtained support the online validation of the proposed advisory system for changes detection in depth of anesthesia signal in a real clinical environment.