Title :
Fuzzy Expert Systems For Sequential Pattern Recognition For Patient Status Monitoring in Operating Room
Author :
Xue, Joel ; Krajnak, Michael
Author_Institution :
GE Healthcare Inf. Technol., Wauwautosa, WI
fDate :
Aug. 30 2006-Sept. 3 2006
Abstract :
In this paper, we present several fuzzy inference systems for monitoring patient status in an operating room. The algorithms used include recursive fuzzy inference (RFIS), and non-recursive with sequential patterns as inputs. The RFIS algorithm combines current patient status data with previous output of the inference system, therefore is able to reinforce the current finding based on previous sequential system output. The results show that the RFIS system can be tuned towards higher sensitivity for more critical status, while generating smoother inference output
Keywords :
fuzzy systems; inference mechanisms; medical computing; patient monitoring; pattern recognition; recursive functions; RFIS algorithm; fuzzy expert systems; operating room; patient status data; patient status monitoring; recursive fuzzy inference system; sequential pattern recognition; Anesthetic drugs; Engines; Feeds; Fuzzy logic; History; Hybrid intelligent systems; Inference algorithms; Patient monitoring; Pattern recognition; Radiofrequency interference;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.259266