Title of article :
Pre-operative ordering of minimally invasive surgical tools: A fuzzy inference system approach
Author/Authors :
Miller، نويسنده , , David J. and Nelson، نويسنده , , Carl A. and Oleynikov، نويسنده , , Dmitry and Jones، نويسنده , , David D.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2008
Pages :
11
From page :
35
To page :
45
Abstract :
SummaryObjective limited number of access ports, minimally invasive surgery (MIS) often requires the complete removal of one tool and reinsertion of another in order to provide surgeons with the full functionality necessary to complete a procedure. als and Methods ope video from 14 MIS procedures performed at the University of Nebraska Medical Center was used to collect usage statistics for various surgical instruments. This usage data was normalized and input to a fuzzy inference system (FIS) with four membership functions (MFs) to provide a crisp rating value for each instrument. Input membership functions included: number of uses (“Use”), total time used (“Time”), number of changes (“Change”) and time per use (“Ave-Time”). Tools were arranged in a simulated cartridge system based on a “Usefulness” output membership function in such a way as to allow easy selection of the next instrument necessary to complete the procedure. Performance was measured by comparing the amount of cartridge indexing needed to complete a procedure using the FIS-generated arrangement against a set of random tool arrangements. s FIS-generated tool arrangements considered in this investigation performed better than 64.11% of randomly generated tool arrangements and as well or better than 80.48% of tool arrangements. Using the FIS in conjunction with a multifunction laparoscopic tool, it is projected that an average cycle savings of 17.75% and 17.39% can be achieved over the mean and median of the random tool arrangements, respectively. sions given set of tools, the FIS used in this investigation provides an efficient method of arranging tools for MIS that performs at least as well or better than simply placing the tool tips into the chambers in a random configuration. This leads to a decrease in operating room time and corresponding decreases in both patient trauma from insertion and removal of tools and monetary cost, which is directly related to the amount of time spent changing instruments.
Keywords :
minimally invasive surgery , Fuzzy Logic , Fuzzy Inference System , Laparoscopic surgery , Surgical robotics
Journal title :
Artificial Intelligence In Medicine
Serial Year :
2008
Journal title :
Artificial Intelligence In Medicine
Record number :
1836687
Link To Document :
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