Generalized approach for modeling minimally invasive surgery as a stochastic process using a discrete Markov model. Rosen, J.; Brown, J. D; Chang, L.; Sinanan, M. N; and Hannaford, B. IEEE Trans Biomed Eng, 53(3):399--413, March, 2006.
Generalized approach for modeling minimally invasive surgery as a stochastic process using a discrete Markov model. [link]Paper  doi  abstract   bibtex   
Minimally invasive surgery (MIS) involves a multidimensional series of tasks requiring a synthesis between visual information and the kinematics and dynamics of the surgical tools. Analysis of these sources of information is a key step in defining objective criteria for characterizing surgical performance. The Blue DRAGON is a new system for acquiring the kinematics and the dynamics of two endoscopic tools synchronized with the endoscopic view of the surgical scene. Modeling the process of MIS using a finite state model [Markov model (MM)] reveals the internal structure of the surgical task and is utilized as one of the key steps in objectively assessing surgical performance. The experimental protocol includes tying an intracorporeal knot in a MIS setup performed on an animal model (pig) by 30 surgeons at different levels of training including expert surgeons. An objective learning curve was defined based on measuring quantitative statistical distance (similarity) between MM of experts and MM of residents at different levels of training. The objective learning curve was similar to that of the subjective performance analysis. The MM proved to be a powerful and compact mathematical model for decomposing a complex task such as laparoscopic suturing. Systems like surgical robots or virtual reality simulators in which the kinematics and the dynamics of the surgical tool are inherently measured may benefit from incorporation of the proposed methodology.
@article{rosen_generalized_2006,
	title = {Generalized approach for modeling minimally invasive surgery as a stochastic process using a discrete {Markov} model.},
	volume = {53},
	url = {http://dx.doi.org/10.1109/TBME.2005.869771},
	doi = {10.1109/TBME.2005.869771},
	abstract = {Minimally invasive surgery (MIS) involves a multidimensional series of tasks requiring a synthesis between visual information and the kinematics and dynamics of the surgical tools. Analysis of these sources of information is a key step in defining objective criteria for characterizing surgical performance. The Blue DRAGON is a new system for acquiring the kinematics and the dynamics of two endoscopic tools synchronized with the endoscopic view of the surgical scene. Modeling the process of MIS using a finite state model [Markov model (MM)] reveals the internal structure of the surgical task and is utilized as one of the key steps in objectively assessing surgical performance. The experimental protocol includes tying an intracorporeal knot in a MIS setup performed on an animal model (pig) by 30 surgeons at different levels of training including expert surgeons. An objective learning curve was defined based on measuring quantitative statistical distance (similarity) between MM of experts and MM of residents at different levels of training. The objective learning curve was similar to that of the subjective performance analysis. The MM proved to be a powerful and compact mathematical model for decomposing a complex task such as laparoscopic suturing. Systems like surgical robots or virtual reality simulators in which the kinematics and the dynamics of the surgical tool are inherently measured may benefit from incorporation of the proposed methodology.},
	language = {eng},
	number = {3},
	journal = {IEEE Trans Biomed Eng},
	author = {Rosen, Jacob and Brown, Jeffrey D and Chang, Lily and Sinanan, Mika N and Hannaford, Blake},
	month = mar,
	year = {2006},
	keywords = {Animal structures, Biological, Biological; Models, Blue DRAGON, Computer Simulation, Computer Simulation, Computer Simulation; Endoscopes; Endoscopy, Computer-Assisted, Dynamics, Endoscopes, Endoscopy, Expert Systems, Expert Systems, Humans, Humans, Information analysis, Information resources, Kinematics, Layout, Man-Machine Systems, Markov Chains, Markov Chains, Markov model, Markov processes, Minimally Invasive, Minimally Invasive, Minimally invasive surgery, Models, Models, Biological, Models, Statistical, Multidimensional systems, Performance analysis, Protocols, Robotics, Statistical, Statistical; Robotics, Stochastic Processes, Stochastic processes, Surgery, Surgery, Computer-Assisted, Surgical Procedures, Surgical Procedures, Minimally Invasive, Task Performance and Analysis, Task Performance and Analysis, User-Computer Interface, User-Computer Interface, discrete Markov model, endoscopes, endoscopic tools, endoscopy, finite state model, haptics, human machine interface, instrumentation/methods, instrumentation/methods; Stochastic Processes; Surgery, instrumentation/methods; Surgical Procedures, instrumentation/methods; Task Performance and Analysis; User-Computer Interface, laparoscopic suturing, man-machine systems, manipulation, medical robotics, methods, methods; Expert Systems; Humans; Man-Machine Systems; Markov Chains; Models, objective learning curve, robot kinematics, robotics, simulation, soft tissue, stochastic process, subjective performance analysis, surgery, surgical robots, surgical skill assessment, surgical tool, surgical tool dynamics, surgical tool kinematics, vector quantization, virtual reality, virtual reality simulators, visual information},
	pages = {399--413}
}
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