Brief report: Building choice opportunities within a robot-assisted occupational program: A case study

1993 ◽  
Vol 8 (3) ◽  
pp. 219-226 ◽  
Author(s):  
Giulio E. Lancioni ◽  
Domenico Bellini ◽  
Doretta Oliva
Author(s):  
G Van Ham ◽  
K Denis ◽  
J Vander Sloten ◽  
R Van Audekercke ◽  
G Van der Perre ◽  
...  

Bone cutting in total joint reconstructions requires a high accuracy to obtain a well-functioning and long-lasting prosthesis. Hence robot assistance can be useful to increase the precision of the surgical actions. A drawback of current robot systems is that they autonomously machine the bone, in that way ignoring the surgeon's experience and introducing a safety risk. This paper presents a semi-active milling procedure to overcome that drawback. In this procedure the surgeon controls robot motion by exerting forces on a force-controlled lever that is attached to the robot end effector. Meanwhile the robot constrains tool motion to the planned motion and generates a tool feed determined by the feed force that the surgeon executes. As a case study the presented milling procedure has been implemented on a laboratory set-up for robot-assisted preparation of the acetabulum in total hip arthroplasty. Two machining methods have been considered. In the first method the surgeon determines both milling trajectory and feed by the forces that he/she executes on the force-controlled lever. In the second method the cavity is machined contour by contour, and the surgeon only provides the feed. Machining experiments have shown that the first method results in large surface irregularities and is not useful. The second method, however, results in accurate cavity preparation and has therefore potential to be implemented in future robot systems.


2016 ◽  
Vol 59 (2) ◽  
pp. 119-128
Author(s):  
Carlos Faria ◽  
Carolina Vale ◽  
Toni Machado ◽  
Wolfram Erlhagen ◽  
Manuel Rito ◽  
...  

Author(s):  
Conor Teljeur ◽  
Paul Carty ◽  
Máirín Ryan

IntroductionEconomic models contain several parameters ordinarily subject to uncertainty. Unlike most other model parameters, costs can constitute numerous distinct components. For example, a surgical intervention can require a variety of disposables and reusable equipment. A micro-costing output may be disaggregated or presented as a total cost. Uncertainty could be applied to individual cost components or to total cost. We aimed to explore how disaggregation of cost data may impact on uncertainty using a case study.MethodsA set of simulations using hypothetical scenarios were developed with uncertainty set at ± 20 percent. The simulations investigated the impact of number of cost components, balance between components, and correlation between them. A cost-utility model from an assessment of robot-assisted radical prostatectomy was analyzed; procedure cost was divided into 32 individual cost components or treated as a total cost.ResultsBased on five equal cost components, uncertainty reduces from ± 20 percent for correlated variables to ± 9 percent for uncorrelated variables. With increasing numbers of uncorrelated cost components, the uncertainty in the total cost decreases markedly. The uncertainty around total robot-assisted surgery procedure equipment costs was ± 19.7 percent when components were correlated and ± 9.4 percent when uncorrelated. The impact on uncertainty in the incremental cost effectiveness ratio (ICER) was negligible but the ranking of parameters in the univariate sensitivity analysis changed.ConclusionsAnalyzing uncertainty by aggregated or disaggregated costs can have implications for presenting uncertainty in costs to decision makers. Applying uncertainty to aggregated costs essentially implies that variation in the cost of individual components is perfectly correlated. By disaggregating cost components they are being treated as uncorrelated, which can substantially reduce uncertainty in the total cost. In this case study we found that although the reduction in uncertainty could be clearly seen in the cost parameter, it had a negligible impact on uncertainty in the ICER.


Author(s):  
David Meary ◽  
Gabriel Baud-Bovy ◽  
Raffaella Chieffo ◽  
Letizia Leocani ◽  
Mauro Comola ◽  
...  

2019 ◽  
Author(s):  
Aleksandra Mikov ◽  
Dragana Vukliš ◽  
Branislav Borovac ◽  
Milan Gnjatović ◽  
Jovica Tasevski ◽  
...  

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