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Heuristic haptic texture for surgical simulations.

Identifieur interne : 001A77 ( PubMed/Corpus ); précédent : 001A76; suivant : 001A78

Heuristic haptic texture for surgical simulations.

Auteurs : Eric Acosta ; Bharti Temkin ; John A. Griswold ; Sammy A. Deeb ; Tom Krummel ; Randy S. Haluck ; Louis R. Kavoussi

Source :

RBID : pubmed:15458053

English descriptors

Abstract

Generation of credible force feedback renderings adds the sense of touch crucial for the development of a realistic virtual surgical environment. However, a number of difficulties must be overcome before this can be achieved. One of the problems is the paucity of data on the in-vivo tissue compliance properties needed to generate acceptable output forces. Without this "haptic texture," the sense of touch component remains relatively primitive and unrealistic. Current research in the quantitative analysis of biomechanics of living tissue, including collection of in-vivo tissue compliance data using specialized sensors, has made tremendous progress. However, integration of all facets of biomechanical data in order to transfer them into haptic texture remains a very difficult problem. For this reason, we are attempting to create a library of heuristic haptic textures of anatomical structures. The library of heuristic haptic textures will capture the expert's sense of feel for selected anatomical structures and will be used to convey the sense of touch for surgical training simulations. Once the techniques for converting biomechanical data into haptic texture become more robust, this library can be used as a benchmark to verify theoretical computational models used for generating output forces in haptic devices.

PubMed: 15458053

Links to Exploration step

pubmed:15458053

Le document en format XML

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