Virtual-reality-based laparoscopic surgical training: the role of simulation fidelity in haptic feedback.
Identifieur interne : 000803 ( Ncbi/Merge ); précédent : 000802; suivant : 000804Virtual-reality-based laparoscopic surgical training: the role of simulation fidelity in haptic feedback.
Auteurs : Hyun K. Kim [États-Unis] ; David W. Rattner ; Mandayam A. SrinivasanSource :
- Computer aided surgery : official journal of the International Society for Computer Aided Surgery [ 1092-9088 ] ; 2004.
English descriptors
- KwdEn :
- MESH :
- education : Minimally Invasive Surgical Procedures.
- methods : Laparoscopy.
- Analysis of Variance, Computer Simulation, Feedback, Humans, Linear Models, User-Computer Interface.
Abstract
Although there have been significant advances in the development of virtual-reality-based surgical simulations, there remain fundamental questions concerning the fidelity required for effective surgical training. A dual-station experimental platform was built for the purpose of investigating these fidelity requirements. Analogous laparoscopic surgical tasks were implemented on a virtual station and a real station, with the virtual station modeling the real environment with various degrees of fidelity. After measuring the subjects' initial performance on the real station, different groups of subjects were trained on the virtual station under a variety of conditions and finally tested on the real station. Experiments involved bimanual pushing and cutting tasks on a nonlinear elastic object. The results showed that force feedback results in significantly improved training transfer as compared to training without force feedback. The training effectiveness of a linear approximation model was approximately the same as that of a more accurate nonlinear model.
DOI: 10.3109/10929080500066997
PubMed: 16192064
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pubmed:16192064Le document en format XML
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<front><div type="abstract" xml:lang="en">Although there have been significant advances in the development of virtual-reality-based surgical simulations, there remain fundamental questions concerning the fidelity required for effective surgical training. A dual-station experimental platform was built for the purpose of investigating these fidelity requirements. Analogous laparoscopic surgical tasks were implemented on a virtual station and a real station, with the virtual station modeling the real environment with various degrees of fidelity. After measuring the subjects' initial performance on the real station, different groups of subjects were trained on the virtual station under a variety of conditions and finally tested on the real station. Experiments involved bimanual pushing and cutting tasks on a nonlinear elastic object. The results showed that force feedback results in significantly improved training transfer as compared to training without force feedback. The training effectiveness of a linear approximation model was approximately the same as that of a more accurate nonlinear model.</div>
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<Abstract><AbstractText>Although there have been significant advances in the development of virtual-reality-based surgical simulations, there remain fundamental questions concerning the fidelity required for effective surgical training. A dual-station experimental platform was built for the purpose of investigating these fidelity requirements. Analogous laparoscopic surgical tasks were implemented on a virtual station and a real station, with the virtual station modeling the real environment with various degrees of fidelity. After measuring the subjects' initial performance on the real station, different groups of subjects were trained on the virtual station under a variety of conditions and finally tested on the real station. Experiments involved bimanual pushing and cutting tasks on a nonlinear elastic object. The results showed that force feedback results in significantly improved training transfer as compared to training without force feedback. The training effectiveness of a linear approximation model was approximately the same as that of a more accurate nonlinear model.</AbstractText>
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