The Role of Simulation Fidelity in Laparoscopic Surgical Training
Identifieur interne : 002996 ( Istex/Corpus ); précédent : 002995; suivant : 002997The Role of Simulation Fidelity in Laparoscopic Surgical Training
Auteurs : K. Kim ; W. Rattner ; A. SrinivasanSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2003.
Abstract
Abstract: Although there have been significant advances in the development of virtual reality based surgical simulations, there still 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 in a virtual and a real station, with the virtual station modeling the real environment to various degrees of fidelity. After measuring subjects’ initial performance in the real station, different groups of subjects were trained on the virtual station under a variety of conditions and tested finally at the real station. Experiments involved bimanual pushing and cutting tasks on a nonlinear elastic object. The results showed that force feedback results in a significantly improved training transfer compared to training without force feedback. The training effectiveness of a linear approximation model was comparable to the effectiveness of a more accurate nonlinear model.
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DOI: 10.1007/978-3-540-39899-8_1
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ISTEX:2775841B871F20FAEF6CB9D735297F1E9CF396D9Le document en format XML
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Rattner</name><affiliation><mods:affiliation>Division of General and Gastrointestinal Surgery Massachusetts General Hospital, The Touch Lab, 02114, Boston, MA, USA</mods:affiliation></affiliation></author><author><name sortKey="Srinivasan, A" sort="Srinivasan, A" uniqKey="Srinivasan A" first="A." last="Srinivasan">A. 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Kim</name><affiliation><mods:affiliation>Department of Mechanical Engineering and The Research Laboratory of Electronics Massachusetts Institute of Technology, The Touch Lab, 02139, Cambridge, MA, USA</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: hyunkim@mit.edu</mods:affiliation></affiliation></author><author><name sortKey="Rattner, W" sort="Rattner, W" uniqKey="Rattner W" first="W." last="Rattner">W. Rattner</name><affiliation><mods:affiliation>Division of General and Gastrointestinal Surgery Massachusetts General Hospital, The Touch Lab, 02114, Boston, MA, USA</mods:affiliation></affiliation></author><author><name sortKey="Srinivasan, A" sort="Srinivasan, A" uniqKey="Srinivasan A" first="A." last="Srinivasan">A. Srinivasan</name><affiliation><mods:affiliation>Department of Mechanical Engineering and The Research Laboratory of Electronics Massachusetts Institute of Technology, The Touch Lab, 02139, Cambridge, MA, USA</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2003</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">2775841B871F20FAEF6CB9D735297F1E9CF396D9</idno><idno type="DOI">10.1007/978-3-540-39899-8_1</idno><idno type="ChapterID">1</idno><idno type="ChapterID">Chap1</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: Although there have been significant advances in the development of virtual reality based surgical simulations, there still 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 in a virtual and a real station, with the virtual station modeling the real environment to various degrees of fidelity. After measuring subjects’ initial performance in the real station, different groups of subjects were trained on the virtual station under a variety of conditions and tested finally at the real station. Experiments involved bimanual pushing and cutting tasks on a nonlinear elastic object. The results showed that force feedback results in a significantly improved training transfer compared to training without force feedback. The training effectiveness of a linear approximation model was comparable to the effectiveness of a more accurate nonlinear model.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>Hyun K. Kim</name><affiliations><json:string>Department of Mechanical Engineering and The Research Laboratory of Electronics Massachusetts Institute of Technology, The Touch Lab, 02139, Cambridge, MA, USA</json:string><json:string>E-mail: hyunkim@mit.edu</json:string></affiliations></json:item><json:item><name>David W. Rattner</name><affiliations><json:string>Division of General and Gastrointestinal Surgery Massachusetts General Hospital, The Touch Lab, 02114, Boston, MA, USA</json:string></affiliations></json:item><json:item><name>Mandayam A. 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After measuring subjects’ initial performance in the real station, different groups of subjects were trained on the virtual station under a variety of conditions and tested finally at the real station. Experiments involved bimanual pushing and cutting tasks on a nonlinear elastic object. The results showed that force feedback results in a significantly improved training transfer compared to training without force feedback. 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A dual station experimental platform was built for the purpose of investigating these fidelity requirements. Analogous laparoscopic surgical tasks were implemented in a virtual and a real station, with the virtual station modeling the real environment to various degrees of fidelity. After measuring subjects’ initial performance in the real station, different groups of subjects were trained on the virtual station under a variety of conditions and tested finally at the real station. Experiments involved bimanual pushing and cutting tasks on a nonlinear elastic object. The results showed that force feedback results in a significantly improved training transfer compared to training without force feedback. The training effectiveness of a linear approximation model was comparable to the effectiveness of a more accurate nonlinear model.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>The Role of Simulation Fidelity in Laparoscopic Surgical Training</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>The Role of Simulation Fidelity in Laparoscopic Surgical Training</title></titleInfo><name type="personal"><namePart type="given">Hyun</namePart><namePart type="given">K.</namePart><namePart type="family">Kim</namePart><affiliation>Department of Mechanical Engineering and The Research Laboratory of Electronics Massachusetts Institute of Technology, The Touch Lab, 02139, Cambridge, MA, USA</affiliation><affiliation>E-mail: hyunkim@mit.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">David</namePart><namePart type="given">W.</namePart><namePart type="family">Rattner</namePart><affiliation>Division of General and Gastrointestinal Surgery Massachusetts General Hospital, The Touch Lab, 02114, Boston, MA, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Mandayam</namePart><namePart type="given">A.</namePart><namePart type="family">Srinivasan</namePart><affiliation>Department of Mechanical Engineering and The Research Laboratory of Electronics Massachusetts Institute of Technology, The Touch Lab, 02139, Cambridge, MA, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference [eBooks]" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2003</dateIssued><copyrightDate encoding="w3cdtf">2003</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: Although there have been significant advances in the development of virtual reality based surgical simulations, there still 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 in a virtual and a real station, with the virtual station modeling the real environment to various degrees of fidelity. After measuring subjects’ initial performance in the real station, different groups of subjects were trained on the virtual station under a variety of conditions and tested finally at the real station. Experiments involved bimanual pushing and cutting tasks on a nonlinear elastic object. The results showed that force feedback results in a significantly improved training transfer compared to training without force feedback. The training effectiveness of a linear approximation model was comparable to the effectiveness of a more accurate nonlinear model.</abstract><relatedItem type="host"><titleInfo><title>Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003</title><subTitle>6th International Conference, Montréal, Canada, November 15-18, 2003. Proceedings</subTitle></titleInfo><name type="personal"><namePart type="given">Randy</namePart><namePart type="given">E.</namePart><namePart type="family">Ellis</namePart><affiliation>Queen’s University, Kingston, Ontario, Canada</affiliation><affiliation>E-mail: ellis@cs.queensu.ca</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Terry</namePart><namePart type="given">M.</namePart><namePart type="family">Peters</namePart><affiliation>Canadian Surgical Technologies and Advanced Robotics, London, Ontario, Canada</affiliation><affiliation>E-mail: tpeters@imaging.robarts.ca</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="Book Series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">2003</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book Subject Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book Subject Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I22021">Image Processing and Computer Vision</topic><topic authority="SpringerSubjectCodes" authorityURI="H28009">Health Informatics</topic><topic authority="SpringerSubjectCodes" authorityURI="H29005">Imaging / Radiology</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. Robotics)</topic><topic authority="SpringerSubjectCodes" authorityURI="I22013">Computer Graphics</topic><topic authority="SpringerSubjectCodes" authorityURI="I2203X">Pattern Recognition</topic></subject><identifier type="DOI">10.1007/b93810</identifier><identifier type="ISBN">978-3-540-20462-6</identifier><identifier type="eISBN">978-3-540-39899-8</identifier><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="BookTitleID">80281</identifier><identifier type="BookID">978-3-540-39899-8</identifier><identifier type="BookChapterCount">98</identifier><identifier type="BookVolumeNumber">2878</identifier><identifier type="BookSequenceNumber">2878</identifier><identifier type="PartChapterCount">15</identifier><part><date>2003</date><detail type="part"><title>Simulation and Planning</title></detail><detail type="volume"><number>2878</number><caption>vol.</caption></detail><extent unit="pages"><start>1</start><end>8</end></extent></part><recordInfo><recordOrigin>Springer-Verlag Berlin Heidelberg, 2003</recordOrigin></recordInfo></relatedItem><relatedItem type="series"><titleInfo><title>Lecture Notes in Computer Science</title></titleInfo><name type="personal"><namePart type="given">Gerhard</namePart><namePart type="family">Goos</namePart><affiliation>Karlsruhe University, Germany</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Juris</namePart><namePart type="family">Hartmanis</namePart><affiliation>Cornell University, NY, USA</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Jan</namePart><namePart type="family">van Leeuwen</namePart><affiliation>Utrecht University, The Netherlands</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><originInfo><copyrightDate encoding="w3cdtf">2003</copyrightDate><issuance>serial</issuance></originInfo><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="SeriesID">558</identifier><recordInfo><recordOrigin>Springer-Verlag Berlin Heidelberg, 2003</recordOrigin></recordInfo></relatedItem><identifier type="istex">2775841B871F20FAEF6CB9D735297F1E9CF396D9</identifier><identifier type="DOI">10.1007/978-3-540-39899-8_1</identifier><identifier type="ChapterID">1</identifier><identifier type="ChapterID">Chap1</identifier><accessCondition type="use and reproduction" contentType="copyright">Springer-Verlag Berlin Heidelberg, 2003</accessCondition><recordInfo><recordContentSource>SPRINGER</recordContentSource><recordOrigin>Springer-Verlag Berlin Heidelberg, 2003</recordOrigin></recordInfo></mods></metadata><enrichments><istex:refBibTEI 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