Multi-sensory force/deformation cues for stiffness characterization in soft-tissue palpation.
Identifieur interne : 001567 ( PubMed/Corpus ); précédent : 001566; suivant : 001568Multi-sensory force/deformation cues for stiffness characterization in soft-tissue palpation.
Auteurs : M. Tavakoli ; A. Aziminejad ; R V Patel ; M. MoallemSource :
- Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference [ 1557-170X ] ; 2006.
English descriptors
- KwdEn :
- MESH :
- methods : Palpation.
- physiology : Connective Tissue, Sensation.
- Adult, Computer Simulation, Cues, Elasticity, Female, Humans, Male, Models, Biological, Task Performance and Analysis, User-Computer Interface.
Abstract
In the commercially available robot-assisted surgical systems, camera vision constitutes the only flow of data from the patient side to the surgeon side. This paper studies how various modalities for feedback of interaction between a surgical tool and soft tissue can improve the efficiency of a typical surgical task. Utilizing a haptics-enabled master-slave test-bed for minimally invasive surgery, user performance during a telemanipulated soft tissue stiffness discrimination task is compared under visual, haptic, graphical, and graphical plus haptic feedback modes in terms of task success rate and completion time and the amount of energy transfer and consequently trauma to tissue. While no significant difference is found in terms of the task completion times, graphical cueing and visual cueing are found to lead to the highest success rate and the highest risk of tissue damage (proportional to energy), respectively.
DOI: 10.1109/IEMBS.2006.260292
PubMed: 17946425
Links to Exploration step
pubmed:17946425Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Multi-sensory force/deformation cues for stiffness characterization in soft-tissue palpation.</title><author><name sortKey="Tavakoli, M" sort="Tavakoli, M" uniqKey="Tavakoli M" first="M" last="Tavakoli">M. Tavakoli</name><affiliation><nlm:affiliation>Canadian Surgical Technologies & Advanced Robotics, London Health Sciences Centre, London, Ontario, Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Aziminejad, A" sort="Aziminejad, A" uniqKey="Aziminejad A" first="A" last="Aziminejad">A. Aziminejad</name></author><author><name sortKey="Patel, R V" sort="Patel, R V" uniqKey="Patel R" first="R V" last="Patel">R V Patel</name></author><author><name sortKey="Moallem, M" sort="Moallem, M" uniqKey="Moallem M" first="M" last="Moallem">M. Moallem</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2006">2006</date><idno type="doi">10.1109/IEMBS.2006.260292</idno><idno type="RBID">pubmed:17946425</idno><idno type="pmid">17946425</idno><idno type="wicri:Area/PubMed/Corpus">001567</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Multi-sensory force/deformation cues for stiffness characterization in soft-tissue palpation.</title><author><name sortKey="Tavakoli, M" sort="Tavakoli, M" uniqKey="Tavakoli M" first="M" last="Tavakoli">M. Tavakoli</name><affiliation><nlm:affiliation>Canadian Surgical Technologies & Advanced Robotics, London Health Sciences Centre, London, Ontario, Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Aziminejad, A" sort="Aziminejad, A" uniqKey="Aziminejad A" first="A" last="Aziminejad">A. Aziminejad</name></author><author><name sortKey="Patel, R V" sort="Patel, R V" uniqKey="Patel R" first="R V" last="Patel">R V Patel</name></author><author><name sortKey="Moallem, M" sort="Moallem, M" uniqKey="Moallem M" first="M" last="Moallem">M. Moallem</name></author></analytic><series><title level="j">Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference</title><idno type="ISSN">1557-170X</idno><imprint><date when="2006" type="published">2006</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult</term><term>Computer Simulation</term><term>Connective Tissue (physiology)</term><term>Cues</term><term>Elasticity</term><term>Female</term><term>Humans</term><term>Male</term><term>Models, Biological</term><term>Palpation (methods)</term><term>Sensation (physiology)</term><term>Task Performance and Analysis</term><term>User-Computer Interface</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Palpation</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Connective Tissue</term><term>Sensation</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Computer Simulation</term><term>Cues</term><term>Elasticity</term><term>Female</term><term>Humans</term><term>Male</term><term>Models, Biological</term><term>Task Performance and Analysis</term><term>User-Computer Interface</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In the commercially available robot-assisted surgical systems, camera vision constitutes the only flow of data from the patient side to the surgeon side. This paper studies how various modalities for feedback of interaction between a surgical tool and soft tissue can improve the efficiency of a typical surgical task. Utilizing a haptics-enabled master-slave test-bed for minimally invasive surgery, user performance during a telemanipulated soft tissue stiffness discrimination task is compared under visual, haptic, graphical, and graphical plus haptic feedback modes in terms of task success rate and completion time and the amount of energy transfer and consequently trauma to tissue. While no significant difference is found in terms of the task completion times, graphical cueing and visual cueing are found to lead to the highest success rate and the highest risk of tissue damage (proportional to energy), respectively.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">17946425</PMID><DateCreated><Year>2007</Year><Month>10</Month><Day>23</Day></DateCreated><DateCompleted><Year>2008</Year><Month>03</Month><Day>19</Day></DateCompleted><DateRevised><Year>2014</Year><Month>08</Month><Day>21</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">1557-170X</ISSN><JournalIssue CitedMedium="Print"><Volume>1</Volume><PubDate><Year>2006</Year></PubDate></JournalIssue><Title>Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference</Title><ISOAbbreviation>Conf Proc IEEE Eng Med Biol Soc</ISOAbbreviation></Journal><ArticleTitle>Multi-sensory force/deformation cues for stiffness characterization in soft-tissue palpation.</ArticleTitle><Pagination><MedlinePgn>837-40</MedlinePgn></Pagination><Abstract><AbstractText>In the commercially available robot-assisted surgical systems, camera vision constitutes the only flow of data from the patient side to the surgeon side. This paper studies how various modalities for feedback of interaction between a surgical tool and soft tissue can improve the efficiency of a typical surgical task. Utilizing a haptics-enabled master-slave test-bed for minimally invasive surgery, user performance during a telemanipulated soft tissue stiffness discrimination task is compared under visual, haptic, graphical, and graphical plus haptic feedback modes in terms of task success rate and completion time and the amount of energy transfer and consequently trauma to tissue. While no significant difference is found in terms of the task completion times, graphical cueing and visual cueing are found to lead to the highest success rate and the highest risk of tissue damage (proportional to energy), respectively.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Tavakoli</LastName><ForeName>M</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Canadian Surgical Technologies & Advanced Robotics, London Health Sciences Centre, London, Ontario, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Aziminejad</LastName><ForeName>A</ForeName><Initials>A</Initials></Author><Author ValidYN="Y"><LastName>Patel</LastName><ForeName>R V</ForeName><Initials>RV</Initials></Author><Author ValidYN="Y"><LastName>Moallem</LastName><ForeName>M</ForeName><Initials>M</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Conf Proc IEEE Eng Med Biol Soc</MedlineTA><NlmUniqueID>101243413</NlmUniqueID><ISSNLinking>1557-170X</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName MajorTopicYN="N" UI="D000328">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D003198">Computer Simulation</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D003238">Connective Tissue</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D003463">Cues</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D004548">Elasticity</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D005260">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006801">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D008297">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D008954">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D010173">Palpation</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D012677">Sensation</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D013647">Task Performance and Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D014584">User-Computer Interface</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2007</Year><Month>10</Month><Day>20</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2008</Year><Month>3</Month><Day>20</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2007</Year><Month>10</Month><Day>20</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="doi">10.1109/IEMBS.2006.260292</ArticleId><ArticleId IdType="pubmed">17946425</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/HapticV1/Data/PubMed/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 001567 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PubMed/Corpus/biblio.hfd -nk 001567 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Ticri/CIDE
|area= HapticV1
|flux= PubMed
|étape= Corpus
|type= RBID
|clé= pubmed:17946425
|texte= Multi-sensory force/deformation cues for stiffness characterization in soft-tissue palpation.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Corpus/RBID.i -Sk "pubmed:17946425" \
| HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Corpus/biblio.hfd \
| NlmPubMed2Wicri -a HapticV1
| This area was generated with Dilib version V0.6.23. |  |