A new user-adapted search haptic algorithm to navigate along filiform structures.
Identifieur interne : 000547 ( PubMed/Corpus ); précédent : 000546; suivant : 000548A new user-adapted search haptic algorithm to navigate along filiform structures.
Auteurs : Laura Raya ; Sofia Bayona ; Luis Pastor ; Marcos GarciaSource :
- IEEE transactions on haptics [ 2329-4051 ]
English descriptors
- KwdEn :
- MESH :
- physiology : Brain, Touch.
- ultrastructure : Brain.
- Algorithms, Calibration, Computer Simulation, Humans, Models, Neurological, Software, User-Computer Interface.
Abstract
One of the mayor research challenges of this century is the understanding of the human brain. Regarding this field line, simulation based research is gaining importance. A large amount of money is being spent in huge international projects such as The Human Brain Project [1] and The Blue Brain [2]. The behavior of the brain and, therefore, the behavior of brain simulations depend to a large extend on the neural topology. Neural elements are organized in a connected, dense, complex network of thread-like (i.e., filiform) structures. The analysis of a computer-based simulation using just the visual modality is a highly complex task due to the complexity of the neural topology and the large amounts of multi-variable and multi-modal data generated by computer simulations. In this paper, we propose the use of haptic devices to aid in the navigation along these neural structures, helping neurobiologists in the analysis of neural network topologies. However, haptic navigation constrained to complex filiform networks entails problems when these structures have high frequency features, noise and/or complex branching nodes. We address these issues by presenting a new user-adapted search haptic method that uses the forces exerted by the users to infer their intentions. In addition, we propose a specific calibration technique to adapt the haptic navigation to the user's skills and to the data. We validate this approach through a perceptual study. Finally, we show in this paper the application of our method to the analysis of dense and complex filiform structures in the neurobiology context. Additionally, our technique could be applied to other problems such as electronic circuits and graph exploration.
DOI: 10.1109/TOH.2014.2324574
PubMed: 25248166
Links to Exploration step
pubmed:25248166Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A new user-adapted search haptic algorithm to navigate along filiform structures.</title><author><name sortKey="Raya, Laura" sort="Raya, Laura" uniqKey="Raya L" first="Laura" last="Raya">Laura Raya</name></author><author><name sortKey="Bayona, Sofia" sort="Bayona, Sofia" uniqKey="Bayona S" first="Sofia" last="Bayona">Sofia Bayona</name></author><author><name sortKey="Pastor, Luis" sort="Pastor, Luis" uniqKey="Pastor L" first="Luis" last="Pastor">Luis Pastor</name></author><author><name sortKey="Garcia, Marcos" sort="Garcia, Marcos" uniqKey="Garcia M" first="Marcos" last="Garcia">Marcos Garcia</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="????"><PubDate><MedlineDate>2014 Jul-Sep</MedlineDate></PubDate></date><idno type="doi">10.1109/TOH.2014.2324574</idno><idno type="RBID">pubmed:25248166</idno><idno type="pmid">25248166</idno><idno type="wicri:Area/PubMed/Corpus">000547</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">A new user-adapted search haptic algorithm to navigate along filiform structures.</title><author><name sortKey="Raya, Laura" sort="Raya, Laura" uniqKey="Raya L" first="Laura" last="Raya">Laura Raya</name></author><author><name sortKey="Bayona, Sofia" sort="Bayona, Sofia" uniqKey="Bayona S" first="Sofia" last="Bayona">Sofia Bayona</name></author><author><name sortKey="Pastor, Luis" sort="Pastor, Luis" uniqKey="Pastor L" first="Luis" last="Pastor">Luis Pastor</name></author><author><name sortKey="Garcia, Marcos" sort="Garcia, Marcos" uniqKey="Garcia M" first="Marcos" last="Garcia">Marcos Garcia</name></author></analytic><series><title level="j">IEEE transactions on haptics</title><idno type="eISSN">2329-4051</idno></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Brain (physiology)</term><term>Brain (ultrastructure)</term><term>Calibration</term><term>Computer Simulation</term><term>Humans</term><term>Models, Neurological</term><term>Software</term><term>Touch (physiology)</term><term>User-Computer Interface</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Brain</term><term>Touch</term></keywords><keywords scheme="MESH" qualifier="ultrastructure" xml:lang="en"><term>Brain</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Calibration</term><term>Computer Simulation</term><term>Humans</term><term>Models, Neurological</term><term>Software</term><term>User-Computer Interface</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">One of the mayor research challenges of this century is the understanding of the human brain. Regarding this field line, simulation based research is gaining importance. A large amount of money is being spent in huge international projects such as The Human Brain Project [1] and The Blue Brain [2]. The behavior of the brain and, therefore, the behavior of brain simulations depend to a large extend on the neural topology. Neural elements are organized in a connected, dense, complex network of thread-like (i.e., filiform) structures. The analysis of a computer-based simulation using just the visual modality is a highly complex task due to the complexity of the neural topology and the large amounts of multi-variable and multi-modal data generated by computer simulations. In this paper, we propose the use of haptic devices to aid in the navigation along these neural structures, helping neurobiologists in the analysis of neural network topologies. However, haptic navigation constrained to complex filiform networks entails problems when these structures have high frequency features, noise and/or complex branching nodes. We address these issues by presenting a new user-adapted search haptic method that uses the forces exerted by the users to infer their intentions. In addition, we propose a specific calibration technique to adapt the haptic navigation to the user's skills and to the data. We validate this approach through a perceptual study. Finally, we show in this paper the application of our method to the analysis of dense and complex filiform structures in the neurobiology context. Additionally, our technique could be applied to other problems such as electronic circuits and graph exploration.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">25248166</PMID><DateCreated><Year>2014</Year><Month>09</Month><Day>24</Day></DateCreated><DateCompleted><Year>2015</Year><Month>11</Month><Day>10</Day></DateCompleted><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">2329-4051</ISSN><JournalIssue CitedMedium="Internet"><Volume>7</Volume><Issue>3</Issue><PubDate><MedlineDate>2014 Jul-Sep</MedlineDate></PubDate></JournalIssue><Title>IEEE transactions on haptics</Title><ISOAbbreviation>IEEE Trans Haptics</ISOAbbreviation></Journal><ArticleTitle>A new user-adapted search haptic algorithm to navigate along filiform structures.</ArticleTitle><Pagination><MedlinePgn>273-84</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1109/TOH.2014.2324574</ELocationID><Abstract><AbstractText>One of the mayor research challenges of this century is the understanding of the human brain. Regarding this field line, simulation based research is gaining importance. A large amount of money is being spent in huge international projects such as The Human Brain Project [1] and The Blue Brain [2]. The behavior of the brain and, therefore, the behavior of brain simulations depend to a large extend on the neural topology. Neural elements are organized in a connected, dense, complex network of thread-like (i.e., filiform) structures. The analysis of a computer-based simulation using just the visual modality is a highly complex task due to the complexity of the neural topology and the large amounts of multi-variable and multi-modal data generated by computer simulations. In this paper, we propose the use of haptic devices to aid in the navigation along these neural structures, helping neurobiologists in the analysis of neural network topologies. However, haptic navigation constrained to complex filiform networks entails problems when these structures have high frequency features, noise and/or complex branching nodes. We address these issues by presenting a new user-adapted search haptic method that uses the forces exerted by the users to infer their intentions. In addition, we propose a specific calibration technique to adapt the haptic navigation to the user's skills and to the data. We validate this approach through a perceptual study. Finally, we show in this paper the application of our method to the analysis of dense and complex filiform structures in the neurobiology context. Additionally, our technique could be applied to other problems such as electronic circuits and graph exploration.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Raya</LastName><ForeName>Laura</ForeName><Initials>L</Initials></Author><Author ValidYN="Y"><LastName>Bayona</LastName><ForeName>Sofia</ForeName><Initials>S</Initials></Author><Author ValidYN="Y"><LastName>Pastor</LastName><ForeName>Luis</ForeName><Initials>L</Initials></Author><Author ValidYN="Y"><LastName>Garcia</LastName><ForeName>Marcos</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>IEEE Trans Haptics</MedlineTA><NlmUniqueID>101491191</NlmUniqueID><ISSNLinking>1939-1412</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D000465">Algorithms</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D001921">Brain</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName><QualifierName MajorTopicYN="Y" UI="Q000648">ultrastructure</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D002138">Calibration</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D003198">Computer Simulation</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006801">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D008959">Models, Neurological</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D012984">Software</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D014110">Touch</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D014584">User-Computer Interface</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2014</Year><Month>9</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2014</Year><Month>9</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2015</Year><Month>11</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="doi">10.1109/TOH.2014.2324574</ArticleId><ArticleId IdType="pubmed">25248166</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 000547 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PubMed/Corpus/biblio.hfd -nk 000547 | 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:25248166
|texte= A new user-adapted search haptic algorithm to navigate along filiform structures.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Corpus/RBID.i -Sk "pubmed:25248166" \
| HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Corpus/biblio.hfd \
| NlmPubMed2Wicri -a HapticV1
| This area was generated with Dilib version V0.6.23. |  |