Haptic exploratory behavior during object discrimination: a novel automatic annotation method.
Identifieur interne : 000423 ( PubMed/Curation ); précédent : 000422; suivant : 000424Haptic exploratory behavior during object discrimination: a novel automatic annotation method.
Auteurs : Sander E M. Jansen [Pays-Bas] ; Wouter M. Bergmann Tiest [Pays-Bas] ; Astrid M L. Kappers [Pays-Bas]Source :
- PloS one [ 1932-6203 ] ; 2015.
English descriptors
- KwdEn :
- MESH :
- physiology : Exploratory Behavior, Hand, Touch.
- Female, Humans, Male, Touch Perception, Young Adult.
Abstract
In order to acquire information concerning the geometry and material of handheld objects, people tend to execute stereotypical hand movement patterns called haptic Exploratory Procedures (EPs). Manual annotation of haptic exploration trials with these EPs is a laborious task that is affected by subjectivity, attentional lapses, and viewing angle limitations. In this paper we propose an automatic EP annotation method based on position and orientation data from motion tracking sensors placed on both hands and inside a stimulus. A set of kinematic variables is computed from these data and compared to sets of predefined criteria for each of four EPs. Whenever all criteria for a specific EP are met, it is assumed that that particular hand movement pattern was performed. This method is applied to data from an experiment where blindfolded participants haptically discriminated between objects differing in hardness, roughness, volume, and weight. In order to validate the method, its output is compared to manual annotation based on video recordings of the same trials. Although mean pairwise agreement is less between human-automatic pairs than between human-human pairs (55.7% vs 74.5%), the proposed method performs much better than random annotation (2.4%). Furthermore, each EP is linked to a specific object property for which it is optimal (e.g., Lateral Motion for roughness). We found that the percentage of trials where the expected EP was found does not differ between manual and automatic annotation. For now, this method cannot yet completely replace a manual annotation procedure. However, it could be used as a starting point that can be supplemented by manual annotation.
DOI: 10.1371/journal.pone.0117017
PubMed: 25658703
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Manual annotation of haptic exploration trials with these EPs is a laborious task that is affected by subjectivity, attentional lapses, and viewing angle limitations. In this paper we propose an automatic EP annotation method based on position and orientation data from motion tracking sensors placed on both hands and inside a stimulus. A set of kinematic variables is computed from these data and compared to sets of predefined criteria for each of four EPs. Whenever all criteria for a specific EP are met, it is assumed that that particular hand movement pattern was performed. This method is applied to data from an experiment where blindfolded participants haptically discriminated between objects differing in hardness, roughness, volume, and weight. In order to validate the method, its output is compared to manual annotation based on video recordings of the same trials. Although mean pairwise agreement is less between human-automatic pairs than between human-human pairs (55.7% vs 74.5%), the proposed method performs much better than random annotation (2.4%). Furthermore, each EP is linked to a specific object property for which it is optimal (e.g., Lateral Motion for roughness). We found that the percentage of trials where the expected EP was found does not differ between manual and automatic annotation. For now, this method cannot yet completely replace a manual annotation procedure. However, it could be used as a starting point that can be supplemented by manual annotation.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">25658703</PMID><DateCreated><Year>2015</Year><Month>02</Month><Day>09</Day></DateCreated><DateCompleted><Year>2016</Year><Month>01</Month><Day>22</Day></DateCompleted><DateRevised><Year>2015</Year><Month>02</Month><Day>19</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>10</Volume><Issue>2</Issue><PubDate><Year>2015</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS ONE</ISOAbbreviation></Journal><ArticleTitle>Haptic exploratory behavior during object discrimination: a novel automatic annotation method.</ArticleTitle><Pagination><MedlinePgn>e0117017</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0117017</ELocationID><Abstract><AbstractText>In order to acquire information concerning the geometry and material of handheld objects, people tend to execute stereotypical hand movement patterns called haptic Exploratory Procedures (EPs). Manual annotation of haptic exploration trials with these EPs is a laborious task that is affected by subjectivity, attentional lapses, and viewing angle limitations. In this paper we propose an automatic EP annotation method based on position and orientation data from motion tracking sensors placed on both hands and inside a stimulus. A set of kinematic variables is computed from these data and compared to sets of predefined criteria for each of four EPs. Whenever all criteria for a specific EP are met, it is assumed that that particular hand movement pattern was performed. This method is applied to data from an experiment where blindfolded participants haptically discriminated between objects differing in hardness, roughness, volume, and weight. In order to validate the method, its output is compared to manual annotation based on video recordings of the same trials. Although mean pairwise agreement is less between human-automatic pairs than between human-human pairs (55.7% vs 74.5%), the proposed method performs much better than random annotation (2.4%). Furthermore, each EP is linked to a specific object property for which it is optimal (e.g., Lateral Motion for roughness). We found that the percentage of trials where the expected EP was found does not differ between manual and automatic annotation. For now, this method cannot yet completely replace a manual annotation procedure. However, it could be used as a starting point that can be supplemented by manual annotation.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Jansen</LastName><ForeName>Sander E M</ForeName><Initials>SE</Initials><AffiliationInfo><Affiliation>MOVE Research Institute, VU University Amsterdam, the Netherlands.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bergmann Tiest</LastName><ForeName>Wouter M</ForeName><Initials>WM</Initials><AffiliationInfo><Affiliation>MOVE Research Institute, VU University Amsterdam, the Netherlands.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kappers</LastName><ForeName>Astrid M L</ForeName><Initials>AM</Initials><AffiliationInfo><Affiliation>MOVE Research Institute, VU University Amsterdam, the Netherlands.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>02</Month><Day>06</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS One</MedlineTA><NlmUniqueID>101285081</NlmUniqueID><ISSNLinking>1932-6203</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>J Neurosci Methods. 2013 Sep 15;218(2):214-24</RefSource><PMID Version="1">23769769</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Science. 1972 Mar 24;175(4028):1382-4</RefSource><PMID Version="1">4258209</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>J Physiol. 1979 Jan;286:283-300</RefSource><PMID Version="1">439026</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Cogn Psychol. 1987 Jul;19(3):342-68</RefSource><PMID Version="1">3608405</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>IEEE Trans Haptics. 2013 Oct-Dec;6(4):464-72</RefSource><PMID Version="1">24808398</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Percept Mot Skills. 1993 Jun;76(3 Pt 1):1035-42</RefSource><PMID Version="1">8321574</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Atten Percept Psychophys. 2012 Jan;74(1):204-15</RefSource><PMID Version="1">22006526</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Atten Percept Psychophys. 2013 Oct;75(7):1451-64</RefSource><PMID Version="1">23757045</PMID></CommentsCorrections></CommentsCorrectionsList><MeshHeadingList><MeshHeading><DescriptorName MajorTopicYN="N" UI="D005106">Exploratory Behavior</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D005260">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006225">Hand</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006801">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D008297">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D014110">Touch</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D055698">Touch Perception</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D055815">Young Adult</DescriptorName></MeshHeading></MeshHeadingList><OtherID Source="NLM">PMC4319767</OtherID></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="ecollection"><Year>2015</Year><Month></Month><Day></Day></PubMedPubDate><PubMedPubDate PubStatus="received"><Year>2014</Year><Month>2</Month><Day>20</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2014</Year><Month>12</Month><Day>17</Day></PubMedPubDate><PubMedPubDate PubStatus="epublish"><Year>2015</Year><Month>2</Month><Day>6</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2015</Year><Month>2</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2015</Year><Month>2</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>1</Month><Day>23</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="doi">10.1371/journal.pone.0117017</ArticleId><ArticleId IdType="pii">PONE-D-14-07976</ArticleId><ArticleId IdType="pubmed">25658703</ArticleId><ArticleId IdType="pmc">PMC4319767</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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