The Task-Dependent Efficacy of Shared-Control Haptic Guidance Paradigms.
Identifieur interne : 000D42 ( PubMed/Corpus ); précédent : 000D41; suivant : 000D43The Task-Dependent Efficacy of Shared-Control Haptic Guidance Paradigms.
Auteurs : D. Powell ; M K O'MalleySource :
- IEEE transactions on haptics [ 1939-1412 ] ; 2012.
Abstract
Shared-control haptic guidance is a common form of robot-mediated training used to teach novice subjects to perform dynamic tasks. Shared-control guidance is distinct from more traditional guidance controllers, such as virtual fixtures, in that it provides novices with real-time visual and haptic feedback from a real or virtual expert. Previous studies have shown varying levels of training efficacy using shared-control guidance paradigms; it is hypothesized that these mixed results are due to interactions between specific guidance implementations ("paradigms") and tasks. This work proposes a novel guidance paradigm taxonomy intended to help classify and compare the multitude of implementations in the literature, as well as a revised proxy rendering model to allow for the implementation of more complex guidance paradigms. The efficacies of four common paradigms are compared in a controlled study with 50 healthy subjects and two dynamic tasks. The results show that guidance paradigms must be matched to a task's dynamic characteristics to elicit effective training and low workload. Based on these results, we provide suggestions for the future development of improved haptic guidance paradigms.
DOI: 10.1109/TOH.2012.40
PubMed: 26964107
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Powell</name></author><author><name sortKey="O Malley, M K" sort="O Malley, M K" uniqKey="O Malley M" first="M K" last="O'Malley">M K O'Malley</name></author></analytic><series><title level="j">IEEE transactions on haptics</title><idno type="ISSN">1939-1412</idno><imprint><date when="2012" type="published">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Shared-control haptic guidance is a common form of robot-mediated training used to teach novice subjects to perform dynamic tasks. Shared-control guidance is distinct from more traditional guidance controllers, such as virtual fixtures, in that it provides novices with real-time visual and haptic feedback from a real or virtual expert. Previous studies have shown varying levels of training efficacy using shared-control guidance paradigms; it is hypothesized that these mixed results are due to interactions between specific guidance implementations ("paradigms") and tasks. This work proposes a novel guidance paradigm taxonomy intended to help classify and compare the multitude of implementations in the literature, as well as a revised proxy rendering model to allow for the implementation of more complex guidance paradigms. The efficacies of four common paradigms are compared in a controlled study with 50 healthy subjects and two dynamic tasks. The results show that guidance paradigms must be matched to a task's dynamic characteristics to elicit effective training and low workload. Based on these results, we provide suggestions for the future development of improved haptic guidance paradigms.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="PubMed-not-MEDLINE"><PMID Version="1">26964107</PMID><DateCreated><Year>2016</Year><Month>03</Month><Day>11</Day></DateCreated><DateCompleted><Year>2016</Year><Month>03</Month><Day>12</Day></DateCompleted><Article PubModel="Print"><Journal><ISSN IssnType="Print">1939-1412</ISSN><JournalIssue CitedMedium="Print"><Volume>5</Volume><Issue>3</Issue><PubDate><Year>2012</Year></PubDate></JournalIssue><Title>IEEE transactions on haptics</Title><ISOAbbreviation>IEEE Trans Haptics</ISOAbbreviation></Journal><ArticleTitle>The Task-Dependent Efficacy of Shared-Control Haptic Guidance Paradigms.</ArticleTitle><Pagination><MedlinePgn>208-19</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1109/TOH.2012.40</ELocationID><Abstract><AbstractText>Shared-control haptic guidance is a common form of robot-mediated training used to teach novice subjects to perform dynamic tasks. Shared-control guidance is distinct from more traditional guidance controllers, such as virtual fixtures, in that it provides novices with real-time visual and haptic feedback from a real or virtual expert. Previous studies have shown varying levels of training efficacy using shared-control guidance paradigms; it is hypothesized that these mixed results are due to interactions between specific guidance implementations ("paradigms") and tasks. This work proposes a novel guidance paradigm taxonomy intended to help classify and compare the multitude of implementations in the literature, as well as a revised proxy rendering model to allow for the implementation of more complex guidance paradigms. The efficacies of four common paradigms are compared in a controlled study with 50 healthy subjects and two dynamic tasks. The results show that guidance paradigms must be matched to a task's dynamic characteristics to elicit effective training and low workload. 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