Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?
Identifieur interne : 000300 ( PubMed/Curation ); précédent : 000299; suivant : 000301Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?
Auteurs : Meike Fels ; Robert Bauer ; Alireza GharabaghiSource :
- Journal of neural engineering [ 1741-2552 ] ; 2015.
English descriptors
- KwdEn :
- Adult, Brain-Computer Interfaces, Cerebral Cortex (physiology), Electromyography (methods), Female, Humans, Male, Middle Aged, Nerve Net (physiology), Neurofeedback (methods), Physical Exertion (physiology), Psychomotor Performance (physiology), Rest (physiology), Robotics (methods), Workload, Young Adult.
- MESH :
- methods : Electromyography, Neurofeedback, Robotics.
- physiology : Cerebral Cortex, Nerve Net, Physical Exertion, Psychomotor Performance, Rest.
- Adult, Brain-Computer Interfaces, Female, Humans, Male, Middle Aged, Workload, Young Adult.
Abstract
Novel rehabilitation strategies apply robot-assisted exercises and neurofeedback tasks to facilitate intensive motor training. We aimed to disentangle task-specific and subject-related contributions to the perceived workload of these interventions and the related cortical activation patterns.
DOI: 10.1088/1741-2560/12/4/046029
PubMed: 26170164
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We aimed to disentangle task-specific and subject-related contributions to the perceived workload of these interventions and the related cortical activation patterns.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">26170164</PMID><DateCreated><Year>2015</Year><Month>07</Month><Day>21</Day></DateCreated><DateCompleted><Year>2016</Year><Month>04</Month><Day>11</Day></DateCompleted><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1741-2552</ISSN><JournalIssue CitedMedium="Internet"><Volume>12</Volume><Issue>4</Issue><PubDate><Year>2015</Year><Month>Aug</Month></PubDate></JournalIssue><Title>Journal of neural engineering</Title><ISOAbbreviation>J Neural Eng</ISOAbbreviation></Journal><ArticleTitle>Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?</ArticleTitle><Pagination><MedlinePgn>046029</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1088/1741-2560/12/4/046029</ELocationID><Abstract><AbstractText Label="OBJECTIVE" NlmCategory="OBJECTIVE">Novel rehabilitation strategies apply robot-assisted exercises and neurofeedback tasks to facilitate intensive motor training. We aimed to disentangle task-specific and subject-related contributions to the perceived workload of these interventions and the related cortical activation patterns.</AbstractText><AbstractText Label="APPROACH" NlmCategory="METHODS">We assessed the perceived workload with the NASA Task Load Index in twenty-one subjects who were exposed to two different feedback tasks in a cross-over design: (i) brain-robot interface (BRI) with haptic/proprioceptive feedback of sensorimotor oscillations related to motor imagery, and (ii) control of neuromuscular activity with feedback of the electromyography (EMG) of the same hand. We also used electroencephalography to examine the cortical activation patterns beforehand in resting state and during the training session of each task.</AbstractText><AbstractText Label="MAIN RESULTS" NlmCategory="RESULTS">The workload profile of BRI feedback differed from EMG feedback and was particularly characterized by the experience of frustration. The frustration level was highly correlated across tasks, suggesting subject-related relevance of this workload component. Those subjects who were specifically challenged by the respective tasks could be detected by an interhemispheric alpha-band network in resting state before the training and by their sensorimotor theta-band activation pattern during the exercise.</AbstractText><AbstractText Label="SIGNIFICANCE" NlmCategory="CONCLUSIONS">Neurophysiological profiles in resting state and during the exercise may provide task-independent workload markers for monitoring and matching participants' ability and task difficulty of neurofeedback interventions.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Fels</LastName><ForeName>Meike</ForeName><Initials>M</Initials></Author><Author ValidYN="Y"><LastName>Bauer</LastName><ForeName>Robert</ForeName><Initials>R</Initials></Author><Author ValidYN="Y"><LastName>Gharabaghi</LastName><ForeName>Alireza</ForeName><Initials>A</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><ArticleDate DateType="Electronic"><Year>2015</Year><Month>07</Month><Day>14</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>J Neural Eng</MedlineTA><NlmUniqueID>101217933</NlmUniqueID><ISSNLinking>1741-2552</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName MajorTopicYN="N" UI="D000328">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D062207">Brain-Computer Interfaces</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D002540">Cerebral Cortex</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D004576">Electromyography</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000379">methods</QualifierName></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="N" UI="D008875">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D009415">Nerve Net</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D058765">Neurofeedback</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D005082">Physical Exertion</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D011597">Psychomotor Performance</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D012146">Rest</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D012371">Robotics</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D016526">Workload</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D055815">Young Adult</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="aheadofprint"><Year>2015</Year><Month>7</Month><Day>14</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2015</Year><Month>7</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2015</Year><Month>7</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>4</Month><Day>12</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="doi">10.1088/1741-2560/12/4/046029</ArticleId><ArticleId IdType="pubmed">26170164</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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