Linked Life Data

21097061

Source:http://linkedlifedata.com/resource/pubmed/id/21097061

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2010-11-24
pubmed:abstractText
Recent research in brain-machine interfaces and devices to treat neurological disease indicate that important network activity exists at temporal and spatial scales beyond the resolution of existing implantable devices. We present innovations in both hardware and software that allow sampling and interpretation of data from brain networks from hundreds or thousands of sensors at submillimeter resolution. These innovations consist of novel flexible, active electrode arrays and unsupervised algorithms for detecting and classifying neurophysiologic biomarkers, specifically high frequency oscillations. We propose these innovations as the foundation for a new generation of closed loop diagnostic and therapeutic medical devices, and brain-machine interfaces.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1557-170X
pubmed:author
pubmed:issnType
Print
pubmed:volume
2010
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
3825-6
pubmed:dateRevised
2011-8-1
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Mining terabytes of submillimeter-resolution ECoG datasets for neurophysiologic biomarkers.
pubmed:affiliation
Department of Bioengineering at the University of Pennsylvania, Philadelphia, PA 19104, USA.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural