FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2295405141> ?p ?o ?g. }

• W2295405141 endingPage "683" @default.
• W2295405141 startingPage "676" @default.
• W2295405141 abstract "Brain-machine interfaces (BMIs) are a rapidly progressing technology with the potential to restore function to victims of severe paralysis via neural control of robotic systems. Great strides have been made in directly mapping a user's cortical activity to control of the individual degrees of freedom of robotic end-effectors. While BMIs have yet to achieve the level of reliability desired for widespread clinical use, environmental sensors (e.g. RGB-D cameras for object detection) and prior knowledge of common movement trajectories hold great potential for improving system performance. Here we present a novel sensor fusion paradigm for BMIs that capitalizes on information able to be extracted from the environment to greatly improve the performance of control. This was accomplished by using dynamic movement primitives to model the 3D endpoint trajectories of manipulating various objects. We then used a switching unscented Kalman filter to continuously arbitrate between the 3D endpoint kinematics predicted by the dynamic movement primitives and control derived from neural signals. We experimentally validated our system by decoding 3D endpoint trajectories executed by a non-human primate manipulating four different objects at various locations. Performance using our system showed a dramatic improvement over using neural signals alone, with median distance between actual and decoded trajectories decreasing from 31.1 cm to 9.9 cm, and mean correlation increasing from 0.80 to 0.98. Our results indicate that our sensor fusion framework can dramatically increase the fidelity of neural prosthetic trajectory decoding." @default.
• W2295405141 created "2016-06-24" @default.
• W2295405141 creator A5027749077 @default.
• W2295405141 creator A5031682953 @default.
• W2295405141 creator A5041768910 @default.
• W2295405141 creator A5049259807 @default.
• W2295405141 creator A5069909173 @default.
• W2295405141 creator A5088964967 @default.
• W2295405141 date "2016-07-01" @default.
• W2295405141 modified "2023-10-01" @default.
• W2295405141 title "High Precision Neural Decoding of Complex Movement Trajectories Using Recursive Bayesian Estimation With Dynamic Movement Primitives" @default.
• W2295405141 cites W1729873854 @default.
• W2295405141 cites W1749494163 @default.
• W2295405141 cites W180512009 @default.
• W2295405141 cites W1983877267 @default.
• W2295405141 cites W1986081132 @default.
• W2295405141 cites W1987580357 @default.
• W2295405141 cites W1994151854 @default.
• W2295405141 cites W2002966689 @default.
• W2295405141 cites W2012204020 @default.
• W2295405141 cites W2014885430 @default.
• W2295405141 cites W2033144847 @default.
• W2295405141 cites W2066921639 @default.
• W2295405141 cites W2067474383 @default.
• W2295405141 cites W2097009900 @default.
• W2295405141 cites W2098373948 @default.
• W2295405141 cites W2105102432 @default.
• W2295405141 cites W2105925198 @default.
• W2295405141 cites W2110304639 @default.
• W2295405141 cites W2113972270 @default.
• W2295405141 cites W2136719407 @default.
• W2295405141 cites W2137897295 @default.
• W2295405141 cites W2140546948 @default.
• W2295405141 cites W2142981049 @default.
• W2295405141 cites W2165376801 @default.
• W2295405141 cites W2166422604 @default.
• W2295405141 cites W2167947958 @default.
• W2295405141 cites W2169783813 @default.
• W2295405141 cites W2171077154 @default.
• W2295405141 cites W2210439423 @default.
• W2295405141 cites W4253453051 @default.
• W2295405141 doi "https://doi.org/10.1109/lra.2016.2516590" @default.
• W2295405141 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5473343" @default.
• W2295405141 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28630937" @default.
• W2295405141 hasPublicationYear "2016" @default.
• W2295405141 type Work @default.
• W2295405141 sameAs 2295405141 @default.
• W2295405141 citedByCount "18" @default.
• W2295405141 countsByYear W22954051412016 @default.
• W2295405141 countsByYear W22954051412017 @default.
• W2295405141 countsByYear W22954051412018 @default.
• W2295405141 countsByYear W22954051412019 @default.
• W2295405141 countsByYear W22954051412020 @default.
• W2295405141 countsByYear W22954051412021 @default.
• W2295405141 countsByYear W22954051412022 @default.
• W2295405141 countsByYear W22954051412023 @default.
• W2295405141 crossrefType "journal-article" @default.
• W2295405141 hasAuthorship W2295405141A5027749077 @default.
• W2295405141 hasAuthorship W2295405141A5031682953 @default.
• W2295405141 hasAuthorship W2295405141A5041768910 @default.
• W2295405141 hasAuthorship W2295405141A5049259807 @default.
• W2295405141 hasAuthorship W2295405141A5069909173 @default.
• W2295405141 hasAuthorship W2295405141A5088964967 @default.
• W2295405141 hasBestOaLocation W22954051412 @default.
• W2295405141 hasConcept C107038049 @default.
• W2295405141 hasConcept C11413529 @default.
• W2295405141 hasConcept C118552586 @default.
• W2295405141 hasConcept C121332964 @default.
• W2295405141 hasConcept C1276947 @default.
• W2295405141 hasConcept C13662910 @default.
• W2295405141 hasConcept C138885662 @default.
• W2295405141 hasConcept C154945302 @default.
• W2295405141 hasConcept C157286648 @default.
• W2295405141 hasConcept C15744967 @default.
• W2295405141 hasConcept C173201364 @default.
• W2295405141 hasConcept C2780226923 @default.
• W2295405141 hasConcept C31972630 @default.
• W2295405141 hasConcept C39920418 @default.
• W2295405141 hasConcept C40743351 @default.
• W2295405141 hasConcept C41008148 @default.
• W2295405141 hasConcept C522805319 @default.
• W2295405141 hasConcept C57273362 @default.
• W2295405141 hasConcept C74650414 @default.
• W2295405141 hasConceptScore W2295405141C107038049 @default.
• W2295405141 hasConceptScore W2295405141C11413529 @default.
• W2295405141 hasConceptScore W2295405141C118552586 @default.
• W2295405141 hasConceptScore W2295405141C121332964 @default.
• W2295405141 hasConceptScore W2295405141C1276947 @default.
• W2295405141 hasConceptScore W2295405141C13662910 @default.
• W2295405141 hasConceptScore W2295405141C138885662 @default.
• W2295405141 hasConceptScore W2295405141C154945302 @default.
• W2295405141 hasConceptScore W2295405141C157286648 @default.
• W2295405141 hasConceptScore W2295405141C15744967 @default.
• W2295405141 hasConceptScore W2295405141C173201364 @default.
• W2295405141 hasConceptScore W2295405141C2780226923 @default.
• W2295405141 hasConceptScore W2295405141C31972630 @default.
• W2295405141 hasConceptScore W2295405141C39920418 @default.
• W2295405141 hasConceptScore W2295405141C40743351 @default.

• next