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dc.contributor.authorHogan, Neville
dc.contributor.authorSternad, Dagmar
dc.date.accessioned2013-07-30T16:03:14Z
dc.date.available2013-07-30T16:03:14Z
dc.date.issued2013-06
dc.date.submitted2013-02
dc.identifier.issn1662-5188
dc.identifier.urihttp://hdl.handle.net/1721.1/79722
dc.description.abstractHumans achieve locomotor dexterity that far exceeds the capability of modern robots, yet this is achieved despite slower actuators, imprecise sensors, and vastly slower communication. We propose that this spectacular performance arises from encoding motor commands in terms of dynamic primitives. We propose three primitives as a foundation for a comprehensive theoretical framework that can embrace a wide range of upper- and lower-limb behaviors. Building on previous work that suggested discrete and rhythmic movements as elementary dynamic behaviors, we define submovements and oscillations: as discrete movements cannot be combined with sufficient flexibility, we argue that suitably-defined submovements are primitives. As the term “rhythmic” may be ambiguous, we define oscillations as the corresponding class of primitives. We further propose mechanical impedances as a third class of dynamic primitives, necessary for interaction with the physical environment. Combination of these three classes of primitive requires care. One approach is through a generalized equivalent network: a virtual trajectory composed of simultaneous and/or sequential submovements and/or oscillations that interacts with mechanical impedances to produce observable forces and motions. Reliable experimental identification of these dynamic primitives presents challenges: identification of mechanical impedances is exquisitely sensitive to assumptions about their dynamic structure; identification of submovements and oscillations is sensitive to their assumed form and to details of the algorithm used to extract them. Some methods to address these challenges are presented. Some implications of this theoretical framework for locomotor rehabilitation are considered.en_US
dc.description.sponsorshipEric P. and Evelyn E. Newman Funden_US
dc.description.sponsorshipUnited States. Defense Advanced Research Projects Agency. Warrior Web Program (BAA-11-72)en_US
dc.language.isoen_US
dc.publisherFrontiers Research Foundationen_US
dc.relation.isversionofhttp://dx.doi.org/10.3389/fncom.2013.00071en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceFrontiers Research Foundationen_US
dc.titleDynamic primitives in the control of locomotionen_US
dc.typeArticleen_US
dc.identifier.citationHogan, Neville, and Dagmar Sternad. “Dynamic Primitives in the Control of Locomotion.” Frontiers in Computational Neuroscience 7 (2013).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Newman Laboratory for Biomechanics and Human Rehabilitationen_US
dc.contributor.mitauthorHogan, Nevilleen_US
dc.relation.journalFrontiers in Computational Neuroscienceen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsHogan, Neville; Sternad, Dagmaren_US
dc.identifier.orcidhttps://orcid.org/0000-0001-5366-2145
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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