Reconstruction and EMG-informed control, simulation and analysis of human movement for athletics: Performance improvement and injury prevention

Handle URI:
http://hdl.handle.net/10754/599466
Title:
Reconstruction and EMG-informed control, simulation and analysis of human movement for athletics: Performance improvement and injury prevention
Authors:
Demircan, E.; Khatib, O.; Wheeler, J.; Delp, S.
Abstract:
In this paper we present methods to track and characterize human dynamic skills using motion capture and electromographic sensing. These methods are based on task-space control to obtain the joint kinematics and extract the key physiological parameters and on computed muscle control to solve the muscle force distribution problem. We also present a dynamic control and analysis framework that integrates these metrics for the purpose of reconstructing and analyzing sports motions in real-time.
Citation:
Demircan E, Khatib O, Wheeler J, Delp S (2009) Reconstruction and EMG-informed control, simulation and analysis of human movement for athletics: Performance improvement and injury prevention. 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Available: http://dx.doi.org/10.1109/IEMBS.2009.5333148.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Issue Date:
Sep-2009
DOI:
10.1109/IEMBS.2009.5333148
PubMed ID:
19964175
PubMed Central ID:
PMC4479296
Type:
Conference Paper
Sponsors:
This work was supported in part bythe Simbios National Center for Biomedical Computing Grant(http://simbios.stanford.edu/, NIH GM072970) and KAUST (KingAbdullah University of Science and Technology).
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Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorDemircan, E.en
dc.contributor.authorKhatib, O.en
dc.contributor.authorWheeler, J.en
dc.contributor.authorDelp, S.en
dc.date.accessioned2016-02-28T05:51:40Zen
dc.date.available2016-02-28T05:51:40Zen
dc.date.issued2009-09en
dc.identifier.citationDemircan E, Khatib O, Wheeler J, Delp S (2009) Reconstruction and EMG-informed control, simulation and analysis of human movement for athletics: Performance improvement and injury prevention. 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Available: http://dx.doi.org/10.1109/IEMBS.2009.5333148.en
dc.identifier.pmid19964175en
dc.identifier.doi10.1109/IEMBS.2009.5333148en
dc.identifier.urihttp://hdl.handle.net/10754/599466en
dc.description.abstractIn this paper we present methods to track and characterize human dynamic skills using motion capture and electromographic sensing. These methods are based on task-space control to obtain the joint kinematics and extract the key physiological parameters and on computed muscle control to solve the muscle force distribution problem. We also present a dynamic control and analysis framework that integrates these metrics for the purpose of reconstructing and analyzing sports motions in real-time.en
dc.description.sponsorshipThis work was supported in part bythe Simbios National Center for Biomedical Computing Grant(http://simbios.stanford.edu/, NIH GM072970) and KAUST (KingAbdullah University of Science and Technology).en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subject.meshTask Performance and Analysisen
dc.titleReconstruction and EMG-informed control, simulation and analysis of human movement for athletics: Performance improvement and injury preventionen
dc.typeConference Paperen
dc.identifier.journal2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Societyen
dc.identifier.pmcidPMC4479296en
dc.contributor.institutionMechanical Engineering Department, Stanford University, Stanford, CA 94305, USA. emeld@stanford.eduen

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