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

E. Demircan, O. Khatib, J. Wheeler, S. Delp

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

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.
Original languageEnglish (US)
Title of host publication2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages6534-6537
Number of pages4
ISBN (Print)9781424432967
DOIs
StatePublished - Sep 2009
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: 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).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

Fingerprint Dive into the research topics of 'Reconstruction and EMG-informed control, simulation and analysis of human movement for athletics: Performance improvement and injury prevention'. Together they form a unique fingerprint.

Cite this