DocumentCode
2385855
Title
Reconstruction and EMG-informed control, simulation and analysis of human movement for athletics: Performance improvement and injury prevention
Author
Demircan, Emel ; Khatib, Oussama ; Wheeler, Jason ; Delp, Scott
Author_Institution
Mech. Eng. Dept., Stanford Univ., Stanford, CA, USA
fYear
2009
fDate
3-6 Sept. 2009
Firstpage
6534
Lastpage
6537
Abstract
In this paper we present methods to track and characterize human dynamic skills using motion capture and electromyographic 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.
Keywords
electromyography; gait analysis; medical signal processing; motion control; signal reconstruction; EMG; athletics; electromyography; human movement; motion capture; muscle force distribution; reconstruction; task-space control; Algorithms; Athletic Injuries; Biofeedback, Psychology; Electromyography; Humans; Movement; Physical Fitness; Sports; Task Performance and Analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location
Minneapolis, MN
ISSN
1557-170X
Print_ISBN
978-1-4244-3296-7
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2009.5333148
Filename
5333148
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