Citation

Demircan E, Khatib O, Wheeler J, Delp SL. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2009; 1: 6534-6537.

Affiliation

Mechanical Engineering Department, Stanford University, Stanford, CA 94305 USA.

Copyright

(Copyright © 2009, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/IEMBS.2009.5333148

PMID

19964175

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.

Language: en