Reconstruction and EMG-informed control, simulation and analysis of human movement for athletics: performance
Emel Demircan1, Oussama Khatib, Jason Wheeler
1Mechanical Engineering Department, Stanford University, Stanford, CA 94305, USA. emeld@stanford.edu
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.
