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Discrete Dynamics in Nature and Society
Volume 2013 (2013), Article ID 586480, 13 pages
Research Article

Towards Human Capture Movement: Estimation of Anatomical Movements of the Shoulder

1National Polytechnic Institute (IPN), SEPI ESIME Azcapotzalco, 02250 México, DF, Mexico
2Facultad de Ingeniería, Universidad Autónoma de San Luis Potosí—UASLP, 78290 San Luis Potosí, SLP, Mexico
3Facultad de Ciencias de la Electrónica, Benemérita Universidad Autónoma de Puebla—BUAP 72450 Puebla, PUE, Mexico

Received 26 October 2012; Revised 20 December 2012; Accepted 3 January 2013

Academic Editor: Gualberto Solís-Perales

Copyright © 2013 B. B. Salmerón-Quiroz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In this paper we focus on the human arm motion capture, which is motivated by the requirements in physical rehabilitation and training of stroke patients in the same way as monitoring of elderly person activities. The proposed methodology uses a data fusion of low-cost and low-weight MEMS sensors jointly to an a priori knowledge of the arm anatomy. The main goal is to estimate the arm position, the anatomical movements of the shoulder and its accelerations. We propose a discrete optimization based-approach which aims to search the optimal attitude ambiguity directly without decorrelation of ambiguity, and to computing the baseline vector consequently. The originality of this paper is to apply the discrete optimization to track the desired trajectory of a nonlinear system such as the Human Movement in the presence of uncertainties. The global asymptotic convergence of the nonlinear observer is guaranteed. Extensive tests of the presented methodology with real world data illustrate the effectiveness of the proposed procedure.