Full body inverse dynamics solution: an error analysis and a hybrid approach
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2004/09/08
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Description:Inverse dynamics is a powerful tool for biomechanical analysis of human movement (Winter 1990), but is subject to various sources of inaccuracy. Otimization-based methods have been developed to improve the precision of inverse dynamics computations (e.g., Kuo 1998; Cahouët et al. 2002). While the efficacy of these methods have been tested using simulated data (Kuo 1998) and real data of symmetric planar motions (Cahouët et al. 2002), they have not been applied to analysis of full-body, asymmetric motions where additional constraints or residual errors may arise. Further, these current methods only consider a partial list of error-contributing factors (e.g., noise-polluted acceleration and force plate data). Many other inverse dynamics input variables such as segmental angle and mass properties can also be subject to significant errors or uncertainties (Desjardins et al.1998; Holden et al. 1997). In this work, we explore a new approach to inverse dynamics computations applicable for full-body asymmetric movements. Our approach incorporates both motion and ground reaction force measurements, and optimally weighs the top-down and bottomup solutions based on an analysis of the uncertainties in all possible variables contained in the equations of motion. [Description provided by NIOSH]
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Pages in Document:1-2
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NIOSHTIC Number:nn:20038383
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Citation:Proceedings of the 28th Annual Meeting of the American Society of Biomechanics, September 8-11, 2004, Portland, Oregon. Calgary, Alberta, Canada: American Society of Biomechanics, 2004 Sep; :1-2
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Email:xudong@uiuc.edu
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Federal Fiscal Year:2004
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Performing Organization:University of Illinois Urbana-Champaign
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Peer Reviewed:False
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Start Date:20030901
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Source Full Name:Proceedings of the 28th Annual Meeting of the American Society of Biomechanics, September 8-11, 2004, Portland, Oregon
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End Date:20070831
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Main Document Checksum:urn:sha-512:f5555d51dfc2ffe0877b2d76b51fa43285c31ae7a2154a1f859a5de34d89a754dfb716f0881102030fa99b8cd0f66e2870153907072c610b682a85e7a09fa6d3
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