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Rapid Identification of Muscle Activation Profiles via Optimization and Smooth Profile Patches
Author(s) -
Strobach Daniel,
Kecskemé Andrés
Publication year - 2005
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.200510237
Subject(s) - smoothness , discretization , computation , computer science , sampling (signal processing) , sensitivity (control systems) , identification (biology) , algorithm , control theory (sociology) , biological system , mathematical optimization , simulation , mathematics , mathematical analysis , artificial intelligence , computer vision , engineering , botany , control (management) , filter (signal processing) , electronic engineering , biology
The identification of muscle activation profiles of the musculoskeletal system is an important ans still open problem in biomechanics. Current methodology consists in finding the amplitude and the time history of the activation functions through optimization techniques. In this setting, function parameterizations such as discretization through sampling values, rectangular and ramp functions, as well as splines have been investigated. However, typical optimization runs display prohibitively long computation times, which make them unsuitable for on‐line applications, such as required for example for patient‐specific therapy. the present paper proposes a new method for parameterizing muscle activation profiles employing smooth ( C ∞ ) base functions. The ides is that, for the target approximation of dynamical motions, the detailed geometry of the activation profiles not significant, while its smoothness facilitates the search within the optimization procedure. The results show that, by applying these methods, the required CPU time can be reduced by factors up to 8. We analyze the method for a flexion/extension two joint subsystem of hip and knee, comprising two pairs of antagonistic muscles, showing the sensitivity to sampling time and initial values. From these studies it becomes obvious that determination of muscle activation through optimization can be very sensitive to carefully chosen parameterizations. (© 2005 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)