Use of a Hill-Based Muscle Model in the Fast Orthogonal Search Method to Estimate Wrist Force and Upper Arm Physiological Parameters
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Date
2008-10-30T15:49:37Z
Authors
Mountjoy, Katherine
Keyword
Fast Orthogonal Search , sEMG , Surface Electromyography , Hill-Based Model , Optimal Joint Angle , Elbow Flexion/Extension
Abstract
Modelling of human motion is used in a wide range of applications.
An important aspect of accurate representation of human movement is
the ability to customize models to account for individual
differences. The following work proposes a methodology using
Hill-based candidate functions in the Fast Orthogonal Search (FOS)
method to predict translational force at the wrist from flexion and
extension torque at the elbow. Within this force estimation
framework, it is possible to implicitly estimate subject-specific
physiological parameters of Hill-based models of upper arm muscles.
Surface EMG data from three muscles of the upper arm (biceps
brachii, brachioradialis and triceps brachii) were recorded from 10
subjects as they performed isometric contractions at varying elbow
joint angles. Estimated muscle activation level and joint kinematic
data (joint angle and angular velocity) were utilized as inputs to
the FOS model. The resulting wrist force estimations were found to
be more accurate for models utilizing Hill-based candidate
functions, than models utilizing candidate functions that were not
physiologically relevant. Subject-specific estimates of optimal
joint angle were determined via frequency analysis of the selected
FOS candidate functions. Subject-specific optimal joint angle
estimates demonstrated low variability and fell within the range of
angles presented in the literature.