Title :
Use of the Fast Orthogonal Search Method to Estimate Optimal Joint Angle For Upper Limb Hill-Muscle Models
Author :
Mountjoy, Katherine ; Morin, Evelyn ; Hashtrudi-Zaad, Keyvan
Author_Institution :
Dept. of Electr. & Comput. Eng., Queen´´s Univ., Kingston, ON, Canada
fDate :
4/1/2010 12:00:00 AM
Abstract :
An important aspect of accurate representation of human movement is the ability to account for differences between individuals. The following paper 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-prediction framework, it is possible to implicitly estimate subject-specific physiological parameters of Hill-based models of upper arm muscles. Surface electromyography data from three muscles of the upper arm (biceps brachii, brachioradialis, and triceps brachii) were recorded from ten subjects, as they performed isometric contractions at varying elbow joint angles. Estimated muscle activation level and joint angle were utilized as inputs to the FOS model. Subject-specific estimates of optimal joint angles for the three muscles were determined via frequency analysis of the selected FOS candidate functions.
Keywords :
biomechanics; bone; electromyography; medical signal processing; physiological models; biceps brachii; brachioradialis; elbow; extension torque; fast orthogonal search method; flexion; force-prediction framework; frequency analysis; human movement; isometric contractions; muscle activation level; optimal joint angle; surface electromyography data; translational force; triceps brachii; upper arm muscles; upper limb hill-muscle models; wrist; Biomechanics; electromyography; modeling; Adult; Arm; Biomechanics; Elbow; Electromyography; Female; Humans; Isometric Contraction; Male; Models, Biological; Muscle, Skeletal; Nonlinear Dynamics; Normal Distribution; Pliability; Range of Motion, Articular; Signal Processing, Computer-Assisted; Statistics, Nonparametric; Torque; Wrist;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2009.2036444