Affiliations: [a] Department of Engineering Science and Mechanics,
Virginia Polytechnic Institute and State University, Blacksburg, VA,
USA | [b] Virginia Tech-Wake Forest School of Biomedical
Engineering and Sciences, Virginia Polytechnic Institute and State University,
Blacksburg, VA, USA | [c] Virginia Tech Center for Gerontology, Virginia
Polytechnic Institute and State University, Blacksburg, VA, USA | [d] Department of Industrial and Systems Engineering,
Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
Note: [] Address for correspondence: Michael L. Madigan, Department of
Engineering Science and Mechanics (MC 0219), Virginia Polytechnic Institute and
State University, Blacksburg, VA 24061, USA. Tel.: +1 540 231 1215; Fax: +1 540
231 4574; E-mail: [email protected]
Abstract: Joint kinematics influence maximum voluntary muscular moment of
force about a joint, and can thereby have substantial effects on available
muscle moment during dynamic activities. A model of maximum voluntary muscle
moment as a function of joint angle and angular velocity has been described
previously. Originally, a computational optimization approach was used to fit
this model to muscle moment data collected using an isokinetic dynamometer. To
make this model more practical and accessible, an algorithm was developed to
directly determine the model parameters without requiring optimization. This
algorithm was compared with the optimization method for fitting measured muscle
moment data from six different lower limb exertions in 14 healthy adults. Both
methods produced models that fit the measured moment data reasonably well
(r^{2} typically > 0.75), and the direct
calculation method reduced r^{2} only slightly compared to
optimization (by an average of 1.14%). The direct calculation algorithm
presented here may be preferable to the optimization approach used previously,
as it displays comparable performance but requires less time and expertise to
employ.
