Abstract of Thesis Presented to the Graduate School
 of the University of Florida in Partial Fulfillment of the
 Requirements for the Degree of Master of Science

 DETERMINATION OF PATIENT-SPECIFIC FUNCTIONAL AXES
 THROUGH TWO-LEVEL OPTIMIZATION

 By

 Jeffrey A. Reinbolt

 August 2003

Chair: Benjamin J. Fregly
Major Department: Biomedical Engineering

 An innovative patient-specific dynamic model would be useful for evaluating and

enhancing corrective surgical procedures. This thesis presents a nested (or two-level)

system identification optimization approach to determine patient-specific model

parameters that best fit a three-dimensional (3D), 18 degree-of-freedom (DOF)

lower-body model to an individual's movement data.

 The whole body was modeled as a 3D, 14 segment, 27 DOF linkage joined by a set

of gimbal, universal, and pin joints. For a given set of model parameters, the inner-level

optimization uses a nonlinear least squares algorithm that adjusts each generalized

coordinate of the lower-body model to minimize 3D marker coordinate errors between

the model and motion data for each time instance. The outer-level optimization

implements a parallel particle swarm algorithm that modifies each model parameter to

minimize the sum of the squares of 3D marker coordinate errors computed by the

inner-level optimization throughout all time instances (or the entire motion).