The utilization of nonlinear dynamics in the assessment of balance and gait kinematics in multiple sclerosis

Date of Award


Degree Name

M.S. in Mechanical Engineering


Department of Mechanical and Aerospace Engineering


Advisor: Kimberly E. Bigelow


Multiple sclerosis (MS) is a progressively debilitating disease that primarily affects the central nervous system of the body. Current research has begun to establish a wide variety of assessment techniques to assist in diagnosis and continued evaluation of disease progression as well as physical and cognitive responses to treatments with biomechanical analyses serving as one of the primary means to accomplish this task. Most notably, how balance and gait are impaired is of great interest since these are two of the most commonly impaired systems in those with MS. This research continues to expand the understanding of how to best evaluate the biomechanics of individuals with MS by investigating the usefulness of relatively new analysis techniques that have started to be implemented in the biomechanics field, notably Detrended Fluctuation Analysis (DFA) and Lyapunov Exponents (LyE). Prior research has revealed the potential usefulness of these methods in other neurodegenerative diseases, but limited application to MS. A total of thirty individuals were recruited for this study, 15 minimally impaired MS subjects (48.5±9.6yrs) and 15 healthy control subjects (47.7±8.7yrs). MS subjects had to be community ambulatory (require no assistance to walk i.e. no use of canes/walkers or other assistive devices), stable on any medication regimens, and also pass a pre-screening health questionnaire. Balance assessment incorporated the use of a balance plate where center of pressure information was collected in a similar methodology as the Modified Clinical Test for Sensory Interaction on Balance (mCTSIB). Gait testing was conducted while walking on a treadmill where joint kinematics were collected using a 3D motion capture system utilizing IR reflective markers placed over prominent bone structures of the lower extremities. Analysis of the balance and gait data revealed significant differences (p<0.05) in both the traditional and nonlinear outcome measures, however no single analysis method stood out amongst the rest. Particularly in the balance assessment, the nonlinear measures do not appear to be an effective way to differentiate between healthy and minimally impaired MS. Unlike in balance, the nonlinear measures used for the gait data performed well in identifying differences between the two groups, indicating that the MS gait system was less stable than that of a healthy system. Even though the traditional gait measures also identified differences, the two sets of results provided different information on the system under investigation, allowing for a more comprehensive assessment of level of impairment. While further work is necessary, the use of nonlinear dynamics in the assessment of balance and gait in neurodegenerative diseases does warrant its use.


Balance Measurement Case studies, Gait in humans Measurement Case studies, Kinematics Case studies, Multiple sclerosis Diagnosis Case studies, Biomechanics Research, Nonlinear mechanics

Rights Statement

Copyright 2012, author