Joseph Hidler, PhD
National Rehabilitation Hospital

Craig Carignan, ScD
Imaging Science and Information Systems Center
Georgetown University

Steven Stanhope, PhD
Physical Disabilities Branch
National Institute of Health

Center for Applied Biomechanics and Rehabilitation Research
National Rehabilitation Hospital
Washington, DC

Significance of the Problem

The proposed research will have a significant clinical impact at neurorehabilitation centers. Current physical therapy interventions rely on subjective measures of a patient's level of walking ability, a strategy that lacks reliability and repeatability. Furthermore, there are no recognized guidelines for baselining, and then progressing the intensity of a patient's therapeutic intervention.

The technique developed in the proposed research will overcome these current limitations. This will allow clinicians to establish the conditions in which the subject exerts the most appropriate forces during stepping, a behavior shown to maximize motor the recovery of stable walking. The technique can also be used as a quantitative tool for evaluating and tracking functional recovery, replacing subjective measures such as the Functional Independence Measure (FIM).

Specific Aims and Objectives

The overall goal of this study is to develop a quantitative method of measuring walking performance in individuals with neurological injury. With an established method, clinicians can optimize therapeutic sessions by training subjects at appropriate walking speeds, levels of body-weight support, and kinematic trajectories. Furthermore, this technique can be used to monitor and track functional recovery, and can also be used to understand how facilatory inputs such as electrical stimulation can be used to enhance step patterns. Accordingly, our specific aims are:

Aim 1. To instrument a Lokomat robotic-orthosis with 6-degrees of freedom load cells which can measure the interaction forces between the patient and the robot while walking on the treadmill.

Aim 2. Develop an inverse dynamics based numerical method for estimating ankle, knee and hip torque patterns during treadmill walking, using refined anthropomorphic and geometric models of the lower limbs.

Aim 3. Test and validate the technique on a small group of healthy individuals with no known neurological injuries.