Advisor:

Stephen H. Sprigle, PhD, PT (School of Mechanical Engineering, Georgia Institute of Technology)

Committee:

Aldo A. Ferri, PhD (School of Mechanical Engineering, Georgia Institute of Technology)
Jun Ueda, PhD (School of Mechanical Engineering, Georgia Institute of Technology)
Young-Hui Chang, PhD (School of Biological Sciences, Georgia Institute of Technology)

Maysam Ghovanloo, PhD (School of Electrical and Computer Engineering, Georgia Institute of Technology)

Mark Greig (Vice President of R&D Engineering, Sunrise Medical LLC)

DEVELOPMENT OF COMPONENT AND SYSTEM-LEVEL TEST METHODS TO CHARACTERIZE MANUAL WHEELCHAIR PROPULSION COST

The current approach to manual wheelchair design lacks a sound and objective connection to metrics for wheelchair performance.  Wheelchair performance directly impacts propulsion effort, which is a strong determinant of user health and mobility.  The objective of this thesis is three-fold: 1) to characterize the inertial and resistive properties of different wheelchair components and configurations, 2) to characterize the systems-level wheelchair propulsion cost, and 3) to model wheelchair propulsion cost as a function of measured component and configuration properties.  To this end, this defense presents the development of 1) a series of instruments and methodologies to evaluate the rotational inertia, rolling resistance, and scrub torque of wheelchair casters and drive wheels on various surface types, and 2) a wheelchair-propelling robot capable of measuring propulsion cost across a collection of maneuvers representative of everyday wheelchair mobility.  Using this collection of devices, I demonstrate the variance manifested in the resistive properties of 8 casters and 4 drive wheels, and the impact of these components (as well as mass and weight distribution) on system-level wheelchair propulsion cost.  Coupling these findings with a theoretical framework describing wheelchair dynamics, I define two empirical models linking system propulsion cost to component resistive properties.  The outcomes of this research empower clinicians and users to make a more informed choice in wheelchair selection by means of a standard, scientifically-motivated performance metric.  Furthermore, the empirical models offer manufacturers a basis by which to optimize their future wheelchair designs, thus motivating a better product for all wheelchair stakeholders.