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