Advisor: Stephen Sprigle, PhD (APPH)

Committee:

Aldo Ferri, PhD (Mechanical Engineering)
Jun Ueda, PhD (Mechanical Engineering)
Maysam Ghovanloo,PhD (Electrical and Computer Engineering)
Young-Hui Chang, PhD (APPH)
Mark Greig (Industry)

Development of a Dynamic Wheelchair Model with Empirical Validation by a Robotic Testbed

For the 1.6 million wheelchair users who live in the United States, the wheelchair forms the foundation for all of their academic, vocational, and societal activities. Amongst these users, 94% own manual wheelchairs, a mobility device that relies on the occupant for propulsive force. Less mechanically efficient wheelchairs require these users to exert greater instantaneous force and total effort for accomplishing desired travel. Greater propulsion effort can lead to difficulty in achieving desired speeds, a higher probability of fatigue over long bouts of mobility, and difficulty negotiating inclines. The accumulation of this greater effort can also increase the potential for injury in the upper extremities. Regretfully, despite the risks associated with low performance wheelchairs, modern wheelchair design is hinged upon hitting arbitrary weight cutoffs that determine the amount of government medical coverage.

Systems-level dynamic wheelchair models would offer the ability to analytically investigate how different components and designs influence efficiency. To date, models have been developed by the wheelchair community, but are limited to straight-line motion, lack accurate modeling of kinetics, or do not have sufficient empirical validation. Therefore, the objective of the proposed research will be to develop a family of dynamic models that define the relationship between wheelchair properties and their respective impacts on wheelchair performance. The novelty of this modeling approach will stem from the use of a wheelchair-propelling robotic test bed for model validation, as well as custom-designed measurement tools that characterize inertial and resistive wheelchair properties for model input. The proposed approach will 1) model wheelchair kinematics to characterize and partition the system kinetic energy, 2) develop a dynamic wheelchair model to partition resistive energy losses, and 3) generate a cost of transport function for optimizing manual wheelchair design.

Specifically, these models will illustrate how mechanical design parameters impact the complex interactions between inertia and energy loss during wheelchair maneuvers. By developing accurate dynamic models for manual wheelchairs, manufacturers will be given the capacity to optimize wheelchair design based on objective performance metrics. Furthermore, users and clinicians will be better informed about selecting wheelchair configurations to best meet the needs of users.