Abstract
The selection of a prosthetic foot that best suits an individual's unique gait patterns and mobility needs is currently an
overwhelmingly challenging process. There are over 100 prosthetic feet available on the market, each with a different
combination of mechanical behaviors, such as forefoot stiffness, heel stiffness, and energy return. Adding to the difficulty,
the current prescription process in the US creates major barriers for patients to "pilot" multiple prosthetic feet, which often
results in most patients being fitted with a sub-optimal prosthesis given their gait biomechanics and ambulation goals.
Unfortunately, sub-optimal prosthesis fit can result in long-term complications such as low back pain, knee osteoarthritis,
discomfort, reduced community ambulation, and decreased quality of life. Prosthetists, the clinical experts that select and
align prosthetic feet to the socket, use informal systems based on both patient feedback and visual assessment of gait quality
to improve prosthesis alignment—but tools and techniques for quickly finding the patient-optimal prosthesis model are
currently not available.
To address this issue, this project aims to develop the Ankle-Foot Optimization Tool (A-FOOT), a robotic device that can
accurately and quickly replicate the behavior of any commercially available ankle-foot prosthesis. This new technology will
consist of a wearable mechatronic platform that will allow the emulated prosthesis’s mechanical properties to be adjusted
by prosthetists using a simple tablet-based app. Specifically, the app will enable prosthetists to make adjustments to the
emulator's heel stiffness, forefoot stiffness, series damping, and parallel damping, providing them with the ability to
customize the emulator's behavior to the specific needs of each patient. The device performance will be validated through
a series of benchtop tests, and by comparing the just-noticeable difference, or limit of patient perception, for
plantar/dorsiflexion alignment, forefoot stiffness, and hindfoot stiffness to values found with quasi-passive systems.
Additionally, a pilot n=3 study will be conducted, in which three prosthetist-patient pairs will work together to select their
preferred setting, and repeated testing (with random re-seeding of the start point) will provide a metric of prescription
consistency.
The long-term vision of this project is to revolutionize the prosthesis prescription process by enabling prosthetists to rapidly
find the optimal foot model and alignment using this robotic emulator, improving the quality of life for individuals who
have lost their leg, and reducing risk of long-term secondary complications. This proposal takes a major step towards
realizing this future by creating and validating the mechatronic system upon which this new future will be built.