Emulating prosthetic feet during the prescription process to improve outcomes and justifications
The current process of prescribing prosthetic feet is hampered by imprecise classifications based on self-assessment, recommendations based on subjective prediction, burdensome justification requirements, and slow, costly testing of devices. These problems have been exacerbated by the introduction of robotic prostheses, which can improve gait performance for some individuals, but are very expensive. We propose an alternative process, in which a versatile robotic emulator is used to preview patient interactions with a range of prostheses, while objective data related to effort, stability, speed and preference are collected, all prior to prescription. Results from pilot testing with a prototype emulator system demonstrate accurate haptic rendering of a wide range of prosthesis classes and differentiation of user performance across these classes. Eventually, emulation-based prescription could reduce bias, cost and waste in the prescription process, while simultaneously improving patient outcomes.