Emerging powered lower limb prostheses hold great promise for restoring normative locomotion in amputees. However, these robotic devices currently lack inter- and intra-wearer adaptability to cope with wearers' physical variations and changes. Frequent manual and heuristic adjustment in clinics is required, which limits the practical use of these advanced prostheses. A new generation of prosthesis control that is intelligent, adaptable, and interactive is needed to better support walking function and improve the quality of life of lower limb amputees. The PIs' long-term research goal is to create bionic legs that can adapt to the individual amputee's physical and cognitive capabilities, coordinate with the wearer's movement and intent, adjust to changing environments, and essentially restore the full function of patients with lower limb impairments. To this end, the PIs' objective in this project is to create a novel optimal control framework for these prostheses. They will systematically address the challenge of supporting automatic adaptation to the wearer's physical capability while achieving desired gait performance for the integrated amputee-prosthesis system. And they will provide a preliminary design and evaluation for an interactive interface that would allow wearers to personalize prosthesis control safely and easily. Project outcomes will open up a new frontier of wearable robotics and lay the foundation for clinical translations of these innovative devices, which will impact not only the prosthetics and orthotics industry but also the robotics community by providing new knowledge relating to human-robot interaction, the biomechanics and neuromotor control community by elucidating the control mechanism of amputee locomotion, and healthcare in general by providing innovative and cost-effective prosthesis solutions.
The new amputee-prosthesis performance-based framework for control of powered lower limb prostheses which this work will introduce represents a departure from existing approaches that mainly focus on design for the prosthesis (a local machine), in that it adopts a global approach by accounting for co-adaptation between amputees and prostheses in order to provide optimal, personalized assistance based on wearers' physical conditions. The PIs will use approximate dynamic programming (ADP) to achieve the global control goal. Such innovative use of ADP will provide an opportunity to demonstrate its optimal adaptive control capability in a new test domain of co-adaptive robotic prosthesis, a unique and significant challenge only seen in human wearable robotics but not in lifeless robots. The ADP scheme is based on approximation and learning that alleviate problems associated with the requirement of accurately modeling wearers' neuromuscular control and dynamics that is difficult, if not impossible, to achieve. Additionally, the PIs will conduct an experimental investigation on subjects with transfemoral amputations of the interactions between amputees and prostheses, including evaluations of the compensatory strategies of amputees, and discrepancy assessment between subjective (human) and objective (machine) preferences in prosthesis control.
