PI: Sensinger, J. W.; Hargrove, L.; and Kording, K. P.<br/>Proposal Number: 1317379<br/><br/>Problem Description: Better robotic prostheses can dramatically improve the quality of life for the more than 40,000 Americans with an upper limb amputation, many of whom reject existing devices because they have trouble controlling them in the same intuitive, subconscious way that they controlled their intact arms. Prosthesis control is difficult because amputees experience great uncertainty both with respect to whether their device will respond appropriately to their control signals and whether sensory feedback cues accurately reflect the actual movement. Researchers have focused on improving isolated aspects of control, for example by improving filters or mimicking able-bodied sensory cues through haptic devices, but these approaches have minimally reduced the uncertainty of prosthesis control. Human interaction with a prosthesis is a multifaceted, time-varying problem that is difficult to solve. What is missing from robotic prosthesis research are principled methods for optimizing control strategies and sensory cues which take into account behavioral choices people are known to make in the face of high uncertainty.<br/><br/>Intellectual Merit: The proposed research is innovative because it poses the co-robot problem in a broader context that incorporates the highly sophisticated behavioral decisions that humans make in optimizing their control strategy and sensory cues. This principled approach is able to integrate multiple effects in ways that were not possible using previous approaches. For example, the proposed approach naturally incorporates the fact that people prefer to use less exerted effort to accomplish a task, but tolerate more effort during portions of movement that require greater precision (e.g. final portion of a trajectory). On the other hand, the approach does not favor high-certainty haptic cues if those cues provide redundant information to existing sensory cues such as vision, or if the haptic information does not reduce the uncertainty of controllable system dynamics. Due to the large sources of control-signal noise present in amputees, the proposed work will lead to improved techniques within the fields of computational motor control and optimal control. This research builds on the team?s extensive experience in the design and control of upper-limb prostheses and in developing the field of computational motor control. Achievement of the proposed aims will contribute to the field of robotic control and to such diverse fields as human-robot interaction, perception, manipulation, and exoskeletons.<br/><br/>Broader Impacts: True biomimetic prostheses, exoskeletons, and humanoid robot control will not be possible until there is a firm understanding of how humans integrate with these co-robots in the face of interacting sources of uncertainty. This computational motor project will provide transformative insight into how humans control movement in the presence of large uncertainty and thus fill a critical gap in the knowledge base of this field. The framework developed in this research will be of great interest to the motor-control research community and may be useful in the restoration of other movement disorders such as spinal cord injury and stroke. The lead institution of this proposal, the Rehabilitation Institute of Chicago (RIC), is consistently ranked the top rehabilitation hospital in the country. The close proximity of research and clinical excellence within RIC ensures that the benefits resulting from this work will be quickly disseminated to prosthesis users. The research team will also seek to reach a broader audience?the laboratories at the RIC are regularly visited by students from local high schools and universities, and the RIC also contributes to outreach activities within inner-city Chicago. These outreach programs promote an awareness of rehabilitation research and an enthusiasm for pursuing a career in engineering. Additionally, the team will develop a K-12 educational module based on the template of the successful Summer School in Computational Sensory-Motor Neuroscience developed at Northwestern University and Queen?s University, which will provide a combination of theory and student-driven experimentation using games that will address many of the Illinois Learning Standards in science, math, and English language arts.