Summary The long term goal of neural interfaces for medical rehabilitation purposes is to replace lost functionality for people with physical disabilities. While great strides have been made in the neuroprosthetics field, the state of the art falls far short of complete restoration of function. For example, there is no consensus on the best modality for extracting signals from the central nervous system, peripheral nervous system, or the musculoskeletal system. There is insufficient evidence of reliable, long-term neural interfaces in human subjects. There are no decoding algorithms that allow for quick, natural, and diverse use of multiple degrees of freedom in the end effector. There is insufficient use of sensory input to close the feedback loop. There are no common measures for training and testing of neural interfaces and human subjects. Technical areas of particular interest that address unmet challenges in neuroscience, medicine, materials, and engineering include: (1) Novel, reliable, and scalable biotic-abiotic interfaces for recording neural or muscle signals; innovation in tissue interface systems that demonstrate high-levels of neural-information extraction, low levels of error, and long functional lifetimes are highly encouraged. (2) Reliable, effective, and clinically viable algorithms for decoding limb-control signals; new algorithmic approaches that maximize the amount and rate of limb-control information while reducing the error, degree of pre-processing, and need for recalibration over time are highly encouraged. (3) Novel, reliable, and scalable biotic-abiotic interfaces for providing sensory stimulation. Proposals should address novel methods that go beyond conventional neural stimulation approaches in order to extend the clinical applications of neural stimulation. Approaches may include, but are not limited to electronic, photonic, tactile, ultrasonic, or chemical stimulation platforms. (4) Training and testing methods; identification of common metrics related to function that would allow systematic investigation of signal processing is encouraged. Applications for this RFP should address one or more of these technical areas. Project Goals The purpose of the proposed RFP is to accelerate research in the field of neural or muscle interfaces with the emphasis on a more naturally controlled prosthesis for people with movement impairments by improving the person/device interface. This solicitation seeks novel approaches for the fusion of neural data with the intent of controlling extracorporeal systems. Proposals designed to capture neural-control signals from central nervous system (CNS) and non-CNS sources (e.g., peripheral nervous system, neuro-musculature system, etc.) are encouraged. The long term goal of the project is to create platform software packages with novel algorithms that can be integrated with one or more modular rehabilitation devices. Phase I Activities and Expected Deliverables Phase I research should generate scientific data confirming the clinical potential of the proposed software. Some of the expected activities are: • Design and development of a prototype system(s). • Development of innovative algorithms to improve neural signal processing methods for guided interventions for individuals with movement impairments. • Demonstration of the capabilities of the software. Final Phase I report should include plans for future work and commercialization. Phase II Activities and Expected Deliverables Production of a laboratory or clinic ready hardware and software package with user friendly graphical interface. Draft user manual.