The objective of this research is to develop a trustworthy and high-performance neural-machine interface (NMI) that accurately determines a user?s locomotion mode in real-time for neural-controlled artificial legs. The proposed approach is to design the NMI by integrating a new pattern recognition strategy with a high-performance computing embedded system. This project tackles the challenges of accurate interpretation of information from the neuromuscular system, a physical system, using appropriate computation in a cyber system to process the information in real-time. The neural-machine interface consists of multiple sensors that reliably monitor the neural and mechanical information and a set of new algorithms that can fuse and coordinate the highly dynamic information for accurate identification of user intent. The algorithm is to be implemented on a high-performance graphic processing unit (GPU) to meet real-time requirements. This project has the potential to enable the design of neural-controlled artificial legs and may initiate a new direction for research in and the design of prosthetic leg systems. Innovations in this domain have the potential to improve the quality of life of leg amputees, including soldiers with limb amputations. The proposed approaches seek to permit cyber systems to cope with physical uncertainty and dynamics, a common challenge in cyber-physical systems, and to pave a way for applying high-performance computing in biomedical engineering. Besides providing comprehensive training to undergraduate and graduate students, the investigators plan to introduce community college students to cyber-physical systems concepts in an interactive and engaging manner.

The objective of this research is to establish a new development paradigm that enables the effective design, implementation, and certification of medical device cyber-physical systems. The approach is to pursue the following research directions: 1) to support medical device interconnectivity and interoperability with network-enabled control; 2) to apply coordination between medical devices to support emerging clinical scenarios; 3) to ?close the loop? and enable feedback about the condition of the patient to the devices delivering therapy; and 4) to assure safety and effectiveness of interoperating medical devices. The intellectual merits of the project are 1) foundations for rigorous development, which include formalization of clinical scenarios, operational procedures, and architectures of medical device systems, as well as patient and caregiver modeling; 2) high-confidence software development for medical device systems that includes the safe and effective composition of clinical scenarios and devices into a dynamically assembled system; 3) validation and certification of medical device cyber-physical systems; and 4) education of the next-generation of medical device system developers who must be literate in both computational and physical aspects of devices. The broader impacts of the project will be achieved in three ways. Novel design methods and certification techniques will significantly improve patient safety. The introduction of closed-loop scenarios into clinical practice will reduce the burden that caregivers are currently facing and will have the potential of reducing the overall costs of health care. Finally, the educational efforts and outreach activities will increase awareness of careers in the area of medical device systems and help attract women and under-represented minorities to the field.