Wearable electronics and health assistive devices have become commonly used for daily activity tracking and medical care. However, the existing devices can no longer satisfy the growing demand on computing power and energy efficiency especially when a large number of sensors are utilized to improve the performance of such devices. This work will develop a new generation of wearable biomedical devices that utilize the emerging computing architecture and state-of-art networking techniques to boost the data processing capability of such devices. The developed techniques will be demonstrated in the state-of-art prostheses for rehabilitation application.
Several key intellectual merits are delivered. First of all, this project will develop novel distributed neuromorphic computing architecture featuring a scalable, reconfigurable, and multi-chip neural network system for sensor fusion enabled biomedical devices. Heterogeneous sensor data from physiological signals will be efficiently processed through reconfigurable neural processors. Moreover, to form a highly efficient network and remove routing congestions, body channel communication will be developed and integrated with the neural processors to achieve a high-bandwidth, low-latency, inter-connected network around the human body.
The work brings significant advancement and benefits to modern biomedical devices by creating highly efficient sensing, computing and networking solutions. The proposed development promotes technology fusion across fields of computer, electrical, biomedical engineering. The sub-tasks of the project will be delivered to undergraduate and graduate classrooms for hands-on experience of integrated circuits design, biomedical instrumentation, machine learning techniques. New courses on computing techniques for sensor fusion enabled biomedical system will be created to disseminate the learned knowledge to broader audience.
All publications, and experimental data, source codes, design files from this project will be retained on institutional servers for 3 years after the completion of the project. All publications along with important data, codes, and supporting design files will be made accessible through PI's data repository, http://nu-vlsi.eecs.northwestern.edu/data_repository.html.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
