CSR: Small: Development of Distributed Neural Processing Electronics for Whole-Body Computing and Biomedical Sensor Fusion

可穿戴电子设备和健康辅助设备已广泛用于日常活动跟踪和医疗保健。然而，现有的设备已经不能满足日益增长的计算能力和能源效率的需求，特别是当大量的传感器被用来提高这些设备的性能时。这项工作将开发新一代可穿戴生物医学设备，利用新兴的计算架构和最先进的网络技术来提高此类设备的数据处理能力。所开发的技术将在最先进的假肢康复应用中得到展示。书中提出了几个关键的智力优点。首先，该项目将开发新型分布式神经形态计算架构，该架构具有可扩展，可重构和多芯片神经网络系统，用于传感器融合生物医学设备。来自生理信号的异构传感器数据将通过可重构的神经处理器进行有效处理。此外，为了形成高效的网络，消除路由拥塞，将开发身体通道通信，并与神经处理器相结合，实现高带宽、低延迟、围绕人体的互联网络。这项工作通过创造高效的传感、计算和网络解决方案，为现代生物医学设备带来了重大的进步和好处。提出的发展促进了计算机、电气、生物医学工程等领域的技术融合。该项目的子任务将交付给本科生和研究生课堂，以获得集成电路设计，生物医学仪器，机器学习技术的实践经验。将开设传感器融合生物医学系统计算技术的新课程，将所学知识传播给更广泛的受众。本项目的所有出版物、实验数据、源代码、设计文件将在项目完成后的3年内保留在机构服务器上。所有出版物以及重要的数据、代码和支持设计文件将通过PI的数据存储库访问，http://nu-vlsi.eecs.northwestern.edu/data_repository.html.This奖反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.