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

CSR: Small: Development of Distributed Neural Processing Electronics for Whole-Body Computing and Biomedical Sensor Fusion
CSR:小型:用于全身计算和生物医学传感器融合的分布式神经处理电子设备的开发
批准号:
1816870
负责人:
Jie Gu
金额:
$50.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-10-01 至 2023-09-30

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中文摘要
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英文摘要
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.
期刊论文(7)
专著(0)
科研奖励(0)
会议论文
A Wearable Bio-signal Processing System with Ultra-low-power SoC and Collaborative Neural Network Classifier for Low Dimensional Data Communication
具有超低功耗 SoC 和用于低维数据通信的协作神经网络分类器的可穿戴生物信号处理系统
DOI: 10.1109/embc44109.2020.9176647
发表时间: 2020
期刊: Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC
影响因子: --
作者: [Wei, Yijie, Cao, Qiankai, Hargrove, Levi, Gu, Jie]
通讯作者: Gu, Jie
A 65nm Implantable Gesture Classification SoC for Rehabilitation with Enhanced Data Compression and Encoding for Robust Neural Network Operation Under Wireless Power Condition
用于康复的 65 纳米植入式手势分类 SoC,具有增强的数据压缩和编码功能,可在无线供电条件下实现稳健的神经网络运行
DOI: 10.1109/cicc53496.2022.9772838
发表时间: 2022
期刊: Custom Integrated Circuit Conference
影响因子: --
作者: [Wei, Yijie, Chen, Xi, Gu, Jie]
通讯作者: Gu, Jie
A Fully-integrated Gesture and Gait Processing SoC for Rehabilitation with ADC-less Mixed-signal Feature Extraction and Deep Neural Network for Classification and Online Training
用于康复的完全集成手势和步态处理 SoC,具有无 ADC 混合信号特征提取和用于分类和在线训练的深度神经网络
DOI: 10.1109/cicc48029.2020.9075910
发表时间: 2020
期刊: Custom Integrated Circuits Conference
影响因子: --
作者: [Wei, Yijie, Cao, Qiankai, Otseidu, Kofi, Hargrove, Levi, Gu, Jie]
通讯作者: Gu, Jie
Human Activity Recognition SoC for AR/VR with Integrated Neural Sensing, AI Classifier and Chained Infrared Communication for Multi-chip Collaboration
用于 AR/VR 的人体活动识别 SoC,具有集成神经传感、AI 分类器和用于多芯片协作的链式红外通信
DOI: 10.23919/vlsitechnologyandcir57934.2023.10185392
发表时间: 2023
期刊: Symposium on VLSI Technology and Circuits
影响因子: --
作者: [Wei, Yijie, Chen, Xi, Gu, Jie]
通讯作者: Gu, Jie
7
    Collaborative Research: CMOS+X: A Device-to-Architecture Co-development and Demonstration of Large-scale Integration of FeFET on CMOS for Emerging Computing Applications
    • 批准号:
      2318807
    • 项目类别:
      Standard Grant
    • 资助金额:
      $38.5万
    • 财政年份:
      2023
    • 负责人:
      Jie Gu
    • 依托单位:
    SHF: Small: A Chip of Happiness: Device-to-System Developments of Affective Computing for Human-in-the-loop Computer System
    • 批准号:
      2208573
    • 项目类别:
      Standard Grant
    • 资助金额:
      $60.0万
    • 财政年份:
      2022
    • 负责人:
      Jie Gu
    • 依托单位:
    SHF: Small: Development of Differentiable Memory Augmented Neural CPU Architecture for Cognitive Computing
    • 批准号:
      2008906
    • 项目类别:
      Standard Grant
    • 资助金额:
      $50.0万
    • 财政年份:
      2020
    • 负责人:
      Jie Gu
    • 依托单位:
    CAREER: Design and Synthesis of Energy-efficient Time-domain Computing for Intelligent Edge Processing
    • 批准号:
      1846424
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $100.0万
    • 财政年份:
      2019
    • 负责人:
      Jie Gu
    • 依托单位:
    国内基金
    海外基金
    昼夜节律性small RNA在血斑形成时间推断中的法医学应用研究
    • 批准号:
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
    • 依托单位:
    tRNA-derived small RNA上调YBX1/CCL5通路参与硼替佐米诱导慢性疼痛的机制研究
    • 批准号:
    • 项目类别:
      省市级项目
    • 资助金额:
      10.0万元
    • 批准年份:
      2022
    • 负责人:
      张祥忠
    • 依托单位:
    Small RNA调控I-F型CRISPR-Cas适应性免疫性的应答及分子机制
    Small RNAs调控解淀粉芽胞杆菌FZB42生防功能的机制研究
    • 批准号:
      31972324
    • 项目类别:
      面上项目
    • 资助金额:
      58.0万元
    • 批准年份:
      2019
    • 负责人:
      高学文
    • 依托单位: