CAREER: Body-Wire: Transforming Healthcare using Secure Human Body Connected Intelligent Nodes

职业：Body-Wire：使用安全的人体连接智能节点改变医疗保健

• 批准号: 1944602
• 负责人: Shreyas Sen
• 金额: $ 50万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1944602&HistoricalAwards=false
• 关键词: CAREER; Body; Wire; Transforming; Healthcare

Continually rising cost of healthcare and side-effects of drugs, such as opioid addiction, could be reduced through remote health monitoring systems and closed-loop electroceuticals, which rely on large amount of data continuously traveling around human body from low-energy wearable and implantable sensors to an on-body hub then to the cloud. Today's standard technologies rely on electromagnetic wave for communication around the human body, which is not physically secure and consume orders of magnitude more power than needed by a typical sensor node, making the communication link the energy bottleneck for ultra-low-power body sensor nodes. This research project will lead to a fundamentally new way of thinking about using human body as a "wire" to achieve orders of magnitude lower energy used for communication around the human body while being physically secure (i.e., signals cannot be snooped without physical contact). In addition, this project will use edge-analytics to reduce data volume for efficient Human-Intranet smart sensor nodes. The project will develop the fundamental understanding for designing the smallest (less than one cubic millimeter) body-connected node for connected healthcare. With simulation tools and hardware verification, backed by concrete mathematical model development, this work will open new research directions in Human-Intranet for Healthcare, Human-Computer Interaction and Brain-Machine Interfaces. The outcome of this research will be integrated with undergraduate and graduate courses on Digital Design and Mixed-Signal Design. Mathematical models representing circuit/system level information and energy trade-off will be disseminated through research website. Such experimentally verified models are expected to provide significant impact by serving a broad community of students, researchers, and engineers. Educational prototypes of the research will be used to engage students in educational workshops. The strong engagement through undergraduate research mentorship and minority student mentorship will strengthen the interest of science and technology from underrepresented students. The objective of this research is to transform data communication around the human body by using the human body as a wire to achieve orders of magnitude reduction in communication energy in the body area network and combining it with in-sensor analytics to reduce data volume without significant reduction in information to further improve energy/information efficiency. The project will develop the foundations of energy-efficient and physically secured network of energy-sparse sensor nodes for Human-Intranet. The research exploits the low-loss human body channel itself to power the sensor, perform edge-analytics to compress the data and extract information before transferring the compressed data using the same low-loss human body channel. The body-wire research is expected to solve the problem of high data traffic by achieving 1000x reduction in energy/information, allowing longer-lasting, smarter, smaller (new form-factors, better patient compliance), and lower cost healthcare. The energy reduction and improved physical security (in addition to encryption) will open possibilities of many new sensor nodes with new form factors (e.g., connected patch) for human-centered healthcare networks. Along with developing bio-physical circuit models for human body as a communication medium, optimized transceiver circuits and systems for lossy broadband electro-quasistatic human body channel will be developed and demonstrated through integrated circuit fabrication and measurement. A system-on-chip with sensing, in-sensor analytics, and human-body-communication transceiver will be designed, fabricated, and measured to demonstrate the end-to-end improvement in energy/information efficiency. The project will develop mathematical models verified by experiments for future design space exploration and information/energy analysis for Human-Intranet. If successful, the project will develop the fundamental understanding of designing the smallest body-connected node for connected healthcare.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.

持续上涨的医疗成本和药物副作用，如阿片成瘾，可以通过远程健康监测系统和闭环电子节能器来减少，这些系统依赖于大量数据在人体内持续传输，从低能量的可穿戴和可植入传感器到身体上的集线器，然后再到云。如今的标准技术依赖于人体周围的电磁波进行通信，这在物理上并不安全，并且消耗的功率比典型的传感器节点所需的功率高出几个数量级，使得通信链路成为超低功率人体传感器节点的能量瓶颈。这一研究项目将带来一种全新的思维方式，即利用人体作为一条“电线”，在身体安全的情况下，将用于人体周围交流的能量降低数量级(即，在没有物理接触的情况下，信号是无法窥探的)。此外，该项目将使用边缘分析来减少高效的人-内联网智能传感器节点的数据量。该项目将为设计用于互联医疗的最小(小于1立方毫米)身体连接节点奠定基础。借助仿真工具和硬件验证，以具体的数学模型开发为后盾，这项工作将在医疗保健、人机交互和脑机接口方面开辟新的研究方向。这项研究的成果将与数字设计和混合信号设计的本科生和研究生课程相结合。表示电路/系统级信息和能量权衡的数学模型将通过研究网站传播。这些经过实验验证的模型预计将通过服务于广泛的学生、研究人员和工程师社区而产生重大影响。这项研究的教育原型将用于让学生参与教育研讨会。通过本科生研究指导和少数族裔学生指导的强烈参与将增强未被充分代表的学生对科学技术的兴趣。这项研究的目标是通过使用人体作为电线来实现人体区域网络中通信能量的数量级减少，并将其与传感器内分析相结合来在不大幅减少信息的情况下减少数据量，从而改变人体周围的数据通信，从而进一步提高能量/信息效率。该项目将为人类内联网开发节能和物理安全的能源稀疏传感器节点网络的基础。这项研究利用低损耗人体通道本身为传感器供电，执行边缘分析以压缩数据并提取信息，然后使用相同的低损耗人体通道传输压缩数据。身体线研究预计将通过将能源/信息减少1000倍来解决高数据流量问题，从而实现更持久、更智能、更小(新的外形因素，更好的患者依从性)和更低成本的医疗保健。能量的减少和物理安全性的提高(除了加密)将为许多新的传感器节点提供可能性，这些节点具有新的外形因素(例如，连接的补丁)，用于以人为中心的医疗网络。在开发人体作为通信媒介的生物物理电路模型的同时，还将通过集成电路制作和测试来开发和验证用于有耗宽带电准静态人体信道的优化收发电路和系统。将设计、制造和测量具有传感、传感器内分析和人体通信收发机的片上系统，以展示能源/信息效率的端到端改进。该项目将为未来的设计、空间探索和人类内联网的信息/能量分析开发经实验验证的数学模型。如果成功，该项目将形成为互联医疗设计最小的身体连接节点的基本理解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Sub-GHz In-Body to Out-of-Body Communication Channel Modeling for Ruminant Animals for Smart Animal Agriculture

用于智能动物农业的反刍动物体内到体外通信信道建模

• DOI: 10.1109/tbme.2022.3213262
• 发表时间: 2022
• 期刊: IEEE Transactions on Biomedical Engineering
• 影响因子: 4.6
• 作者: Datta, Arunashish;Kaur, Upinder;Malacco, Victor;Nath, Mayukh;Chatterjee, Baibhab;Donkin, Shawn S.;Voyles, Richard M.;Sen, Shreyas
• 通讯作者: Sen, Shreyas

EICO: Energy-Harvesting Long-Range Environmental Sensor Nodes With Energy-Information Dynamic Co-Optimization

• DOI: 10.1109/jiot.2022.3178422
• 发表时间: 2021-07
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Shitij Avlani;Dong-Hyun Seo;Baibhab Chatterjee;Shreyas Sen

A 415 nW Physically and Mathematically Secure Electro-Quasistatic HBC Node in 65nm CMOS for Authentication and Medical Applications

采用 65nm CMOS 的 415 nW 物理和数学安全电准静态 HBC 节点，适用于身份验证和医疗应用

• DOI: 10.1109/cicc48029.2020.9075930
• 发表时间: 2020
• 期刊: IEEE Custom Integrated Circuits Conference (CICC
• 作者: Maity, Shovan;Modak, Nirmoy;Yang, David;Avlani, Shitij;Nath, Mayukh;Danial, Josef;Das, Debayan;Mehrotra, Parikha;Sen, Shreyas
• 通讯作者: Sen, Shreyas

In-body to Out-of-body Communication Channel Modeling for Ruminant Animals for Smart Animal Agriculture

智能畜牧业反刍动物体内到体外通信通道建模

• DOI: 10.1109/embc46164.2021.9629743
• 发表时间: 2021
• 期刊: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC
• 作者: Datta, Arunashish;Kaur, Upinder;Malacco, Victor;Nath, Mayukh;Chatterjee, Baibhab;Donkin, Shawn S.;Voyles, Richard M.;Sen, Shreyas
• 通讯作者: Sen, Shreyas

A 16 pJ/bit 0.1-15Mbps Compressive Sensing IC with on-chip DWT Sparsifier for Audio Signals

具有用于音频信号的片上 DWT 稀疏器的 16 pJ/bit 0.1-15Mbps 压缩传感 IC

• DOI: 10.1109/cicc51472.2021.9431569
• 发表时间: 2021
• 期刊: 2021 IEEE Custom Integrated Circuits Conference (CICC
• 作者: Gaurav Kumar, K;Chatterjee, Baibhab;Sen, Shreyas
• 通讯作者: Sen, Shreyas