CRII: SHF: IMPLANALYTICS: Smart Implantable with In-Sensor Analytics and Body Coupled Power/Data Transfer

CRII：SHF：IMPLANALYTICS：具有传感器内分析和身体耦合电源/数据传输功能的智能植入物

• 批准号: 1657455
• 负责人: Shreyas Sen
• 金额: $ 17.5万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2021-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1657455&HistoricalAwards=false
• 关键词: CRII; SHF; IMPLANALYTICS; Smart; Implantable

The development of in-sensor analytics, energy-efficient power delivery and secure data transfer has the potential of transforming the network of wearables/implantables in/on/around human-body to seamlessly connect with each other to form a "Human-Intranet", enriching human daily lives with deep societal impact. The objective of this research is to develop the key techniques and models to enable energy- efficient, secure, self-powered network of energy-sparse sensor nodes for Human-Intranet. This research will develop fundamentally new understanding of in-sensor analytics (computation), body-coupled data (communication) and power delivery for smart implanted sensor nodes, supported by mathematical models verified through hardware prototypes.The proposed research will develop a smart implantable self-powered sensor node that can be always connected to an on-body hub without external intervention. Present techniques require physically bringing an interrogation device close to the implanted node to power it and read out data. The proposed technique exploits the low-loss human body channel to power the sensor, in-sensor analytics to compress the data and transfer data using the same low-loss body coupled channel. The project will develop mathematical models verified by experiments for future design space exploration and information/energy analysis for human body network. The outcome of this research will be integrated with the undergraduate and graduate-level courses on Digital and Mixed-Signal Design, published through project website and nano-HUB at Purdue University. The research contributions will be disseminated through publications and transferred to industry partners.

传感器内分析、节能电力输送和安全数据传输的发展有可能改变人体内/上/周围的可穿戴设备/植入设备网络，使其彼此无缝连接，形成“人类内联网”，丰富人类日常生活，并产生深远的社会影响。本研究的目的是开发关键技术和模型，使能源效率，安全，自供电的能量稀疏传感器节点网络的人类内联网。这项研究将从根本上对传感器内分析（计算）、身体耦合数据（通信）和智能植入传感器节点的电力输送产生新的理解，并通过硬件原型验证数学模型。拟议的研究将开发一种智能植入式自供电传感器节点，该节点可以始终连接到身体上的集线器，而无需外部干预。 目前的技术需要物理地将询问设备靠近植入节点以对其供电并读出数据。所提出的技术利用低损耗人体通道来为传感器供电，传感器内分析来压缩数据并使用相同的低损耗身体耦合通道来传输数据。该项目将开发通过实验验证的数学模型，用于未来的设计空间探索和人体网络的信息/能量分析。 这项研究的成果将与本科和研究生课程的数字和混合信号设计，通过项目网站和纳米HUB在普渡大学出版。研究成果将通过出版物传播，并转让给行业合作伙伴。

项目成果

An Improved Update Rate CDR for Interference Robust Broadband Human Body Communication Receiver

抗干扰宽带人体通信接收机更新率改进的CDR

• DOI: 10.1109/tbcas.2019.2940746
• 发表时间: 2019
• 期刊: IEEE Transactions on Biomedical Circuits and Systems
• 影响因子: 5.1
• 作者: Mehrotra, Parikha;Maity, Shovan;Sen, Shreyas
• 通讯作者: Sen, Shreyas

Characterization of Human Body Forward Path Loss and Variability Effects in Voltage-Mode HBC

• DOI: 10.1109/lmwc.2018.2800529
• 发表时间: 2018-03-01
• 期刊: IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS
• 影响因子: 3
• 作者: Maity, Shovan;Mojabe, Kavian;Sen, Shreyas
• 通讯作者: Sen, Shreyas

Energy-Efficient Deep Neural Networks with Mixed-Signal Neurons and Dense-Local and Sparse-Global Connectivity

具有混合信号神经元以及密集局部和稀疏全局连接的节能深度神经网络

• DOI: 10.1145/3394885.3431614
• 发表时间: 2021
• 期刊: Asia and South Pacific Design Automation Conference
• 作者: Chatterjee, Baibhab;Sen, Shreyas
• 通讯作者: Sen, Shreyas

Enabling Covert Body Area Network using Electro-Quasistatic Human Body Communication

• DOI: 10.1038/s41598-018-38303-x
• 发表时间: 2019-03-11
• 期刊: SCIENTIFIC REPORTS
• 影响因子: 4.6
• 作者: Das, Debayan;Maity, Shovan;Sen, Shreyas
• 通讯作者: Sen, Shreyas

Bio-Physical Modeling, Characterization, and Optimization of Electro-Quasistatic Human Body Communication

• DOI: 10.1109/tbme.2018.2879462
• 发表时间: 2019-06-01
• 期刊: IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
• 影响因子: 4.6
• 作者: Maity, Shovan;He, Mingxuan;Sen, Shreyas
• 通讯作者: Sen, Shreyas