| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | March 14, 2017 |
| Latest Amendment Date: | March 14, 2017 |
| Award Number: | 1657455 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Erik Brunvand
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | April 1, 2017 |
| End Date: | March 31, 2021 (Estimated) |
| Total Intended Award Amount: | $175,000.00 |
| Total Awarded Amount to Date: | $175,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
2550 NORTHWESTERN AVE # 1100 WEST LAFAYETTE IN US 47906-1332 (765)494-1055 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
155 South Grant Street West Lafayette IN US 47907-2114 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | CRII CISE Research Initiation |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The development of in-sensor analytics, energy-efficient power delivery and secure data transfer has been used to transform the network of wearables/implantables in/on/around human-body. The objectives of this research to develop the key techniques and models to enable energy- efficient, secure, self-powered network of energy-sparse sensor nodes for internet of body (IoB) were met and the publications produced from the research are presented below.
Channel modeling for various modalities of Human Body Communication were performed to investigate the use of human body to act as a communication medium for devices around it.
- On the Safety of Human Body Communication
- Characterization of Human Body Forward Path Loss and Variability Effects in Voltage-Mode HBC
- Bio-Physical Modeling, Characterization, and Optimization of Electro-Quasistatic Human Body Communication
- Understanding The Role of Magnetic and Magneto-Quasistatic Fields in Human Body Communication
- A 100KHz-1GHz Termination-dependent Human Body Communication Channel Measurement using Miniaturized Wearable Devices
- Characterization and Classification of Human Body Channel as a function of Excitation and Termination Modalities
Enhanced signal security in the physical layer using Electroquasistatic Human Body Communication was investigated.
- BodyWire-HCI: Enabling New Interaction Modalities by Communicating Strictly During Touch Using Electro-Quasistatic Human Body Communication
- Wearable health monitoring using capacitive voltage-mode Human Body Communication
- Secure Human-Internet using dynamic Human Body Communication
- Enabling Covert Body Area Network using Electro-Quasistatic Human Body Communication
The design and implementation of state-of-the-art circuits and wearable systems were performed demonstrating low power and physically secure communication enabling efficient Internet of Body.
- Sub-μWRComm: 415-nW 1–10-kb/s Physically and Mathematically Secure Electro-Quasi-Static HBC Node for Authentication and Medical Applications
- A 415 nW Physically and Mathematically Secure Electro-Quasistatic HBC Node in 65nm CMOS for Authentication and Medical Applications
- Flexible submental sensor patch with remote monitoring controls for management of oropharyngeal swallowing disorders
- BodyWire: A 6.3-pJ/b 30-Mb/s −30-dB SIR-Tolerant Broadband Interference-Robust Human Body Communication Transceiver Using Time Domain Interference Rejection
- A 6.3pJ/b 30Mbps −30dB SIR-tolerant broadband interference-robust human body communication transceiver using time domain signal-interference separation
- An Improved Update Rate Baud Rate CDR for Integrating Human Body Communication Receiver
- An Improved Update Rate CDR for Interference Robust Broadband Human Body Communication Receiver
- A Context-aware Reconfigurable Transmitter with 2.24 pJ/bit, 802.15.6 NB-HBC and 4.93 pJ/bit, 400.9 MHz MedRadio Modes with 33.6% Transmit Efficiency
- A sub-nW Wake-up Receiver for Human Body Communication
- Theoretical Analysis of AM and FM Interference Robustness of Integrating DDR Receiver for Human Body Communication
Increasing communication energy efficiency by edge intelligence was analyzed to improve battery lifetime in wearable device technologies.
- Context-Aware Intelligence in Resource-Constrained IoT Nodes: Opportunities and Challenges
- Energy-Efficient Deep Neural Networks with Mixed-Signal Neurons and Dense-Local and Sparse-Global Connectivity
- A 65nm Image Processing SoC Supporting Multiple DNN Models and Real-Time Computation-Communication Trade-Off Via Actor-Critical Neuro-Controller
- Exploiting Inherent Error Resiliency of Deep Neural Networks to Achieve Extreme Energy Efficiency Through Mixed-Signal Neurons.
The outcome of this research was also integrated with the undergraduate and graduate-level courses on Digital and Mixed-Signal Design, published through project website and nano-HUB at Purdue University.
Last Modified: 09/27/2021
Modified by: Shreyas Sen
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