Search Results for author:
Found 17 papers, 0 papers with code
Invited: Can Wi-R enable perpetual IoB nodes?
While the number of wearables is steadily growing, the wearables/person wearing them faces a limitation due to the need for charging all of them every day.
Sub-1ms Instinctual Interference Adaptive GaN LNA Front-End with Power and Linearity Tuning
The system permits an LNA power consumption to tune from 500 mW to 2 W (4X increase) in order to adjust the linearity from P\textsubscript{1dB, IN}=-10. 5 dBm to 0. 5 dBm (>10X increase).
TD-BPQBC: A 1.8μW 5.5mm3 ADC-less Neural Implant SoC utilizing 13.2pJ/Sample Time-domain Bi-phasic Quasi-static Brain Communication
Untethered miniaturized wireless neural sensor nodes with data transmission and energy harvesting capabilities call for circuit and system-level innovations to enable ultra-low energy deep implants for brain-machine interfaces.
Bi-Phasic Quasistatic Brain Communication for Fully Untethered Connected Brain Implants
To solve the challenge of powering and communication in a brain implant with low end-end channel loss, we present Bi-Phasic Quasistatic Brain Communication (BP-QBC), achieving < 60dB worst-case end-to-end channel loss at a channel length of 55mm, by avoiding the transduction losses during field-modality conversion.
Channel Modeling for Physically Secure Electro-Quasistatic In-Body to Out-of-Body Communication with Galvanic Tx and Multimodal Rx
Increasing number of devices being used in and around the human body has resulted in the exploration of the human body as a communication medium.
A Quantitative Analysis of Physical Security and Path Loss With Frequency for IBOB Channel
Security vulnerabilities demonstrated in implantable medical devices have opened the door for research into physically secure and low power communication methodologies.
A mmWave Oscillator Design Utilizing High-Q Active-Mode On-Chip MEMS Resonators for Improved Fundamental Limits of Phase Noise
(RFT) allows very high-Q active mode resonators, promising crystal-less monolithic clock generation for mmWave systems.
OpenSerDes: An Open Source Process-Portable All-Digital Serial Link
The recent introduction of open source Process Development Kit (OpenPDK) by Skywater technologies in June 2020 has eliminated the barriers to Application-Specific Integrated Circuit (ASIC) design, which is otherwise considered expensive and not easily accessible.
In-The-Wild Interference Characterization and Modelling for Electro-Quasistatic-HBC with Miniaturized Wearables
However, there is a gap in the knowledge about the mechanism and sources of interference in this region (crucial in allowing for proper choice of data transmission band).
Understanding The Role of Magnetic and Magneto-Quasistatic Fields in Human Body Communication
With the advent of wearable technologies, Human Body Communication (HBC) has emerged as a physically secure and power-efficient alternative to the otherwise ubiquitous Wireless Body Area Network (WBAN).
Advanced Biophysical Model to Capture Channel Variability for EQS Capacitive HBC
FEM based simulation results are used to analyze the channel response of human body for different positions and sizes of the device which are further verified using measurement results to validate the developed biophysical model.
Analysis and Design Considerations for Achieving the Fundamental Limits of Phase Noise in mmWave Oscillators with On-Chip MEMS Resonator
Very small electromechanical coupling coefficient in micro-electromechanical systems (MEMS) or acoustic resonators is quite of a concern for oscillator performance, specially at mmWave frequencies.
Electro-Quasistatic Animal Body Communication for Chronic Untethered Rodent Biopotential Recording
Continuous multi-channel monitoring of biopotential signals is vital in understanding the body as a whole, facilitating accurate models and predictions in neural research.
Exploiting Inherent Error-Resiliency of Neuromorphic Computing to achieve Extreme Energy-Efficiency through Mixed-Signal Neurons
In this work, we will analyze, compare and contrast existing neuron architectures with a proposed mixed-signal neuron (MS-N) in terms of performance, power and noise, thereby demonstrating the applicability of the proposed mixed-signal neuron for achieving extreme energy-efficiency in neuromorphic computing.
RF-PUF: Enhancing IoT Security through Authentication of Wireless Nodes using In-situ Machine Learning
Traditional authentication in radio-frequency (RF) systems enable secure data communication within a network through techniques such as digital signatures and hash-based message authentication codes (HMAC), which suffer from key recovery attacks.
RF-PUF: IoT Security Enhancement through Authentication of Wireless Nodes using In-situ Machine Learning
Physical unclonable functions (PUF) in silicon exploit die-to-die manufacturing variations during fabrication for uniquely identifying each die.
An Energy-Efficient Mixed-Signal Neuron for Inherently Error-Resilient Neuromorphic Systems
This work presents the design and analysis of a mixed-signal neuron (MS-N) for convolutional neural networks (CNN) and compares its performance with a digital neuron (Dig-N) in terms of operating frequency, power and noise.
