218 research outputs found

    An Integrated Platform for Differential Electrochemical and ISFET Sensing

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    A fully-integrated differential biosensing platform on CMOS is presented for miniaturized enzyme-based electrochemical sensing. It enables sensor background current elimination and consists of a differential sensor array and a differential readout IC (DiRIC). The sensor array includes a four-electrode sensor for amperometric electrochemical sensing, as well as a differential ISFET-based pH sensor to calibrate the biosensors. The ISFET is biased in weak inversion and co-designed with DiRIC to enable pH measurements from 1 to 14 with resolution of 0.1 pH. DiRIC enables differential current measurement in the range of ¿¿100 ¿¿A with more than 120dB dynamic range

    An investigation into spike-based neuromorphic approaches for artificial olfactory systems

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    The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over the last decade, research on neuromorphic olfaction has established the capability of these sensors to tackle problems that plague the current e-nose implementations such as drift, response time, portability, power consumption and size. This article brings together the key contributions in neuromorphic olfaction and identifies future research directions to develop near-real-time olfactory sensors that can be implemented for a range of applications such as biosecurity and environmental monitoring. Furthermore, we aim to expose the computational parallels between neuromorphic olfaction and gustation for future research focusing on the correlation of these senses

    Integrated Electronics to Control and Readout Electrochemical Biosensors for Implantable Applications

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    Biosensors can effectively be used to monitor multiple metabolites such as glucose, lactate, ATP and drugs in the human body. Continuous monitoring of these metabolites is essential for patients with chronic or critical conditions. Moreover, this can be used to tune the dosage of a drug for each individual patient, in order to achieve personalized therapy. Implantable medical devices (IMDs) based on biosensors are emerging as a valid alternative for blood tests in laboratories. They can provide continuous monitoring while reduce the test costs. The potentiostat plays a fundamental role in modern biosensors. A potentiostat is an electronic device that controls the electrochemical cell, using three electrodes, and runs the electrochemical measurement. In particular the IMDs require a low-power, fully-integrated, and autonomous potentiostats to control and readout the biosensors. This thesis describes two integrated circuits (ICs) to control and readout multi-target biosensors: LOPHIC and ARIC. They enable chronoamperometry and cyclic voltammetrymeasurements and consume sub-mW power. The design, implementation, characterisation, and validation with biosensors are presented for each IC. To support the calibration of the biosensors with environmental parameters, ARIC includes circuitry to measure the pHand temperature of the analyte through an Iridiumoxide pH sensor and an off-chip resistor-temperature detector (RTD). In particular, novel circuits to convert resistor value into digital are designed for RTD readout. ARIC is integrated into two IMDs aimed for health-care monitoring and personalized therapy. The control and readout of the embedded sensor arrays have been successfully achieved, thanks to ARIC, and validated for glucose and paracetamol measurements while it is remotely powered through an inductive link. To ensure the security and privacy of IMDs, a lightweight cryptographic system (LCS) is presented. This is the first ASIC implementation of a cryptosystem for IMDs, and is integrated into ARIC. The resulting system provides a unique and fundamental capability by immediately encrypting and signing the sensor data upon its creation within the body. Nano-structures such as Carbon nanotubes have been widely used to improve the sensitivity of the biosensors. However, in most of the cases, they introduce more noise into the measurements and produce a large background current. In this thesis the noise of the sensors incorporating CNTs is studied for the first time. The effect of CNTs as well as sensor geometry on the signal to noise ratio of the sensors is investigated experimentally. To remove the background current of the sensors, a differential readout scheme has been proposed. In particular, a novel differential readout IC is designed and implemented that measures inputcurrents within a wide dynamic range and produces a digital output that corresponds to the -informative- redox current of the biosensor

    Solid State Circuits Technologies

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    The evolution of solid-state circuit technology has a long history within a relatively short period of time. This technology has lead to the modern information society that connects us and tools, a large market, and many types of products and applications. The solid-state circuit technology continuously evolves via breakthroughs and improvements every year. This book is devoted to review and present novel approaches for some of the main issues involved in this exciting and vigorous technology. The book is composed of 22 chapters, written by authors coming from 30 different institutions located in 12 different countries throughout the Americas, Asia and Europe. Thus, reflecting the wide international contribution to the book. The broad range of subjects presented in the book offers a general overview of the main issues in modern solid-state circuit technology. Furthermore, the book offers an in depth analysis on specific subjects for specialists. We believe the book is of great scientific and educational value for many readers. I am profoundly indebted to the support provided by all of those involved in the work. First and foremost I would like to acknowledge and thank the authors who worked hard and generously agreed to share their results and knowledge. Second I would like to express my gratitude to the Intech team that invited me to edit the book and give me their full support and a fruitful experience while working together to combine this book

    High Voltage and Nanoscale CMOS Integrated Circuits for Particle Physics and Quantum Computing

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    Design and Implementation of an Integrated Biosensor Platform for Lab-on-a-Chip Diabetic Care Systems

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    Recent advances in semiconductor processing and microfabrication techniques allow the implementation of complex microstructures in a single platform or lab on chip. These devices require fewer samples, allow lightweight implementation, and offer high sensitivities. However, the use of these microstructures place stringent performance constraints on sensor readout architecture. In glucose sensing for diabetic patients, portable handheld devices are common, and have demonstrated significant performance improvement over the last decade. Fluctuations in glucose levels with patient physiological conditions are highly unpredictable and glucose monitors often require complex control algorithms along with dynamic physiological data. Recent research has focused on long term implantation of the sensor system. Glucose sensors combined with sensor readout, insulin bolus control algorithm, and insulin infusion devices can function as an artificial pancreas. However, challenges remain in integrated glucose sensing which include degradation of electrode sensitivity at the microscale, integration of the electrodes with low power low noise readout electronics, and correlation of fluctuations in glucose levels with other physiological data. This work develops 1) a low power and compact glucose monitoring system and 2) a low power single chip solution for real time physiological feedback in an artificial pancreas system. First, glucose sensor sensitivity and robustness is improved using robust vertically aligned carbon nanofiber (VACNF) microelectrodes. Electrode architectures have been optimized, modeled and verified with physiologically relevant glucose levels. Second, novel potentiostat topologies based on a difference-differential common gate input pair transimpedance amplifier and low-power voltage controlled oscillators have been proposed, mathematically modeled and implemented in a 0.18μm [micrometer] complementary metal oxide semiconductor (CMOS) process. Potentiostat circuits are widely used as the readout electronics in enzymatic electrochemical sensors. The integrated potentiostat with VACNF microelectrodes achieves competitive performance at low power and requires reduced chip space. Third, a low power instrumentation solution consisting of a programmable charge amplifier, an analog feature extractor and a control algorithm has been proposed and implemented to enable continuous physiological data extraction of bowel sounds using a single chip. Abdominal sounds can aid correlation of meal events to glucose levels. The developed integrated sensing systems represent a significant advancement in artificial pancreas systems

    A 177 ppm RMS Error-Integrated Interface for Time-Based Impedance Spectroscopy of Sensors

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    This paper presents an integrated circuit for time-based electrical impedance spectroscopy (EIS) of sensors. The circuit exploits maximum-length sequences (MLS) in order to perform a broadband excitation of the sensors under test. Therefore, the measured time-domain EIS is obtained by cross-correlating the input with the output of the analog front end (AFE). Unlike the conventional digital approach, the cross-correlation operation is performed in the analog domain. This leads to a lower RMS error in the measured time-domain EIS since the signal processing is not affected by the quantization noise of the analog-to-digital converter (ADC). It also relaxes the sampling frequency of the ADC leading, along with the lack of random access memory (RAM) usage, to a reduced circuit complexity. Theoretical concepts about the circuit’s design and operation are presented, with an emphasis on the thermal noise phenomenon. The simulated performances are shown by testing a sensor’s equivalent model composed of a 50 kΩ resistor in parallel with a 100 (Formula presented.) (Formula presented.) capacitor. A time-based EIS output of 255 points was obtained with a maximum tested frequency of 500 (Formula presented.) (Formula presented.) and a simulated RMS error of 0.0177% (or 177 ppm)

    Noise Efficient Integrated Amplifier Designs for Biomedical Applications

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    The recording of neural signals with small monolithically integrated amplifiers is of high interest in research as well as in commercial applications, where it is common to acquire 100 or more channels in parallel. This paper reviews the recent developments in low-noise biomedical amplifier design based on CMOS technology, including lateral bipolar devices. Seven major circuit topology categories are identified and analyzed on a per-channel basis in terms of their noise-efficiency factor (NEF), input-referred absolute noise, current consumption, and area. A historical trend towards lower NEF is observed whilst absolute noise power and current consumption exhibit a widespread over more than five orders of magnitude. The performance of lateral bipolar transistors as amplifier input devices is examined by transistor-level simulations and measurements from five different prototype designs fabricated in 180 nm and 350 nm CMOS technology. The lowest measured noise floor is 9.9 nV/√Hz with a 10 µA bias current, which results in a NEF of 1.2
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