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Current Research

 

*     High Channel Count Neural Signal Processing

*     Low-noise low-power electrochemical instrumentation for wearable health monitoring of biological and chemical hazards

*     Automating and organizing data collection for electrochemical sensor arrays

*     Ionic liquid based Miniaturized Electrochemical Gas Sensor

*     Readout system for detection of plasmodium falciparum parasites

*     Wearable microsystem for biomedical and environmental analysis for health and safety monitoring

 


 

Previous Research

*     Multi-function Microsystem for Electrochemical Biosensor Array

*     Monolithic gas sensor array for health and safety monitoring

*     Post CMOS fabrication for the integration of CMOS and electrochemical biosensors

*     Wearable Autonomous Microsystem with Electrochemical Gas Sensor Array for Real-Time Health and Safety Monitoring

*     Gas sensor array signal processing

*     A Neural Signal Processor for Wireless Implants

*     Low power, low noise, multi-channel implanted neural interface circuit

*     Post CMOS fabrication for electrochemical measurement of biointerface

*     Electrochemical Microsystem Array for Functional Proteomics

*     Chemiresistor Instrumentation

*     On-Chip Amperometric Readout of Electrochemical Sensors

*     AMSaC Mixed Signal Generic Test Board

*     Highly Adaptive Multi-Sensor Readout and Communication Interface Circuits

*     Process-Scalable Optimization of Wide-Issue Superscalar Microprocessors

*     On-Chip Readout of Electrochemical Sensors: CMOS Potentiostats and Impedance Spectroscopy


Multi-function Microsystem for Electrochemical Biosensor Array

 

Text Box:  Description: An on-chip biosensor array CMOS microsystem provides a low-cost, high accuracy, and parallel measurement solution for biosensor detection and quantification. The goal of this project is to develop an integrated microsystem platform that incorporates a bio-interface array into a continuous-use, cost-effective, electrochemical characterization system suitable for DNA, protein, and enzyme detection and quantification. To achieve the benefits of this miniaturized microsystem, compact, ultra-low power and high sensitivity CMOS biosensor CMOS instrument circuits are extremely necessary. A multi-function readout circuit, stimulus signal generator and potentiostat blocks are integrated into one single chip.

 

 

Investigators: Xiaowen Liu


High Channel Count Neural Signal Processing

 

Text Box:  Description: This research thrust aims to develop a power-area efficient NSP capable of preserving useful neural data information while achieving a high compression rate. We have analyzed and applied techniques from signal detection theory and pattern recognition to neural signals, resulting in reliable spike-sorting algorithms which are robust to neural noise. Streaming digital hardware architectures have been developed with the goal of implementing these algorithms on-chip, enabling significant power and area savings without loss of sorting performance compared to existing NSPs. Statistical analysis on neural signals is now being performed to optimize design parameters and minimize hardware cost. Future research will focus on integrating a complete spike-sorting processing chain into a fully implantable VLSI architecture capable of processing a massive data from thousands of simultaneously recorded neurons.

 

 


Investigators
:
Yuning Yang


Low-noise low-power electrochemical instrumentation for wearable health monitoring of biological and chemical hazards

 

Text Box:  Description: In our modern global environment, pandemic diseases and air toxins present serious health hazards to worldwide populations. Although pandemic diseases and air toxins have global impact, the root causes are local phenomenon that can probably best be addressed by monitoring local environments experienced by individuals. However, traditional air toxin and disease agent sensing instruments are not suitable for individual use because of their large size, huge power consumption, lack of intelligence and high cost. Therefore, a smart personal hazard monitoring system is urgently needed to generate early danger alerts to individuals and pool all this local data to enable new means of population-level healthcare and disease control. Three generations of iEGAS have been built to study the system architecture and demonstrate the system function, cost, size and power consumption. A novel power efficient instrumentation circuit with high sensitivity and large dynamic range has been built for wearable chronoamperometric gas sensor arrays. This instrumentation combines an input digital modulation technique and a semi-synchronous incremental Σ∆ ADC structure. Measurement results demonstrate that 164 dB cross-scale dynamic range and 100 fA sensitivity are achieved by the instrumentation with 241 W power.

 

 

Investigators: Haitao Li


Automating and organizing data collection for electrochemical sensor arrays

 

Text Box:  Description: Employing electrochemical sensors to estimate the concentration of target compounds in real-world environments involves complex mixed-signal interrogation protocols and signal processing software. To make sense of the massive datasets and many confounding variables seen in these complex workflows, microsystem development researchers need better tools for methodical execution of experiments and differential analysis of results. We are developing a general-purpose software application to help address these organizational burdens, integrated with computer-controlled instrumentation hardware for automatically executing large volumes of electrochemical sensor experiments. We believe that this work will improve the reusability and reliability of sensor development research in many different fields.

 

 

Investigators: Sam Boling


Ionic liquid based Miniaturized Electrochemical Gas Sensor

 

Text Box:  Description: The growing potential impact of airborne pollutants and explosive gases on human health and occupational safety has escalated the demand for sensors to monitor hazardous gases. Current preventative measures and treatments for air toxins are ineffective due in large part of our inability to properly characterize and quantify acute exposure to air pollutants. To overcome these challenges both in environment and human health, the goal of this project is to develop a wearable autonomous multi-gas sensor system capable of real-time individual environmental monitoring which could provide immediate feedback to warn the wearer of imminent environmental threats as well as a record of individual exposure that would aid the development of new treatment approaches. To achieve this goal, sensors, electronics, and data analysis algorithms were synergistically integrated into an autonomous wearable system. The electrochemical sensors featuring room temperature ionic liquid are utilized for low-power operation, high sensitivity and selectivity, and long life with low maintenance. Electrodes Microfabrication on porous membrane process was developed to build up planar miniaturized electrodes; array technology was designed for multi-gas detection.

 

 




Investigators
:
Heyu Yin


Readout system for detection of plasmodium falciparum parasites

 

Text Box:  Description: Malaria is one of the most important infectious diseases in the world, with an estimated 216 million infections and 655,000 deaths in 2010. However, it is estimated that there are an equal number of undocumented deaths so the total annual death toll is more than 1.24 million. Efforts within the past decade have dramatically decreased disease burden in malaria-endemic countries; however, it is still one of the leading causes of morbidity and mortality in children under 5 years of age in Africa. This project tries to implement a system for automated, fast and reliable clinical detection of deadly Plasmodium falciparum malaria parasites. The system is intended to be usable by any individual with access to a smart phone with minimal technical knowledge. Hence, the test station can be moved deep into infected regions on a broad scale providing us with opportunity to reduce number of infections even lower. The system is composed of a low noise and low power consuming analog interface paired with a commercial DAC and ADC that are controlled by a microcontroller. The microcontroller is responsible for generating arbitrary waveform as well has passing massive amounts of data to the smartphone using USB 2.0. The device is powered
through the phone USB and requires no external power
source.

 

 

Investigators: Sina Parsnejad


Wearable microsystem for biomedical and environmental analysis for health and safety monitoring

 

Text Box:  Description: Monitoring the existing level of air pollutants is of high importance particularly for people who are working in especial environments such as mines and those who face chemicals in their daily works. Furthermore, using tiny sensors for collecting biological signals of a human body would help physicians to collect important health data from their patients. In such situations, a wearable microsystem with different nodes of sensors could be very helpful for health and safety issues. An important issue in wearable microsystems is the efficient communication between nodes as well as designing power efficient circuits. Seeking novel methods for networking between the nodes of sensors is the main direction of this work.

 

 

 








Investigators
:
Ehsan Ashoorie


Multi-function Microsystem for Electrochemical Biosensor Array

 

Text Box:  Description: An on-chip biosensor array CMOS microsystem provides a low-cost, high accuracy, and parallel measurement solution for biosensor detection and quantification. The goal of this project is to develop an integrated microsystem platform that incorporates a bio-interface array into a continuous-use, cost-effective, electrochemical characterization system suitable for DNA, protein, and enzyme detection and quantification. To achieve the benefits of this miniaturized microsystem, compact, ultra-low power and high sensitivity CMOS biosensor CMOS instrument circuits are extremely necessary. A multi-function readout circuit, stimulus signal generator and potentiostat blocks are integrated into one single chip.

 

 


Investigators
:
Xiaowen Liu

Monolithic gas sensor array for health and safety monitoringr

 

Description: The growing potential impact of airborne pollutants on personal health and safety has propelled the demand for hand-held sensor device to monitor hazardous gases. Miniaturization of a sensor system would gain benefits of low cost, low power, small size for such hand-held sensor device. This project aims to develop a new type of miniaturized gas sensor system that utilizes room temperature ionic liquid sensor and electrochemical instrumentation. A new sensor structure with electrodes on a permeable membrane has been developed to achieve rapid gas sensing response. A monolithic sensor-on-chip solution is now being explored to integrate both sensor arrays and instrumentation on a single chip and permits rapid sensing of hazardous gases.

 

Investigators: Xiaoyi Mu

 


Post CMOS fabrication for the integration of CMOS and electrochemical biosensors

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Description: The goal of this multidisciplinary project is to develop an integrated microsystem platform that incorporates a bio-interface array onto a CMOS of electrochemical circuitry that can perform the sensing and measurement in real time. Electrochemical techniques such as cyclic voltammetry (CV) and electrical impedance spectroscopy (EIS) are often employed to characterize biosensor interface properties. Such techniques can readily be implemented within CMOS instrumentation circuits. As part of electrochemical microsystem project, this project mainly focuses on the realization of on-chip electrochemical measurement. To achieve this goal, post-CMOS fabrication needs to be developed including 1) on-chip gold microelectrode array, 2) reliable test packaging scheme for experiments in liquid environment which requires electrical insulation, 3) novel packaging approach that can enable integration of microfluidic system. The challenge is to apply conventional MEMS fabrication techniques to the specific CMOS chip to meet all the requirements set by the biosensing application.

 

Investigators: Lin Li


 

Wearable Autonomous Microsystem with Electrochemical Gas Sensor Array for Real-Time Health and Safety Monitoring

 

Description: Exposure to air pollution consistently ranks among the leading global causes of illness and mortality, and explosive gases are an increasing threat to occupational safety as energy demands rise. Although there have been many important advances in gas sensor technologies, development of a wearable, autonomous multi-analyte gas sensor system remains an open challenge. We are designing a new system to meet the goals for environmental monitoring by integrating sensor arrays, electronics, and data analysis algorithms into a thumb-drive sized microsystem, called the intelligent electrochemical gas analysis system, or iEGAS. A novel electrochemical (EC) sensor array was under studied to improve selectivity and sensitivity. A novel multi-mode EC instrumentation chip (MEIC) provides stimulus signals for the EC sensor array and measures sensor response. A microcontroller (MCU) controls the system, analyzes data and generates alert signals to warn users of adverse conditions. A prototype iEGAS has been constructed which is able to read sensor data and upload it in real time to a PC for display and storage. For the next generation iEGAS, MEIC is under developement, and communications between MEIC, MCU and PC are setting up.

 

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Investigators: Haitao Li

 


Gas sensor array signal processing

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Description: An intelligent electrochemical gas analysis system is an instrument that is used to measure target gases in the air based on a gas sensor array. This project aims to develop a hardware efficient algorithm to estimate concentrations of individual gases within a real world mixture of gases. This project seeks to model the sensor array as a system of nonlinear equations and simultaneously identify and estimate concentration of target gases. A VLSI architecture is being designed to implement the algorithm for low power and potable application.

 

 

 

 

Investigators: Yuning Yang


 

A Neural Signal Processor for Wireless Implants

 

Text Box:  Description: This project aims to develop an implantable system-on-chip for compressing real-time neural data recorded from microelectrode arrays, permitting data from a large number of channels to be wirelessly transmitted to external processing units. The on-chip front-end signal processing and resulting compression must maintain the distinctive features in the shape of neural spikes to enable high-quality spike sorting at the receiver. The compression and transmission hardware must be power efficient to avoid heating tissue, and area efficient to facilitate surgical procedures. The proposed system contains analog, digital, and RF circuits. Neural signals are amplified and digitized before being transformed into time-frequency domain at the discrete wavelet transform (DWT) block. Lossy compression at the threshold block is followed by lossless compression in the run length encoder block. The compressed data and configuration commands are communicated over a bi-directional half-duplex wireless link to external processing units. The first iteration of the DWT block was fabricated in a 0.5μm CMOS process. The circuit supports 4 levels of wavelet decomposition and processes 32 neural data channels pseudo-simultaneously. A second generation that permits the number of channels recorded to be user determined has been designed in 0.13μm CMOS and optimized for low power operation. This project is supported by the National Institute of Health under award number 1R01NS062031.

 

Investigators: Awais M. Kamboh, Yuning Yang


 

Low power, low noise, multi-channel implanted neural interface circuit

Description: This project aims to build an interface circuit to detect the weak neural signal from human brain. The challenge is to achieve low power, low noise goal while consuming little chip area. The preamplifier performance is the most critical part of the system since it interfaces directly to V level neural signal from the electrodes. We have developed a preamplifier with transistors operating in sub-threshold region in 0.5m CMOS process. One SAR ADC is placed after 32 channels to convert the amplified, filtered analog signal into digital signal for further digitized processing. All the modules are built on a single chip.

 

Investigators: Haitao Li

 

 


 

Post CMOS fabrication for electrochemical measurement of biointerface

Description: With the completion of the Human Genome Project and the sequencing of several other scientifically important genomes, emphasis has shifted to determining the structure and function of the gene products, i.e., the proteins. The goal of this multidisciplinary project is to develop an integrated microsystem platform that incorporates a protein-based bio-interface array into a continuous-use, cost-effective, electrochemical characterization system suitable for functional proteomics research. As part of electrochemical microsystem array project this project focuses mainly on the the realization of on chip electrochemical measurement.To achieve this goal, post-CMOS fabrication needs to be developed including 1) on-chip gold microelectrode array, 2) reliable test packaging scheme for biotesting in liquid environment which requires electrical insulation and microfluidic system. The challenge is to apply conventional MEMS fabrication techniques to the specific CMOS chip for liquid environment measurement.

Investigators: Lin Li

 

 


 

Electrochemical Microsystem Array for Functional Proteomics

Description: With the completion of the Human Genome Project and the sequencing of several other scientifically important genomes, emphasis has shifted to determining the structure and function of the gene products, i.e., the proteins. The goal of this multidisciplinary project is to develop an integrated microsystem platform that incorporates a protein-based bio-interface array into a continuous-use, cost-effective, electrochemical characterization system suitable for functional proteomics research. To achieve this goal, we have synergistically explored several technical challenges including: 1) the development of novel nanostructured bio-interfaces appropriate for integration on the surface of a microelectronics chip, 2) the design of high performance integrated circuits for multiple electrochemical assays, 3) the design of circuits, structures, and packaging for on-chip thermal control of individual bio-interface sites, and 4) the development of microfabrication techniques enabling a miniaturized, multi-protein, array-on-chip platform that incorporates fluid handling. Electrode arrays on silicon have been fabricated and functionalized with nanostructured enzyme and membrane protein interfaces. A new multi-channel electrochemical impedance spectroscopy circuit, with on-chip AC stimulus generator, has been implemented and provides a resolution of ~100fA and current range up to 100nA Microhotplate arrays with thermal control circuitry has been realized in standard CMOS and verified to control the temperature of individual on-chip electrodes within the biological testing range. Several packaging options are now being explored to integrate all the elements of this microsystem platform and permit rapid functional characterization of a wide range of proteins.

Investigators: Xiaowen Liu, Lin Li


Chemiresistor Instrumentation

Description: Chemiresistors (CR) utilizing thiolate-monolayer-protected gold nanoparticles (MPN) as interfacial layers form highly sensitive vapor sensors useful for air quality monitoring, explosives detection, and breath analysis for health screening. All of these applications require compact and inexpensive instrumentation to realize their full potential. However, most CRs are currently being interrogated with large and expensive bench top instrumentation. Some chip-level solutions have been proposed for similar resistance based gas sensors, but those solutions do not posses the resolution required to make full use of the MPN CRs sensitivity. In addition, the CR posses a capacitive response which has not been fully explored, but may present additional information about the vapors being detected. This project aims to develop a system integrating the CR sensor itself and high resolution instrumentation on a single chip.

 

Investigators: Xiaoyi Mu and Daniel Rairigh


 

On-Chip Amperometric Readout of Electrochemical SensorsText Box:

 

Description: In order to realize chip-scale bioelectrochemical systems, this project seeks to develop integrated circuits that permit on-chip measurements using both electrochemical impedance spectroscopy (EIS) and cyclic voltammetry techniques. Our amperometric measurement approach utilizes a multi-function signal generator for voltage stimulus and a current readout circuit with sub-pA resolution. All circuits are implemented on a single chip, vastly reducing the system size for electrochemical analysis and enabling for multi-channel readout of electrochemical sensor arrays for a wide range of biological and chemical detection applications. A key feature of this effort is the development of a highly programmable signal generator that produces both AC excitations with a wide frequency range as well as constant and cyclic DC excitations, enhancing the capability and flexibility of the system.

 

Investigators: Waqar A. Qureshi, Liya Meng


 

AMSaC Mixed Signal Generic Test Board

Text Box:  Description: We have begun to develop a generic test board to verify the functions and to evaluate the performance of our chips. The goal of this project is to provide a platform for a broad variety of digital, analog and mixed signal chips. This board acts not only as an electrical interface between the device under test and the PC, but it also offers specific functionalities using different types of onboard ASICs. To achieve as much flexibility as possible, control signals and test stimuli are provided by a reprogrammable FPGA. In order to reduce the time and effort to access and process the data, a data acquisition card is used.

Investigators: Stefan Schorr

 


 

Highly Adaptive Multi-Sensor Readout and Communication Interface Circuits

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Description: As a legacy of prior work integrating multi-parameter microsystems, several generations of sensor interface circuits have been developed. Early versions demonstrated adaptability to different capacitive transducers. We then introduced a new sensor bus structure uniquely tailored to integrated microsystems with multiple intra-module sensor nodes. Utilizing this sensor bus, subsequently developed interface circuits provided a very high level of readout configurability and system flexibility. Our universal microsensor interface (UMSI) chip achieved unprecedented adaptability to many different sensor types and implemented numerous performance enhancing features, such as online recalibration and mixed-signal actuator control, not available in any other miniature, low-power, sensor interface circuit. We have also recently incorporated these ideas into a new system-on-chip (SoC) implementation with an embedded controller and a highly hardware-efficient sensor readout block. This chip has won two prizes in an SoC design contest sponsored by the Semiconductor Research Corporation, and is a finalist for Best Student Paper in the upcoming IEEE Sensors Conference.

 

Investigators: Chao Yang, Jichun Zhang, Junwei Zhou


 

image014Process-Scalable Optimization of Wide-Issue Superscalar Microprocessors

 

Description: Combining an understanding of circuit-level performance constraints with architectural-level high throughput structures, we have analyzed the design tradeoffs for wide-issue superscalar microprocessors as CMOS feature size shrinks in the submicron regime. We have identified several effective methods for decreasing delays in the processor instruction queue and designed circuits to significantly reduce processor delays with negligible performance loss. We have shown that our hardware banking/segmenting approach can be adapted to match performance characteristics of different wide-issue processors, enabling significant performance improvement for both single program and multi-program workloads.

 

Investigators: Chao Yang, Jichun Zhang, Junwei Zhou


 

On-Chip Readout of Electrochemical Sensors: CMOS Potentiostats and Text Box:  Impedance Spectroscopy

 

Description: In unison with the topic above, we have been developing the backbone circuitry necessary to realize miniature bioelectrochemical systems with on-chip measurement electronics. Utilizing state-of-the art mixed-signal integrated circuit techniques, we developed a high performance potentiostat that can resolve sub-picoampere currents, operate over six orders of magnitude in base current, and perform on-chip cyclic voltammetry on a sensor array. This circuit is currently being tested with electrochemical sensors for a journal paper to be submitted by Dec. 2006. Electrochemical impedance spectroscopy (EIS) is another important measurement technique for bio/chem-interfaces, but there are no existing chip-scale EIS solutions. We have analyzed several EIS techniques and evaluated their feasibility for on-chip implementation with biological and chemical sensors. We have created a new methodology and circuit to rapidly perform EIS in the low frequency range (invention disclosure filed), as necessary for many biosensors. With the proliferation of nano-technology sensors in recent years, we anticipate these chip-scale readout circuits, particularly EIS, to be critical for next generation sensory systems.

 

Investigators: Chao Yang.


 

Some of this material is based upon work supported by the National Science Foundation under Grant No. 0649847. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.


 

428 S. Shaw Lane, Rm 1522 517-432-3506
MSU, East Lansing amsac@egr.msu.edu

Michigan 48824

 

Advanced Microsystems and Circuits Research Group

Electrical and Computer Engineering, Michigan State University

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