Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Circuits and Systems I: Regular Papers, IEEE Transactions on

Issue 11 • Date Nov. 2006

Filter Results

Displaying Results 1 - 25 of 28
  • Table of contents

    Publication Year: 2006 , Page(s): C1 - C4
    Save to Project icon | Request Permissions | PDF file iconPDF (95 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Circuits and Systems—I: Regular Papers publication information

    Publication Year: 2006 , Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (36 KB)  
    Freely Available from IEEE
  • Special Issue on Advances in Life Science Systems and Applications: Guest Editorial

    Publication Year: 2006 , Page(s): 2345 - 2348
    Save to Project icon | Request Permissions | PDF file iconPDF (1128 KB) |  | HTML iconHTML  
    Freely Available from IEEE
  • A Bio-Inspired Ultra-Energy-Efficient Analog-to-Digital Converter for Biomedical Applications

    Publication Year: 2006 , Page(s): 2349 - 2356
    Cited by:  Papers (17)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1791 KB) |  | HTML iconHTML  

    There is an increasing trend in several biomedical applications such as pulse-oximetry, ECG, PCG, EEG, neural recording, temperature sensing, and blood pressure for signals to be sensed in small portable wireless devices. Analog-to-digital converters (ADCs) for such applications only need modest precision (les 8 bits) and modest speed (les 40 kHz) but need to be very energy efficient. ADCs for implanted medical devices need micropower operation to run on a small battery for decades. We present a bio-inspired ADC that uses successive integrate-and-fire operations like spiking neurons to perform analog-to-digital conversion on its input current. In a 0.18-mum subthreshold CMOS implementation, we were able to achieve 8 bits of differential nonlinearlity limited precision and 7.4 bits of thermal-noise-limited precision at a 45-kHz sample rate with a total power consumption of 960 nW. This converter's net energy efficiency of 0.12 pJ/quantization level appears to be the best reported so far. The converter is also very area efficient (<0.021 mm2) and can be used in applications that need several converters in parallel. Its algorithm allows easy generalization to higher speed applications through interleaving, to performing polynomial analog computations on its input before digitization, and to direct time-to-digital conversion of event-based cardiac or neural signals View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Multichannel Femtoampere-Sensitivity Potentiostat Array for Biosensing Applications

    Publication Year: 2006 , Page(s): 2357 - 2363
    Cited by:  Papers (33)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (769 KB) |  | HTML iconHTML  

    Rapid and accurate detection of pathogens using conductometric biosensors requires potentiostats that can measure small variations in conductance. In this paper, we present an architecture and implementation of a multichannel potentiostat array based on a novel semi-synchronous sigma-delta (SigmaDelta) analog-to-digital conversion algorithm. The algorithm combines continuous time SigmaDelta with time-encoding machines, and enables measurement of currents down to femtoampere range. A 3-mmtimes3-mm chip implementing a 42-channel potentiostat array has been prototyped in a 0.5-mum CMOS technology. Measured results demonstrate that the prototype can achieve 10 bits of resolution, with a sensitivity down to 50-fA current. The power consumption of the potentiostat has been measured to be 11 muW per channel for a sampling rate of 250 kHz. Experiments with a conductometric biosensor specific to Bacillus Cereus bacterium, demonstrate the ability of the potentiostat in identifying different concentration levels of the pathogen in a biological sample View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An Integrated Patch-Clamp Amplifier in Silicon-on-Sapphire CMOS

    Publication Year: 2006 , Page(s): 2364 - 2370
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1741 KB) |  | HTML iconHTML  

    We designed and tested an integrated patch-clamp amplifier capable of recording from pico to tens of microamperes of current. The high-dynamic range of seven decades and the picoampere sensitivity of the instrument was targeted to whole-cell patch-clamp recordings. The prototype was fabricated on a 0.5-mum silicon-on-sapphire process. The device employs an integrating headstage with a pulse frequency modulated output, ranging from 3 Hz to 10 MHz. A digital interface produces a 16-bit output conversion of the input currents. We report on electronic characterization of the fabricated device, dynamic performance, and examples of measurements on biological cells for patch-clamp applications. The device will be used in an advanced planar high-throughput patch-clamp screening system for testing medicines View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • 16-Channel Integrated Potentiostat for Distributed Neurochemical Sensing

    Publication Year: 2006 , Page(s): 2371 - 2376
    Cited by:  Papers (34)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1116 KB) |  | HTML iconHTML  

    We present the architecture and VLSI circuit implementation of a BiCMOS potentiostat bank for monitoring neurotransmitter concentration on a screen-printed carbon electrode array. The potentiostat performs simultaneous acquisition of bidirectional reduction-oxidation currents proportional to neurotransmitter concentration on 16 independent channels at controlled redox potentials. Programmable current gain control yields over 100-dB cross-scale dynamic range with 46-pA input-referred rms noise over 12-kHz bandwidth. The cutoff frequency of a second-order log-domain anti-aliasing filter ranges from 50 Hz to 400 kHz. Track-and-hold current integration is triggered at the sampling rate between dc and 200 kHz. A 2.25-mmtimes2.25-mm prototype was fabricated in a 1.2-mum VLSI technology and dissipates 12.5 mW. Chronoamperometry dopamine concentration measurements results are given. Other types of neurotransmitters can be selected by adjusting the redox potential on the electrodes and the surface properties of the sensor coating View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An Accurate DNA Sensing and Diagnosis Methodology Using Fabricated Silicon Nanopores

    Publication Year: 2006 , Page(s): 2377 - 2383
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (696 KB) |  | HTML iconHTML  

    Nanopore-based biomolecular sensing is an emerging nanotechnology which relies on the ability to measure changes in ionic conductance of single nanoscale pores as biomolecular analytes are driven through them, one at a time, by an applied electric field. Nanopores constructed from self-assembled proteins as well as using silicon-based fabrication techniques have been demonstrated to allow sizing and identification of DNA, RNA, proteins, and other biomolecules many times faster than with current technology. Despite the potential of nanopore sensing to produce "next generation" biomolecule analysis devices, its current demonstrations are based on the use of a simple dc stimulus across the nanopore. As a result, the resolution obtained is insufficient for many practical applications. In this paper, we report a novel diagnosis methodology for nanopore sensors based on optimization of a generalized electrical stimulus and a microscopic model of the biomolecule transport process. This methodology is applied to analyze the size distribution of an arbitrary mixture of DNA strands, which is a critical step in DNA sequencing. A transport model for long polymers in nanopores is built and parameterized to reproduce existing experimental data. The electrical stimulus is optimized "on-the-fly" using the model, to obtain a significant increase in the sizing resolution for any given range of DNA sizes and hence a clear identification of all sizes of DNA in the mixture. Hence, it is proposed that nanopore-based DNA sensing can be advanced significantly incurring no (or minimal) hardware overhead, by a combination of optimized stimuli and microscopic transport modeling View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A New Hand-Held Microsystem Architecture for Biological Analysis

    Publication Year: 2006 , Page(s): 2384 - 2395
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2926 KB) |  | HTML iconHTML  

    This paper presents a hand-held microsystem based on new fully integrated magnetoresistive biochips for biomolecular recognition (DNA hybridization, antibody antigen interaction, etc.). Magnetoresistive chip surfaces are chemically treated, enabling the immobilization of probe biomolecules such as DNA or antibodies. Fluid handling is also integrated in the biochip. The proposed microsystem not only integrates the biochip, which is an array of 16times16 magnetoresistive sensors, but it also provides all the electronic circuitry for addressing and reading out each transducer. The proposed architecture and circuits were specifically designed for achieving a compact, programmable and portable microsystem. The microsystem also integrates a hand-held analyzer connected through a wireless channel. A prototype of the system was already developed and detection of magnetic nanoparticles was obtained. This indicates that the system may be used for magnetic label based bioassays View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Absolute Temperature Monitoring Using RF Radiometry in the MRI Scanner

    Publication Year: 2006 , Page(s): 2396 - 2404
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2337 KB) |  | HTML iconHTML  

    Temperature detection using microwave radiometry has proven value for noninvasively measuring the absolute temperature of tissues inside the body. However, current clinical radiometers operate in the gigahertz range, which limits their depth of penetration. We have designed and built a noninvasive radiometer which operates at radio frequencies (64 MHz) with ~100-kHz bandwidth, using an external RF loop coil as a thermal detector. The core of the radiometer is an accurate impedance measurement and automatic matching circuit of 0.05 Omega accuracy to compensate for any load variations. The radiometer permits temperature measurements with accuracy of plusmn0.1degK, over a tested physiological range of 28degC-40 degC in saline phantoms whose electric properties match those of tissue. Because 1.5 T magnetic resonance imaging (MRI) scanners also operate at 64 MHz, we demonstrate the feasibility of integrating our radiometer with an MRI scanner to monitor RF power deposition and temperature dosimetry, obtaining coarse, spatially resolved, absolute thermal maps in the physiological range. We conclude that RF radiometry offers promise as a direct, noninvasive method of monitoring tissue heating during MRI studies and thereby providing an independent means of verifying patient-safe operation. Other potential applications include titration of hyper- and hypo-therapies View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Nuclei Segmentation Using Marker-Controlled Watershed, Tracking Using Mean-Shift, and Kalman Filter in Time-Lapse Microscopy

    Publication Year: 2006 , Page(s): 2405 - 2414
    Cited by:  Papers (35)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (938 KB) |  | HTML iconHTML  

    It is important to observe and study cancer cells' cycle progression in order to better understand drug effects on cancer cells. Time-lapse microscopy imaging serves as an important method to measure the cycle progression of individual cells in a large population. Since manual analysis is unreasonably time consuming for the large volumes of time-lapse image data, automated image analysis is proposed. Existing approaches dealing with time-lapse image data are rather limited and often give inaccurate analysis results, especially in segmenting and tracking individual cells in a cell population. In this paper, we present a new approach to segment and track cell nuclei in time-lapse fluorescence image sequence. First, we propose a novel marker-controlled watershed based on mathematical morphology, which can effectively segment clustered cells with less oversegmentation. To further segment undersegmented cells or to merge oversegmented cells, context information among neighboring frames is employed, which is proved to be an effective strategy. Then, we design a tracking method based on modified mean shift algorithm, in which several kernels with adaptive scale, shape, and direction are designed. Finally, we combine mean-shift and Kalman filter to achieve a more robust cell nuclei tracking method than existing ones. Experimental results show that our method can obtain 98.8% segmentation accuracy, 97.4% cell division tracking accuracy, and 97.6% cell tracking accuracy View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Automated Segmentation of Drosophila RNAi Fluorescence Cellular Images Using Deformable Models

    Publication Year: 2006 , Page(s): 2415 - 2424
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4036 KB) |  | HTML iconHTML  

    Image-based high-throughput genome-wide RNA interference (RNAi) experiments are increasingly carried out to facilitate the understanding of gene functions in intricate biological processes. Robust automated segmentation of the large volumes of output images generated from image-based screening is much needed for data analyses. In this paper, we propose a new automated segmentation technique to fill the void. The technique consists of two steps: nuclei and cytoplasm segmentation. In the former step, nuclei are extracted, labeled, and used as starting points for the latter step. A new force obtained from rough segmentation is introduced into the classical level set curve evolution to improve the performance for odd shapes, such as spiky or ruffly cells. A scheme of preventing curve intersection is proposed to treat the difficulty of segmenting touching cells. Synthetic images are generated to test the capabilities of our approach. Then, we apply it to three types of Drosophila cells in RNAi fluorescence images. In all cases, accuracy of greater than 92% is obtained View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Spectral Pattern Comparison Methods for Cancer Classification Based on Microarray Gene Expression Data

    Publication Year: 2006 , Page(s): 2425 - 2430
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB) |  | HTML iconHTML  

    We present, in this paper, two spectral pattern comparison methods for cancer classification using microarray gene expression data. The proposed methods are different from other current classifiers in the ways features are selected and pattern similarities measured. In addition, these spectral methods do not require any data preprocessing which is necessary for many other classification techniques. Experimental results using three popular microarray data sets demonstrate the robustness and effectiveness of the spectral pattern classifiers View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optimizing Consistency-Based Design of Context-Sensitive Gene Regulatory Networks

    Publication Year: 2006 , Page(s): 2431 - 2437
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (195 KB) |  | HTML iconHTML  

    When designing a gene regulatory network, except in rare circumstances there will be inconsistencies in the data. Modeling data inconsistencies fits naturally into the framework of probabilistic Boolean networks (PBNs). This model consists of a family of deterministic models and the overall model is based on random switching between constituent networks, each of which determines a context. A previous paper has proposed an inference procedure for PBNs to achieve data consistency within constituent networks. This paper proposes optimization methods targeted at two data-consistent design issues having to do with network structure: (1) generalization (namely, model selection) arising from the one-to-many mapping between the data set and PBN model; (2) model reduction under constraint on network connectivity, which is typically made for computational, statistical, or biological reasons. Regarding generalization, we combine connectivity and minimal logical realization to formulate the optimality criterion and propose two algorithms to solve it, the second algorithm guaranteeing a minimally connected PBN. Regarding constrained connectivity, we rephrase it as a lossy coding problem and develop an algorithm to find a best subset of predictors from the full set of predictors with the objective of minimizing probability of prediction error View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Gene Lethality Detection and Characterization via Topological Analysis of Regulatory Networks

    Publication Year: 2006 , Page(s): 2438 - 2443
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (601 KB) |  | HTML iconHTML  

    Recent engineering approaches to the analysis of biomolecular systems have shown a connection between the topological centrality of a protein in an interaction network and importance of that protein's underlying gene in the survival of the system. The recognized reason for this connection is the scale-free nature of these networks, which induces the presence of highly connected nodes (hubs) in the network. This approach would also be expected to identify these critical genes-called lethal because their removal would kill the cell- in the E. coli transcriptional regulation network, a prototypical scale-free network. However, this method does little better than simple random selection. Here we introduce a new approach, based on random walks, that identifies the critical nodes in the network on the basis of global properties of the network rather than the local connectivity of each node; we show that it significantly outperforms the standard local approach. We also find that lethal genes are more likely to belong to certain functional categories. The success of the our approach suggests that computational lethal gene detection can be effective and that scale free networks-and their biological instances-may enjoy more global properties than the one identified so far View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Designing Gene Regulatory Networks With Specified Functions

    Publication Year: 2006 , Page(s): 2444 - 2450
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (313 KB) |  | HTML iconHTML  

    To design and construct gene regulatory networks with specified functions, such as gene switches or gene oscillators, a precise mathematical description of the networks and their properties are developed from the viewpoint of integrated systems biology. The theoretical results provide insights into the modular structures of gene regulatory networks and their quantitative functions. Specifically, based on priori knowledge of the structure of functional modules, we use feedback system to create gene regulatory networks performing basic tasks. Two typical biological networks: positive and cyclic feedback networks are used to create functions as bistable switches or oscillators. The hybrid feedback networks are adopted to provide a variety of functional designs, which demonstrate the crucial role of interactions between biological modules View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Stability of Genetic Networks With SUM Regulatory Logic: Lur'e System and LMI Approach

    Publication Year: 2006 , Page(s): 2451 - 2458
    Cited by:  Papers (60)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (521 KB) |  | HTML iconHTML  

    In this paper, we present a nonlinear model for genetic regulatory networks with SUM regulatory functions. We show that the genetic network can be transformed into Lur'e form. Based on the Lyapunov method and the Lur'e system approach, sufficient conditions for the stability of the genetic networks are derived, in particular for the cases with time delays owing to the slow processes of transcription, translation, and translocation, and for the cases with stochastic perturbations due to natural random intra- and inter-cellular fluctuations. All the stability conditions are given in terms of linear matrix inequalities (LMIs), which are very easy to be verified. To test the effectiveness of our theoretical results, several examples of genetic networks are also presented in this paper View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Cycle-Averaged Models of Cardiovascular Dynamics

    Publication Year: 2006 , Page(s): 2459 - 2468
    Cited by:  Papers (3)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (714 KB) |  | HTML iconHTML  

    Lumped-parameter time-varying electrical circuit analogs for the cardiovascular system are frequently used in medical research and teaching for simulating and analyzing hemodynamic data. Pulsatile models provide details of the intracycle dynamics of each heart beat. In some settings, however, such as when tracking a hospital patient's hemodynamic state over time, it is more useful to dynamically track the beat-to-beat or intercycle dynamics. Rather than introducing heuristic averaging during the model-building step, as is done in existing nonpulsatile models, we apply a short-term, cycle-averaging operation to the differential equations of the underlying pulsatile model to obtain cycle-averaged models. The cycle-averaging method preserves the dependence of the output variables on the model parameters. In this paper, we apply cycle averaging to a simple pulsatile cardiovascular model to derive a cycle-averaged model for cardiovascular dynamics. The resultant model captures the intercycle dynamics with relatively small approximation errors for a large range of perturbations in important system parameters View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Adaptive EEG-Based Alertness Estimation System by Using ICA-Based Fuzzy Neural Networks

    Publication Year: 2006 , Page(s): 2469 - 2476
    Cited by:  Papers (25)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2094 KB) |  | HTML iconHTML  

    Drivers' fatigue has been implicated as a causal factor in many accidents. The development of human cognitive state monitoring system for the drivers to prevent accidents behind the steering wheel has become a major focus in the field of safety driving. It requires a technique that can continuously monitor and estimate the alertness level of drivers. The difficulties in developing such a system are lack of significant index for detecting drowsiness and the interference of the complicated noise in a realistic and dynamic driving environment. An adaptive alertness estimation methodology based on electroencephalogram, power spectrum analysis, independent component analysis (ICA), and fuzzy neural network (FNNs) models is proposed in this paper for continuously monitoring driver's drowsiness level with concurrent changes in the alertness level. A novel adaptive feature selection mechanism is developed for automatically selecting effective frequency bands of ICA components for realizing an on-line alertness monitoring system based on the correlation analysis between the time-frequency power spectra of ICA components and the driving errors defined as the deviation between the center of the vehicle and the cruising lane in the virtual-reality driving environment. The mechanism also provides effective and efficient features that can be fed into ICA-mixture-model-based self-constructing FNN to indirectly estimate driver's drowsiness level expressed by approximately and predicting the driving error View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • 2007 IEEE International Symposium on Circuits and Systems (ISCAS 2007)

    Publication Year: 2006 , Page(s): 2477
    Save to Project icon | Request Permissions | PDF file iconPDF (617 KB)  
    Freely Available from IEEE
  • 2007 International Conference on Multimedia & Expo (ICME)

    Publication Year: 2006 , Page(s): 2478
    Save to Project icon | Request Permissions | PDF file iconPDF (573 KB)  
    Freely Available from IEEE
  • IEEE Biomedical Circuits and Systems Conference healthcare technology (BioCAS 2006)

    Publication Year: 2006 , Page(s): 2479
    Save to Project icon | Request Permissions | PDF file iconPDF (248 KB)  
    Freely Available from IEEE
  • Special issue on systems biology

    Publication Year: 2006 , Page(s): 2480
    Save to Project icon | Request Permissions | PDF file iconPDF (146 KB)  
    Freely Available from IEEE
  • Special issue on multimedia data mining

    Publication Year: 2006 , Page(s): 2481
    Save to Project icon | Request Permissions | PDF file iconPDF (110 KB)  
    Freely Available from IEEE
  • Special issue on nanoelectronic circuits and nanoarchitectures

    Publication Year: 2006 , Page(s): 2482
    Save to Project icon | Request Permissions | PDF file iconPDF (168 KB)  
    Freely Available from IEEE

Aims & Scope

The theory, analysis, design, and practical implementations of circuits, and the application of circuit techniques to systems and to signal processing.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Shanthi Pavan
Indian Institute of Technology, Madras