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This page shows you the most recent publications within this specialty of the MedWorm directory. This is page number 22.

Blind Identification of Multi-Channel ARMA Models Based on Second-Order Statistics
This correspondence presents a new second-order statistical approach to blind identification of single-input multiple-output (SIMO) autoregressive and moving average (ARMA) system models. The proposed approach exploits the dynamical autoregressive information of the model contained in the autocorrelation matrices of the system outputs but does not require the block Toeplitz structure of the channel convolution matrix used by classical subspace methods. For the multi-channel model with the same autoregressive (AR) polynomial, sufficient conditions and an efficient identification algorithm are given such that the multi-chann...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Joint Source-Channel Coding and Channelization for Embedded Video Processing With Flash Memory Storage
This paper presents a joint source coding, channel coding, and flash memory channelization design framework to obtain optimized tradeoffs among energy consumption, bit rate, and end-to-end distortion (i.e., optimal E-R-D tradeoff space) for embedded and mobile devices with limited power source and abundant flash memory storage capacity. The optimal E-R-D tradeoff space enables embedded and mobile devices to cohesively optimize the source coding and data storage system operations subject to run-time power source, storage capacity, and/or distortion constraints. By treating flash memory as a communication channel, this work ...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Jointly Designed Architecture-Aware LDPC Convolutional Codes and Memory-Based Shuffled Decoder Architecture
In this paper, we jointly design architecture-aware (AA) low-density parity-check convolutional codes (LDPC-CCs) and the associated memory-based decoder architecture based on shuffled message-passing decoding (MPD). We propose a method for constructing AA-LDPC-CCs that can facilitate the design of a memory-based shuffled decoder using parallelization in both iteration and node dimensions. Through the use of shuffled MPD, the number of base processors and, hence, the decoder area is significantly reduced, since a fewer number of iterations is required in order to achieve a desired error performance. In addition, the use of ...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Joint Parameter Estimation and Base-Calling for Pyrosequencing Systems
Sequencing-by-synthesis technology takes us a step closer to the promises of personalized medicine by enabling affordable and fast DNA sequencing. Its accuracy, however, is fundamentally limited by the imperfections of the underlying biochemical processes and signal acquisition noise. In this paper, we focus on pyrosequencing systems, derive a mathematical model of the signal they acquire, and develop a joint parameter estimation and base-calling procedure which relies on Markov chain Monte Carlo (MCMC) and iterative least squares techniques. Simulations and experimental results demonstrate that the MCMC algorithm outperfo...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

A Joint Time-Invariant Filtering Approach to the Linear Gaussian Relay Problem
In this paper, the linear Gaussian relay problem is considered. Under the linear time-invariant (LTI) model the rate maximization problem in the linear Gaussian relay channel is formulated in the frequency domain based on the Toeplitz distribution theorem. Under the further assumption of realizable input spectra, the rate maximization problem is converted to the problem of joint source and relay filter design with two power constraints, one at the source and the other at the relay, and a practical solution to this problem is proposed based on the (adaptive) projected (sub)gradient method. Numerical results show that the pr...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Distributed, Robust Acoustic Source Localization in a Wireless Sensor Network
A distributed, robust source location estimation method using acoustic signatures in a wireless sensor network (WSN) is presented. A contaminated Gaussian (CG) noise model is proposed to characterize the impulsive, non-Gaussian nature of acoustic background noise observed in some real-world WSNs. A bi-square M-estimate approach then is applied to provide robust estimation of acoustic source locations in the presence of outlier. Moreover, a Consensus based Distributed Robust Acoustic Source Localization (C-DRASL) algorithm is proposed. With C-DRASL, individual sensor nodes will solve for the bi-square M-estimate of the sour...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Likelihood Consensus and Its Application to Distributed Particle Filtering
We consider distributed state estimation in a wireless sensor network without a fusion center. Each sensor performs a global estimation task—based on the past and current measurements of all sensors—using only local processing and local communications with its neighbors. In this estimation task, the joint (all-sensors) likelihood function (JLF) plays a central role as it epitomizes the measurements of all sensors. We propose a distributed method for computing, at each sensor, an approximation of the JLF by means of consensus algorithms. This “likelihood consensus” method is applicable if the loc...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Low-Complexity Distributed Total Least Squares Estimation in Ad Hoc Sensor Networks
Total least squares (TLS) estimation is a popular solution technique for overdetermined systems of linear equations with a noisy data matrix. In this paper, we revisit the distributed total least squares (D-TLS) algorithm, which operates in an ad hoc network, where each node has access to a subset of the linear equations. The D-TLS algorithm computes the TLS solution of the full system of equations in a fully distributed fashion (without fusion center). To reduce the large computational complexity due to an eigenvalue decomposition (EVD) at every node and in each iteration, we modify the D-TLS algorithm based on inverse po...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Distributed Detection Over Noisy Networks: Large Deviations Analysis
We study the large deviations performance of consensus+innovations distributed detection over noisy networks, where agents at a time step $k$ cooperate with their immediate neighbors (consensus) and assimilate their new observations (innovation.) We show that, under noisy communication, all agents can still achieve an exponential error rate, even when certain (or most) agents cannot detect the event of interest in isolation. The key to achieving this is the appropriate design of the time-varying weight sequence ${alpha_k=b_0/(a+k)}$ by which agents weigh their neighbors' messages. We find a communication payoff threshold o...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Diffusion Adaptation Strategies for Distributed Optimization and Learning Over Networks
We propose an adaptive diffusion mechanism to optimize global cost functions in a distributed manner over a network of nodes. The cost function is assumed to consist of a collection of individual components. Diffusion adaptation allows the nodes to cooperate and diffuse information in real-time; it also helps alleviate the effects of stochastic gradient noise and measurement noise through a continuous learning process. We analyze the mean-square-error performance of the algorithm in some detail, including its transient and steady-state behavior. We also apply the diffusion algorithm to two problems: distributed estimation ...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Interference Alignment as a Rank Constrained Rank Minimization
We show that the maximization of the sum degrees-of-freedom for the static flat-fading multiple-input multiple-output (MIMO) interference channel (IC) is equivalent to a rank constrained rank minimization problem (RCRM), when the signal subspaces span all available dimensions. The rank minimization corresponds to maximizing interference alignment (IA) so that interference spans the lowest dimensional subspace possible. The rank constraints account for the useful signal subspaces spanning all available spatial dimensions. That way, we reformulate the IA requirements to requirements involving ranks. Then, we present a convex...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Coordinated Linear Precoding in Downlink Multicell MIMO-OFDMA Networks
We consider coordinated linear precoding in downlink multicell multiple-input multiple-output orthogonal frequency-division multiple access (MIMO-OFDMA) systems, where multiple base stations (BSs) coordinate to mitigate the co-channel interference. Two nonconvex rate optimization problems with per-cell power constraints are addressed: weighted sum rate maximization (WSRM) and maximizing the weighted sum of the minimal user rates (MWSMR) of the coordinated cells. We propose two iterative algorithms to achieve suboptimal solutions for the WSRM problem. One attempts to solve the Karush-Kuhn-Tucker (KKT) conditions of the prob...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Tradeoff Analysis of Delay-Power-CSIT Quality of Dynamic Backpressure Algorithm for Energy Efficient OFDM Systems
In this paper, we analyze the fundamental power-delay tradeoff in point-to-point OFDM systems under imperfect channel state information quality and nonideal circuit power. We consider the dynamic backpressure (DBP) algorithm, where the transmitter determines the rate and power control actions based on the instantaneous channel state information (CSIT) and the queue state information (QSI). We exploit a general fluid queue dynamics using a continuous time dynamic equation. Using the sample-path approach and renewal theory, we decompose the average delay in terms of multiple unfinished works along a sample path, and derive a...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Nondata-Aided Joint Channel Estimation and Equalization for OFDM Systems in Very Rapidly Varying Mobile Channels
This paper is concerned with the challenging and timely problem of joint channel estimation and equalization for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and very rapidly time varying channels. The resulting algorithm is based on the space alternating generalized expectation maximization—maximum a posteriori probability (SAGE-MAP) technique which is particularly well suited to multicarrier signal formats. The algorithm is implemented in the time-domain which enables one to use the Gaussian approximation of the transmitted OFDM samples. Consequently, the averagi...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

SIMO Channel Estimation Using Space-Time Signal Subspace Projection and Soft Information
We consider the channel estimation of a time-slotted wireless communication system with a mobile user and a base station, where the base station employs an $M$-element $(M>1)$ antenna array. The uplink single-input multiple-output (SIMO) channel is usually estimated by training sequence within each time slot. To improve the estimation performance, the channel estimate is often refined by projecting it to the corresponding spatial signal subspace. However, this projection will not work when the number of resolvable multipath rays is larger than that of the antenna array elements, which makes the channel matrix full row rank...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

CS Decomposition Based Bayesian Subspace Estimation
In numerous applications, it is required to estimate the principal subspace of the data, possibly from a very limited number of samples. Additionally, it often occurs that some rough knowledge about this subspace is available and could be used to improve subspace estimation accuracy in this case. This is the problem we address herein and, in order to solve it, a Bayesian approach is proposed. The main idea consists of using the CS decomposition of the semi-orthogonal matrix ${bf H}$ whose columns span the subspace of interest. This parametrization is intuitively appealing and allows for non informative prior distributions ...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Performance Tradeoffs in Amplify-and-Forward Bidirectional Network Beamforming
We study and compare the performance of two bidirectional network beamforming schemes, namely the multiple access broadcast channel (MABC) strategy and the time division broadcast channel (TDBC) protocol, using joint optimal power control and beamforming design. To do so, we first design two TDBC-based bidirectional network beamformers, through minimization of the total power consumed in the whole network subject to quality of service (QoS) constraints, for the two cases with and without a direct link between the two transceivers. The corresponding power minimization problems are carried out over the transceiver transmit p...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

A CLT on the SNR of Diagonally Loaded MVDR Filters
This paper studies the fluctuations of the signal-to-noise ratio (SNR) of minimum variance distorsionless response (MVDR) filters implementing diagonal loading in the estimation of the covariance matrix. Previous results in the signal processing literature are generalized and extended by considering both spatially as well as temporarily correlated samples. Specifically, a central limit theorem (CLT) is established for the fluctuations of the SNR of the diagonally loaded MVDR filter, under both supervised and unsupervised training settings in adaptive filtering applications. Our second-order analysis is based on the Nash-Po...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Robust Clustering Using Outlier-Sparsity Regularization
Notwithstanding the popularity of conventional clustering algorithms such as K-means and probabilistic clustering, their clustering results are sensitive to the presence of outliers in the data. Even a few outliers can compromise the ability of these algorithms to identify meaningful hidden structures rendering their outcome unreliable. This paper develops robust clustering algorithms that not only aim to cluster the data, but also to identify the outliers. The novel approaches rely on the infrequent presence of outliers in the data, which translates to sparsity in a judiciously chosen domain. Leveraging sparsity in the ou...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Kernel Methods for Ill-Posed Range-Based Localization Problems
A kernel regression technique for the ill-posed range-based localization problem is proposed. We introduce a generic kernel design method which relies on a probabilistic modeling of the respective physical environment in terms of a class of stochastic differential equations. The combination of dynamic modeling with physical and stochastic interpretability leads to a unique solution in a Reproducing Kernel Hilbert Space and thus eliminates the need for a time-discrete representation of the localization solution. By design of the problem formulation, an extended Kalman filter naturally evolves as an iterative optimization me...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Feedback Message Passing for Inference in Gaussian Graphical Models
While loopy belief propagation (LBP) performs reasonably well for inference in some Gaussian graphical models with cycles, its performance is unsatisfactory for many others. In particular for some models LBP does not converge, and in general when it does converge, the computed variances are incorrect (except for cycle-free graphs for which belief propagation (BP) is non-iterative and exact). In this paper we propose feedback message passing (FMP), a message-passing algorithm that makes use of a special set of vertices (called a feedback vertex set or FVS) whose removal results in a cycle-free graph. In FMP, standard BP is ...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Sparsity-Exploiting Robust Multidimensional Scaling
Multidimensional scaling (MDS) seeks an embedding of $N$ objects in a $p< N$ dimensional space such that inter-vector distances approximate pairwise object dissimilarities. Despite their popularity, MDS algorithms are sensitive to outliers, yielding grossly erroneous embeddings even if few outliers contaminate the available dissimilarities. This work introduces robust MDS approaches exploiting the degree of sparsity in the outliers present. Links with compressive sampling lead to robust MDS solvers capable of coping with unstructured and structured outliers. The novel algorithms rely on a majorization-minimization appro...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Optimal Pivot Selection in Fast Weighted Median Search
Weighted median filters are increasingly being used in signal processing applications and thus fast implementations are of importance. This paper introduces a fast algorithm to compute the weighted median (WM) of $N$ samples which has linear time and space complexity as opposed to $O(N log N)$ which is the time complexity of traditional sorting algorithms. A popular selection algorithm often used to find the WM in large data sets is Quickselect whose performance is highly dependent on how the pivots are chosen. We introduce an optimization based pivot selection strategy which results in significantly improved performance a...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Block-Sparse Recovery via Convex Optimization
Given a dictionary that consists of multiple blocks and a signal that lives in the range space of only a few blocks, we study the problem of finding a block-sparse representation of the signal, i.e., a representation that uses the minimum number of blocks. Motivated by signal/image processing and computer vision applications, such as face recognition, we consider the block-sparse recovery problem in the case where the number of atoms in each block is arbitrary, possibly much larger than the dimension of the underlying subspace. To find a block-sparse representation of a signal, we propose two classes of nonconvex optimizat...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Proof of Convergence and Performance Analysis for Sparse Recovery via Zero-Point Attracting Projection
A recursive algorithm named zero-point attracting projection (ZAP) is proposed recently for sparse signal reconstruction. Compared with the reference algorithms, ZAP demonstrates rather good performance in recovery precision and robustness. However, any theoretical analysis about the mentioned algorithm, even a proof on its convergence, is not available. In this work, a strict proof on the convergence of ZAP is provided and the condition of convergence is put forward. Based on the theoretical analysis, it is further proved that ZAP is nonbiased and can approach the sparse solution to any extent, with the proper choice of s...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

STFT With Adaptive Window Width Based on the Chirp Rate
An adaptive time-frequency representation (TFR) with higher energy concentration usually requires higher complexity. Recently, a low-complexity adaptive short-time Fourier transform (ASTFT) based on the chirp rate has been proposed. To enhance the performance, this method is substantially modified in this paper: i) because the wavelet transform used for instantaneous frequency (IF) estimation is not signal-dependent, a low-complexity ASTFT based on a novel concentration measure is addressed; ii) in order to increase robustness to IF estimation error, the principal component analysis (PCA) replaces the difference operator f...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Discrete-Time LTI Systems Beyond Convolution
Examples for LTI systems are found in the literature that cannot be represented as a convolution. Their outputs can be approximated by outputs of FIR filters and considered as generalized convolution systems. These examples illustrate that impulse and frequency response provide no complete description of the system. In this paper, a general theory for discrete-time LTI systems is represented. LTI systems are defined on a signal space, which is a vector space, closed with respect to a shift operation. Signals are not necessarily bounded and need not belong to a normed vector space. Vector space concepts like dependent and i...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

On the Design of Highly Accurate and Efficient IIR and FIR Filters
We describe a systematic method for designing highly accurate and efficient infinite impulse response (IIR) and finite impulse response (FIR) filters given their specifications. In our approach, we first meet the specifications by constructing an IIR filter with, possibly, a large number of poles. We then construct, for any given accuracy, an optimal IIR version of such filter (with a minimal number of poles). Finally, also for any given accuracy, we convert the IIR filter to an efficient FIR filter cascade (either serial or parallel). Since in this FIR approximation the non-causal part of the IIR filter only introduces an...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Peak-Error-Constrained Sparse FIR Filter Design Using Iterative SOCP
In this paper, a novel algorithm is proposed to design sparse FIR filters. It is known that this design problem is highly nonconvex due to the existence of $l_{0}$ -norm of a filter coefficient vector in its objective function. To tackle this difficulty, an iterative procedure is developed to search a potential sparsity pattern, which is then used to compute the final solution by solving a convex optimization problem. In each iterative step, the original sparse filter design problem is successively transformed to a simpler subproblem. It can be proved that under a weak condition, globally optimal solutions of these subprob...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Spatio-Temporal Diffusion Strategies for Estimation and Detection Over Networks
We present diffusion algorithms for distributed estimation and detection over networks that endow all nodes with both spatial cooperation abilities and temporal processing abilities. Each node in the network is allowed to share information locally with its neighbors; this step amounts to sharing and processing of spatial data. At the same time, each node is allowed to filter and process past estimates to improve estimation accuracy through an overall collaborative process. In this manner, the resulting distributed algorithms consist of three stages: adaptation, spatial processing, and temporal processing. Moreover, the ord...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Adaptive Widely Linear Reduced-Rank Interference Suppression Based on the Multistage Wiener Filter
We propose a widely linear multistage Wiener filter (WL-MSWF) receiver to suppress inter-/intra-symbol interference, multiuser interference, and narrowband interference in a high data rate direct-sequence ultra wideband (DS-UWB) system. The proposed WL receiver fully exploits the second-order statistics of the received signal, yielding a smaller Minimum Mean Square Error (MMSE) than the linear receiver. The WL-MSWF receiver mainly consists of a low-rank transformation and an adaptive reduced-rank filter. The rank-reduction is achieved via a transformation matrix. Based on the linear MSWF concept, two constructions of this ...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Low-Complexity Variable Forgetting Factor Mechanism for Blind Adaptive Constrained Constant Modulus Algorithms
In this paper, we propose a novel low-complexity variable forgetting factor (VFF) mechanism for blind adaptive constrained constant modulus (CCM) recursive least squares (RLS) algorithms applied to linear interference suppression in direct-sequence code-division multiple access (DS-CDMA) systems. The proposed variable forgetting factor mechanism employs an updated component related to the time average of the constant modulus (CM) cost function to automatically adjust the forgetting factor in order to ensure good tracking of the interference and the channel. Convergence and tracking analyses are carried out. Analytical expr...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Recursive Group Lasso
We introduce a recursive adaptive group lasso algorithm for real-time penalized least squares prediction that produces a time sequence of optimal sparse predictor coefficient vectors. At each time index the proposed algorithm computes an exact update of the optimal $ell_{1,infty}$-penalized recursive least squares (RLS) predictor. Each update minimizes a convex but nondifferentiable function optimization problem. We develop an on-line homotopy method to reduce the computational complexity. Numerical simulations demonstrate that the proposed algorithm outperforms the $ell_{1}$ regularized RLS algorithm for a group sparse sy...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Sparse Bayesian Methods for Low-Rank Matrix Estimation
Recovery of low-rank matrices has recently seen significant activity in many areas of science and engineering, motivated by recent theoretical results for exact reconstruction guarantees and interesting practical applications. In this paper, we present novel recovery algorithms for estimating low-rank matrices in matrix completion and robust principal component analysis based on sparse Bayesian learning (SBL) principles. Starting from a matrix factorization formulation and enforcing the low-rank constraint in the estimates as a sparsity constraint, we develop an approach that is very effective in determining the correct ra...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

An Efficient Parametric Technique for Doppler-Delay Estimation
Receiving an output signal that is a weighted sum of Doppler and delay shifted versions of an input signal arises in various engineering systems including radar, sonar, and communications. It is often desired to estimate the Doppler and delay parameters from noisy measurements of the output signal. An estimation algorithm is developed herein for the Doppler frequencies, delays, and amplitudes, for a specific choice of the input. The algorithm is based on a computationally efficient search-free frequency estimation technique for the sum of complex exponentials. Asymptotic performance bounds are developed for the estimated p...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

A Semidefinite Relaxation-Based Algorithm for Robust Attitude Estimation
This paper presents a tractable method for solving a robust attitude estimation problem, based on a weighted least squares approach with nonlinear constraints. Attitude estimation requires information of a few vector quantities, each obtained from both a sensor and a mathematical model. By considering the modeling errors, measurement noise, sensor biases and offsets as infinity-norm bounded uncertainties, we formulate a robust optimization problem, which is nonconvex with nonlinear cost and constraints. The robust min-max problem is approximated with a nonconvex minimization problem using an upper bound. A new regularizati...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

SNR and Noise Variance Estimation for MIMO Systems
Accurate signal-to-noise ratio (SNR) and noise variance estimation are extremely important aspects of receiver design in multiple-input multiple-output (MIMO) systems. Typically, these parameters are estimated using known pilot/training symbols. However, significant improvements may be made by using both the known pilot symbols as well as the unknown data symbols. In this paper, we address SNR and noise variance estimation of MIMO systems for both a data aided (DA) model, a non-data aided (NDA) model, as well as a mixed model that uses known and unknown data symbols. The Cramér–Rao lower bound (CRLB) and modi...
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

IEEE Transactions on Signal Processing publication information
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

Table of contents
Presents the table of contents for this issue of the periodical.
Source: IEEE Transactions on Signal Processing - July 28, 2012 Category: Biomedical Engineering Source Type: research

IEEE Transactions on Biomedical Engineering Associate Editors
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research

IEEE Transactions on Biomedical Engineering information for authors
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research

Heterogeneity of Intrinsic Repolarization Properties Within the Human Heart: New Insights From Simulated Three-Dimensional Current Surfaces
Heterogeneity of repolarization properties is pivotal for both physiology and pathology of the heart and mathematical models of different cardiac cell types that are tuned to experimental data in order to reproduce it in silico. Repolarization heterogeneity is described most of the times with reference to one or the other of the many repolarization parameters, like action potential (AP) form and duration, or the maximum conductance of a given ion current, which are nonlinearly connected and frequently overdetermined. A compact representation of models dynamics would help their standardization, their use, and the understand...
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research

Mapping Infected Cell Phenotype
Quantitative modeling of the phenotypic changes in the host cell during the bacterial infection makes it possible to explore an empirical relation between the infection stages and the quantifiable host-cell phenotype. A statistically reliable model of this relation can facilitate therapeutic defense against threats due to natural and genetically engineered bacterium. In the preliminary experiment, we have collected several thousand cell images over a period of 72 h of infection with a 2-h sampling frequency that covers various stages of infection by Francisella tularenesis (Ft). Segmentation of macrophages in images...
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research

Variation of Respiratory Resistance Suggests Optimization of Airway Caliber
Physiologically optimized processes, such as respiration, walking, and cardiac function, usually show a range of variability about the optimized value. Airway resistance has, in the past, been noted as variable, and this variability has been connected to pulmonary disease (e.g., asthma). A hypothesis was presented many years ago that postulated airway resistance as an optimized parameter in healthy individuals, and we have noticed that respiratory measurements made with the airflow perturbation device (APD) tend to be variable in nature. It was posited that this variability indicates that respiratory resistance is optimize...
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research

Ex Vivo Measurement of Postmortem Tissue Changes in the Crystalline Lens by Brillouin Spectroscopy and Confocal Reflectance Microscopy
Use of Brillouin spectroscopy in ophthalmology enables noninvasive, spatially resolved determination of the rheological properties of crystalline lens tissue. Furthermore, the Brillouin shift correlates with the protein concentration inside the lens. In vitro measurements on extracted porcine lenses demonstrate that results obtained with Brillouin spectroscopy depend strongly on time after death. The intensity of the Brillouin signal decreases significantly as early as 5 h postmortem. Moreover, the fluctuation of the Brillouin frequency shift inside the lens increases with postmortem time. Images of lens tiss...
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research

An Optimization-Based Study of Equivalent Circuit Models for Representing Recordings at the Neuron–Electrode Interface
Extracellular neuroelectronic interfacing is an emerging field with important applications in the fields of neural prosthetics, biological computation, and biosensors. Traditionally, neuron–electrode interfaces have been modeled as linear point or area contact equivalent circuits but it is now being increasingly realized that such models cannot explain the shapes and magnitudes of the observed extracellular signals. Here, results were compared and contrasted from an unprecedented optimization-based study of the point contact models for an extracellular “on-cell” neuron–patch electrode and a plan...
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research

Biopsy Needle Localization Using Magnetic Induction Imaging Principles: A Feasibility Study
The accurate navigation and location of a biopsy needle is of main clinical interest in cases of image-guided biopsies for patients with suspected cancerous lesions. Magnetic induction (MI) imaging is a relatively new simple and low-cost noninvasive imaging modality that can be used for measuring the changes of electrical conductivity distribution inside a biological tissue. The feasibility of using MI principles for measuring and imaging the location of a biopsy needle in a tissue with suspected lesion was studied in simulations and with an experimental system. A contactless excitation/sensing unit was designed, and raste...
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research

Bioimpedance Analysis for the Characterization of Breast Cancer Cells in Suspension
The bioimpedance spectroscopy (BIS) technique is potentially a useful tool to differentiate malignancy based on the variation of electrical properties presented by different tissues and cells. The different tissues and cells present variant electrical resistance and reactance when excited at different frequencies. The main purpose of this area of research is to use impedance measurements over a low-frequency bandwidth ranging from 1 kHz to 3 MHz to 1) differentiate the pathological stages of cancer cells under laboratory conditions and 2) permit the extraction of electrical parameters related to cellular info...
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research

An Automatic Patient-Adapted ECG Heartbeat Classifier Allowing Expert Assistance
In this paper, we present a patient-adaptable algorithm for ECG heartbeat classification, based on a previously developed automatic classifier and a clustering algorithm. Both classifier and clustering algorithms include features from the RR interval series and morphology descriptors calculated from the wavelet transform. Integrating the decisions of both classifiers, the presented algorithm can work either automatically or with several degrees of assistance. The algorithm was comprehensively evaluated in several ECG databases for comparison purposes. Even in the fully automatic mode, the algorithm slightly improved the pe...
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research

Novel Passive Element Circuits for Microdosimetry of Nanosecond Pulsed Electric Fields
Microdosimetric models for biological cells have assumed increasing significance in the development of nanosecond pulsed electric field technology for medical applications. In this paper, novel passive element circuits, able to take into account the dielectric dispersion of the cell, are provided. The circuital analyses are performed on a set of input pulses classified in accordance with the current literature. Accurate data in terms of transmembrane potential are obtained in both time and frequency domains for different cell models. In addition, a sensitivity study of the transfer function for the cell geometrical and die...
Source: IEEE Transactions on Biomedical Engineering - July 28, 2012 Category: Biomedical Engineering Source Type: research