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Biomedical Engineering

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

Kernel Additive Models for Source Separation
Source separation consists of separating a signal into additive components. It is a topic of considerable interest with many applications that has gathered much attention recently. Here, we introduce a new framework for source separation called Kernel Additive Modelling, which is based on local regression and permits efficient separation of multidimensional and/or nonnegative and/or non-regularly sampled signals. The main idea of the method is to assume that a source at some location can be estimated using its values at other locations nearby, where nearness is defined through a source-specific proximity kernel. Such a ker...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Outage-Constrained Coordinated Beamforming With Opportunistic Interference Cancellation
In this paper, interference management is considered for the K-user multiple-input single-output (MISO) block-faded interference channel. It is assumed that perfect channel state information (CSI) can be obtained at the receivers, whereas only channel distribution information (CDI) is available to the transmitters. Furthermore, the receivers are assumed to be capable of implementing opportunistic interference cancellation (OIC). Based on these assumptions, the beamforming design problem for the MISO interference channel under consideration is formulated as a rate utility maximization problem under outage constraints and in...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

An MGF-Based Unified Framework to Determine the Joint Statistics of Partial Sums of Ordered i.n.d. Random Variables
The joint statistics of partial sums of ordered random variables (RVs) are often needed for the accurate performance characterization of a wide variety of wireless communication systems. A unified analytical framework to determine the joint statistics of partial sums of ordered independent and identically distributed (i.i.d.) random variables was recently presented. However, the identical distribution assumption may not be valid in several real-world applications. With this motivation in mind, we consider in this paper the more general case in which the random variables are independent but not necessarily identically distr...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

An Online Algorithm for Separating Sparse and Low-Dimensional Signal Sequences From Their Sum
This paper designs and extensively evaluates an online algorithm, called practical recursive projected compressive sensing (Prac-ReProCS), for recovering a time sequence of sparse vectors $S_{t}$ and a time sequence of dense vectors $L_{t}$ from their sum, $M_{t}:=S_{t}+L_{t}$, when the $L_{t}$ 's lie in a slowly changing low-dimensional subspace of the full space. A key application where this problem occurs is in real-time video layering where the goal is to separate a video sequence into a slowly changing background sequence and a sparse foreground sequence that consists of one or more moving regions/objects on-the-fly. ...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

A Primal-Dual Proximal Algorithm for Sparse Template-Based Adaptive Filtering: Application to Seismic Multiple Removal
Unveiling meaningful geophysical information from seismic data requires to deal with both random and structured “noises”. As their amplitude may be greater than signals of interest (primaries), additional prior information is especially important in performing efficient signal separation. We address here the problem of multiple reflections, caused by wave-field bouncing between layers. Since only approximate models of these phenomena are available, we propose a flexible framework for time-varying adaptive filtering of seismic signals, using sparse representations, based on inaccurate templates. We recast the ...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Blind Source Separation by Entropy Rate Minimization
By assuming latent sources are statistically independent, independent component analysis separates underlying sources from a given linear mixture. Since in many applications, latent sources are both non-Gaussian and have sample dependence, it is desirable to exploit both properties jointly. In this paper, we use mutual information rate to construct a general framework for analysis and derivation of algorithms that take both properties into account. We discuss two types of source models for entropy rate estimation—a Markovian and an invertible filter model—and give the general independent component analysis co...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Likelihood Estimators for Dependent Samples and Their Application to Order Detection
Estimation of the dimension of the signal subspace, or order detection, is one of the key issues in many signal processing problems. Information theoretic criteria are widely used to estimate the order under the independently and identically distributed (i.i.d.) sampling assumption. However, in many applications, the i.i.d. sampling assumption does not hold. Previous approaches address the dependent sample issue by downsampling the data set so that existing order detection methods can be used. By discarding data, the sample size is decreased causing degradation in the accuracy of the order estimation. In this paper, we int...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Optimal Index Policies for Anomaly Localization in Resource-Constrained Cyber Systems
The objective is a probing strategy that minimizes the total expected cost, incurred by all the components during the detection process, under reliability constraints. We consider both independent and exclusive models. In the former, each component can be abnormal with a certain probability independent of other components. In the latter, one and only one component is abnormal. We develop optimal index policies under both models. The proposed index policies apply to a more general case where a subset (more than one) of the components can be probed simultaneously. The problem under study also finds applications in spectrum s...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Sparse Recovery of Streaming Signals Using $ell_1$-Homotopy
Most of the existing sparse-recovery methods assume a static system: the signal is a finite-length vector for which a fixed set of measurements and sparse representation are available and an $ell_1$ problem is solved for the reconstruction. However, the same representation and reconstruction framework is not readily applicable in a streaming system: the signal changes over time, and it is measured and reconstructed sequentially over small intervals. This is particularly desired when dividing signals into disjoint blocks and processing each block separately is infeasible or inefficient. In this paper, we discuss two streami...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Bayesian Estimation of Clean Speech Spectral Coefficients Given a Priori Knowledge of the Phase
While most short-time discrete Fourier transform-based single-channel speech enhancement algorithms only modify the noisy spectral amplitude, in recent years the interest in phase processing has increased in the field. The goal of this paper is twofold. First, we derive Bayesian probability density functions and estimators for the clean speech phase when different amounts of prior knowledge about the speech and noise amplitudes is given. Second, we derive a joint Bayesian estimator of the clean speech amplitudes and phases, when uncertain a priori knowledge on the phase is available. Instrumental measures predict that by i...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Sum-Rate Maximization for Active Channels With Unequal Subchannel Noise Powers
In this paper, an active channel, between a source and a destination, refers to a parallel channel where the source transmits power over different subchannels as well as the powers of the subchannels can be adjusted. We herein study the sum-rate maximization for an active channel subject to two constraints, one on the source total transmit power and one on the total channel power. Although this maximization is not convex, we use Karush–Kuhn–Tucker (KKT) conditions to develop a computationally efficient algorithm for optimal source and channel power allocation. To do so, we first show how KKT conditions can be...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Efficient Hardware Architecture for Sparse Coding
Sparse coding encodes natural stimuli using a small number of basis functions known as receptive fields. In this work, we design custom hardware architectures for efficient and high-performance implementations of a sparse coding algorithm called the sparse and independent local network (SAILnet). A study of the neuron spiking dynamics uncovers important design considerations involving the neural network size, target firing rate, and neuron update step size. Optimal tuning of these parameters keeps the neuron spikes sparse and random to achieve the best image fidelity. We investigate practical hardware architectures for SAI...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Ramanujan Sums in the Context of Signal Processing—Part II: FIR Representations and Applications
The mathematician Ramanujan introduced a summation in 1918, now known as the Ramanujan sum $c_q(n)$ . In a companion paper (Part I), properties of Ramanujan sums were reviewed, and Ramanujan subspaces ${cal S}_q$ introduced, of which the Ramanujan sum is a member. In this paper, the problem of representing finite duration (FIR) signals based on Ramanujan sums and spaces is considered. First, it is shown that the traditional way to solve for the expansion coefficients in the Ramanujan-sum expansion does not work in the FIR case. Two solutions are then developed. The first one is based on a linear combination of the first $N...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Ramanujan Sums in the Context of Signal Processing—Part I: Fundamentals
The famous mathematician S. Ramanujan introduced a summation in 1918, now known as the Ramanujan sum $c_q(n)$ . For any fixed integer $q$ , this is a sequence in $n$ with periodicity $q$ . Ramanujan showed that many standard arithmetic functions in the theory of numbers, such as Euler’s totient function $phi(n)$ and the Möbius function $mu (n)$, can be expressed as linear combinations of $c_q(n), 1 leq q leq infty$. In the last ten years, Ramanujan sums have aroused some interest in signal processing. There is evidence that these sums can be used to extract periodic components in discrete-time signals. The pu...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Multitask Diffusion Adaptation Over Networks
Adaptive networks are suitable for decentralized inference tasks. Recent works have intensively studied distributed optimization problems in the case where the nodes have to estimate a single optimum parameter vector collaboratively. However, there are many important applications that are multitask-oriented in the sense that there are multiple optimum parameter vectors to be inferred simultaneously, in a collaborative manner, over the area covered by the network. In this paper, we employ diffusion strategies to develop distributed algorithms that address multitask problems by minimizing an appropriate mean-square error cri...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Deep Scattering Spectrum
A scattering transform defines a locally translation invariant representation which is stable to time-warping deformation. It extends MFCC representations by computing modulation spectrum coefficients of multiple orders, through cascades of wavelet convolutions and modulus operators. Second-order scattering coefficients characterize transient phenomena such as attacks and amplitude modulation. A frequency transposition invariant representation is obtained by applying a scattering transform along log-frequency. State-the-of-art classification results are obtained for musical genre and phone classification on GTZAN and TIMIT...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Compressive Shift Retrieval
The classical shift retrieval problem considers two signals in vector form that are related by a shift. This problem is of great importance in many applications and is typically solved by maximizing the cross-correlation between the two signals. Inspired by compressive sensing, in this paper, we seek to estimate the shift directly from compressed signals. We show that under certain conditions, the shift can be recovered using fewer samples and less computation compared to the classical setup. We also illustrate the concept of superresolution for shift retrieval. Of particular interest is shift estimation from Fourier coeff...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Relabeling and Summarizing Posterior Distributions in Signal Decomposition Problems When the Number of Components is Unknown
This paper addresses the problems of relabeling and summarizing posterior distributions that typically arise, in a Bayesian framework, when dealing with signal decomposition problems with an unknown number of components. Such posterior distributions are defined over union of subspaces of differing dimensionality and can be sampled from using modern Monte Carlo techniques, for instance, the increasingly popular RJ-MCMC method. No generic approach is available, however, to summarize the resulting variable-dimensional samples and extract from them component-specific parameters. We propose a novel approach, named Variable-dime...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Tomlinson–Harashima Precoding for Multiuser MIMO Systems With Quantized CSI Feedback and User Scheduling
This paper studies the sum rate performance of a low complexity quantized CSI-based Tomlinson–Harashima (TH) precoding scheme for downlink multiuser MIMO transmission, employing greedy user selection. The asymptotic distribution of the output-signal-to-interference-plus-noise ratio of each selected user and the asymptotic sum rate as the number of users $K$ grows large are derived by using extreme value theory. For fixed finite signal-to-noise ratios and a finite number of transmit antennas $n_{T}$ , we prove that as $K$ grows large, the proposed approach can achieve the optimal sum rate scaling of the MIMO broadcas...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Estimation of Amplitude, Phase and Unbalance Parameters in Three-phase Systems: Analytical Solutions, Efficient Implementation and Performance Analysis
This paper focuses on the estimation of the instantaneous amplitude, phase, and unbalance parameters in three-phase power systems. Due to the particular structure of three-phase systems, we demonstrate that the maximum-likelihood estimates (MLEs) of the unknown parameters have simple closed-form expressions and can be easily implemented without matrix algebra libraries. We also derive and analyze the Cramér–Rao Bounds (CRBs) for the considered estimation problem. The performance of the proposed approach is evaluated using synthetic signals compliant with the IEEE Standard C37.118. Simulation results show that...
Source: IEEE Transactions on Signal Processing - July 22, 2014 Category: Biomedical Engineering Source Type: research

Evaluating Environmental Education
Studies in Educational Evaluation, Volume 41, pages 1-142 (Jun-14) Edited by Jelle Boeve-de Pauw (Source: Elsevier Updates: Engineering)
Source: Elsevier Updates: Engineering - July 22, 2014 Category: Biomedical Engineering Source Type: news

Louisiana Tech University professor presents at International Bioprinting Congress
(Louisiana Tech University) Dr. Mark DeCoster, the James E. Wyche III Endowed Professor in Biomedical Engineering at Louisiana Tech University, will present 'Bioprinting interfaces for 2D and 3D cell and tissue models' focusing on the development of a novel, matrix-free method for generating 3D cell spheroids that are combining knowledge from bioprinting methods on 2D surfaces to link 3D cellular structures. (Source: EurekAlert! - Medicine and Health)
Source: EurekAlert! - Medicine and Health - July 21, 2014 Category: Global & Universal Source Type: news

Implementation of expert systems to support the functional evaluation of stand-to-sit activity
Conclusions: The developed expert systems can support the physiotherapist in evaluating stand-to-sit activity through a conclusion suggestion about the "level of inadequacy" for the "degree of inadequacy" searched during its execution. Results of experts' evaluation analyzed through statistical methods indicate that the automation of protocols contributed to the standardization of the evaluation of stand-to-sit activity and that it has application for teaching purposes. (Source: BioMedical Engineering OnLine)
Source: BioMedical Engineering OnLine - July 21, 2014 Category: Biomedical Engineering Authors: MaĆ­ra Junkes-CunhaGlauco CardozoChristine BoosFernando de Azevedo Source Type: research

Experimental study of PLLA/INH slow release implant fabricated by three dimensional printing technique and drug release characteristics in vitro
Conclusions: Three dimensional printing technique was a reliable technique to fabricate complicated implants. Drug release pattern in MDST was the most stable among the three implants. It was an ideal drug delivery system for the antibiotics. Biocompatibility tests demonstrated that the INH-PLLA implant did not have cytotoxicity. The multilayer donut-shaped tablet provided a new constant slow release method after an initial burst for the topical application of the antibiotic. (Source: BioMedical Engineering OnLine)
Source: BioMedical Engineering OnLine - July 19, 2014 Category: Biomedical Engineering Authors: Gui WuWeigang WuQixin ZhengJingfeng LiJianbo ZhouZhilei Hu Source Type: research

Towards the Asymptotic Sum Capacity of the MIMO Cellular Two-Way Relay Channel
In this paper, we consider the transceiver and relay design for the multiple-input multiple-output (MIMO) cellular two-way relay channel (cTWRC), where a multi-antenna base station (BS) exchanges information with multiple multiantenna mobile stations via a multi-antenna relay station (RS). We propose a novel two-way relaying scheme to approach the sum capacity of the MIMO cTWRC. A key contribution of this work is a new nonlinear lattice-based precoding technique to precompensate the interstream interference, so as to achieve efficient interference-free lattice decoding at the relay. We derive sufficient conditions for the ...
Source: IEEE Transactions on Signal Processing - July 18, 2014 Category: Biomedical Engineering Source Type: research

Distributed Hybrid Power State Estimation Under PMU Sampling Phase Errors
Phasor measurement units (PMUs) have the advantage of providing direct measurements of power states. However, as the number of PMUs in a power system is limited, the traditional supervisory control and data acquisition (SCADA) system cannot be replaced by the PMU-based system overnight. Therefore, hybrid power state estimation taking advantage of both systems is important. As experiments show that sampling phase errors among PMUs are inevitable in practical deployment, this paper proposes a distributed power state estimation algorithm under PMU phase errors. The proposed distributed algorithm only involves local computatio...
Source: IEEE Transactions on Signal Processing - July 18, 2014 Category: Biomedical Engineering Source Type: research

IEEE Transactions on Biomedical Engineering information for authors
Provides instructions and guidelines to prospective authors who wish to submit manuscripts. (Source: IEEE Transactions on Biomedical Engineering)
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research

IEEE Transactions on Industrial Electronics publication information
(Source: IEEE Transactions on Biomedical Engineering)
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research

Preoperative Discrimination of Benign from Malignant Disease in Thyroid Nodules With Indeterminate Cytology Using Elastic Light-Scattering Spectroscopy
We describe the results of a large, prospective, blinded study validating the ESS algorithm in patients with thyroid nodules. An ESS system was used to acquire spectra from human thyroid tissue. Spectroscopic results were compared to the histopathology of the biopsy samples. Sensitivity and specificity of the ESS system in the differentiation of benign from malignant thyroid nodules are 74% and 90% respectively, with a negative predictive value of 97%. These data suggest that ESS has the potential for use in real time diagnosis of thyroid nodules as an adjunct to FNAB cytology. (Source: IEEE Transactio...
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research

Microwave Stethoscope: Development and Benchmarking of a Vital Signs Sensor Using Computer-Controlled Phantoms and Human Studies
This paper describes a new microwave-based method and associated measurement system for monitoring multiple vital signs (VS) as well as the changes in lung water content. The measurement procedure utilizes a single microwave sensor for reflection coefficient measurements, hence the name “microwave stethoscope (MiSt),” as opposed to the two-sensor transmission method previously proposed by the authors. To compensate for the reduced sensitivity due to reflection coefficient measurements, an improved microwave sensor design with enhanced matching to the skin and broadband operation, as well as an advanced digita...
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research

Wavelet-Based Localization of Oscillatory Sources From Magnetoencephalography Data
This study is aimed at describing, evaluating, and illustrating with clinical data a new method for localizing the sources of oscillatory cortical activity recorded by MEG. The method combines time–frequency representation and an entropic regularization technique in a common framework, assuming that brain activity is sparse in time and space. Spatial sparsity relies on the assumption that brain activity is organized among cortical parcels. Sparsity in time is achieved by transposing the inverse problem in the wavelet representation, for both data and sources. We propose an estimator of the wavelet coefficients of th...
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research

Tumor Localization Using Magnetic Nanoparticle-Induced Acoustic Signals
Cancer is a major public health problem worldwide, especially in developed countries. Early detection of cancer can greatly increase both survival rates and quality of life for patients. A magnetoacoustic-based method had been previously proposed for early tumor detection, in a minimal invasive procedure, using magnetic nanoparticles (MNPs). This paper presents a supporting localization algorithm that can provide the clinician with essential tumor location data and could enable a sequential biopsy. It provides localization algorithm development, as well as its validation in both computerized simulations and in vitro experi...
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research

Analysis of Low-Dimensional Radio-Frequency Impedance-Based Cardio-Synchronous Waveforms for Biometric Authentication
Over the past two decades, there have been a lot of advances in the field of pattern analyses for biomedical signals, which have helped in both medical diagnoses and in furthering our understanding of the human body. A relatively recent area of interest is the utility of biomedical signals in the field of biometrics, i.e., for user identification. Seminal work in this domain has already been done using electrocardiograph (ECG) signals. In this paper, we discuss our ongoing work in using a relatively recent modality of biomedical signals—a cardio-synchronous waveform measured using a Radio-Frequency Impedance-Interro...
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research

Caenorhabditis Elegans Segmentation Using Texture-Based Models for Motility Phenotyping
With widening interests in using model organisms for reverse genetic approaches and biomimmetic microrobotics, motility phenotyping of the nematode Caenorhabditis elegans is expanding across a growing array of locomotive environments. One ongoing bottleneck lies in providing users with automatic nematode segmentations of C. elegans in image sequences featuring complex and dynamic visual cues, a first and necessary step prior to extracting motility phenotypes. Here, we propose to tackle such automatic segmentation challenges by introducing a novel texture factor model (TFM). Our approach revolves around the use of combined ...
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research

Spatiotemporal Representations of Rapid Visual Target Detection: A Single-Trial EEG Classification Algorithm
Brain computer interface applications, developed for both healthy and clinical populations, critically depend on decoding brain activity in single trials. The goal of the present study was to detect distinctive spatiotemporal brain patterns within a set of event related responses. We introduce a novel classification algorithm, the spatially weighted FLD-PCA (SWFP), which is based on a two-step linear classification of event-related responses, using fisher linear discriminant (FLD) classifier and principal component analysis (PCA) for dimensionality reduction. As a benchmark algorithm, we consider the hierarchical discrimin...
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research

Combining Motor Imagery With Selective Sensation Toward a Hybrid-Modality BCI
A hybrid modality brain-computer interface (BCI) is proposed in this paper, which combines motor imagery with selective sensation to enhance the discrimination between left and right mental tasks, e.g., the classification between left/ right stimulation sensation and right/ left motor imagery. In this paradigm, wearable vibrotactile rings are used to stimulate both the skin on both wrists. Subjects are required to perform the mental tasks according to the randomly presented cues (i.e., left hand motor imagery, right hand motor imagery, left stimulation sensation or right stimulation sensation). Two-way ANOVA statistical an...
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research

Reduction of Edge Effect on Disk Electrodes by Optimized Current Waveform
Rectangular pulses applied to disk electrodes result in high current density at the edges of the disk, which can lead to electrode corrosion and tissue damage. We explored a method for reducing current density and corrosion, by varying the leading edge of the current pulse. Finite-element modeling and mathematical analysis were used to predict an optimal waveform that reduces current density at the edge while also maintaining short pulse duration. An approximation of the optimized waveform was implemented experimentally and applied to platinum disk electrodes. Surface analysis using energy-dispersive spectroscopy showed si...
Source: IEEE Transactions on Biomedical Engineering - July 18, 2014 Category: Biomedical Engineering Source Type: research