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Biomedical Engineering, IEEE Transactions on

Issue 11 • Date Nov. 2001

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Displaying Results 1 - 15 of 15
  • The localization of spontaneous brain activity: an efficient way to analyze large data sets

    Page(s): 1221 - 1228
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    An efficient solution is presented of the problem to localize the electric generators of spontaneous magnetoencephalography (MEG) and electroencephalography (EEG) data for large data sets. When a data set contains more than 100,000 samples standard methods fail or become impractical. The method presented here is useful, for example, for the localization of (pathological) brain rhythms or the analysis of single-trial data. The problem is defined as finding the good fitting dipoles using the single-dipole model applied on each time sample. First, the data is bandpass filtered to select the rhythm of interest. Next, the empirical relationship between data power and probability of a dipole with a high goodness of fit (g.o.f.) is used to preselect data points. Then a global search algorithm is applied, based on precomputed lead fields on a fixed grid, to obtain a good initial guess for the nonlinear dipole search. Finally, the dipole search is applied on those samples that have a low initial guess error. In a group of five patients, it is found that 50% of the dipoles with a g.o.f. of at least 90% can be found by disregarding 90% of the data samples. Those dipoles can be found efficiently by disregarding all sample points with an initial guess relative residual error of 15% or lower. Finally, a simple empirical expression is found for the optimal mesh size of the global search grid. The method is completely automatic and makes it possible to study simple generators of large MEG and EEG data sets on a routine basis. View full abstract»

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  • A computer model of human atria with reasonable computation load and realistic anatomical properties

    Page(s): 1229 - 1237
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    Atrial fibrillation is the most frequent arrhythmia, provoking discomfort, heart failure and arterial embolisms. The aim of this work is to develop a simplified anatomical computer model of human atria for the study of atrial arrhythmias and the understanding of electrical propagation mechanisms. With the model the authors propose, up to 40 s of real-time propagation have been simulated on a single-processor computer. The size and the electrophysiological properties of the simulated atria are within realistic values and information about anatomy has been taken into account in a three-dimensional structure. Besides normal sinus beat, pathological phenomena such as flutter and fibrillation have been induced using a programmed stimulation protocol. One important observation in the authors' model is that atrial arrhythmias are a combination of functional and anatomical reentries and that the geometry plays an important role. This virtual atrium can reproduce electrophysiological observations made in humans but with the advantage of showing in great detail how arrhythmias are initiated and sustained. Such details are difficult or impossible to study in humans. This model will serve one as a tool to evaluate the impact of new therapeutic strategies and to improve them. View full abstract»

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  • The computational performance of a high-order coupled FEM/BEM procedure in electropotential problems

    Page(s): 1238 - 1250
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    Presents a thorough analysis of the computational performance of a coupled cubic Hermite boundary element/finite element procedure. This C 1 (i.e., value and derivative continuous) method has been developed specifically for electropotential problems, and has been previously applied to torso and skull problems. Here, the behavior of this new procedure is quantified by solving a number of dipole in spheres problems. A detailed set of results generated with a wide range of the various input parameters (such as dipole orientation, location, conductivity, and solution method used in each spherical shell [either finite element or boundary elements]) is presented. The new cubic Hermite boundary element procedure shows significantly better accuracy and convergence properties and a significant reduction in CPU time than a traditional boundary element procedure which uses linear or constant elements. Results using the high-order method are also compared with other computational methods which have had quantitative results published for electropotential problems. In all eases, the high-order method offered a significant improvement in computational efficiency by increasing the solution accuracy for the same, or fewer, solution degrees of freedom. View full abstract»

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  • Distortion properties of the interval spectrum of IPFM generated heartbeats for heart rate variability analysis

    Page(s): 1251 - 1264
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (416 KB) |  | HTML iconHTML  

    The integral pulse frequency modulation (IPFM) model converts a continuous-time signal into a modulated series of event times, often represented as a pulse train. The IPFM process is important to the field of heart rate variability (HRV) as a simple model of the sinus modulation of heart rate. Here, the authors discuss the distortion properties associated with employing the interval spectrum for the recovery of the input signal from an IPFM process's output pulse train. The results state, in particular for HRV, how precisely the interval spectrum can be used to infer the modulation signal responsible for a series of heartbeats. The authors have developed a detailed analytical approximation of the interval spectrum of an IPFM process with multiple sinusoids as the input signal. Employing this result, they describe the structure and the distortion of the interval spectrum. The distortion properties of the interval spectrum are investigated systematically for a pair of frequency components. The effects of linear and nonlinear distortion of the fundamentals, the overall contribution of harmonic components to the total power, the relative contribution of "folded back" power due to aliasing and the total distortion of the input spectrum are investigated. The authors also provide detailed comparisons between the interval spectrum and the spectrum of counts (SOC). The spectral distortion is significant enough that caution should be taken when interpreting the interval spectrum, especially for high frequencies or large modulation amplitudes. Nevertheless, the distortion levels are not significantly larger than those of the SOC. Therefore, the spectrum of intervals may be considered a viable technique that suffers more distortion than the SOC. View full abstract»

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  • Optimal filter-based detection of microcalcifications

    Page(s): 1272 - 1281
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    Deals with the problem of texture feature extraction in digital mammograms. The authors use the extracted features to discriminate between texture representing clusters of microcalcifications and texture representing normal tissue. Having a two-class problem, the authors suggest a texture feature extraction method based on a single filter optimized with respect to the Fisher criterion. The advantage of this criterion is that it uses both the feature mean and the feature variance to achieve good feature separation. Image compression is desirable to facilitate electronic transmission and storage of digitized mammograms. In this paper, the authors also explore the effects of data compression on the performance of their proposed detection scheme. The mammograms in their test set were compressed at different ratios using the Joint Photographic Experts Group compression method. Results from an experimental study indicate that the authors' scheme is very well suited for detecting clustered microcalcifications in both uncompressed and compressed mammograms. For the uncompressed mammograms, at a rate of 1.5 false positive clusters/image the authors' method reaches a true positive rate of about 95%, which is comparable to the best results achieved so far. The detection performance for images compressed by a factor of about four is very similar to the performance for uncompressed images. View full abstract»

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  • Entropy, entropy rate, and pattern classification as tools to typify complexity in short heart period variability series

    Page(s): 1282 - 1291
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    An integrated approach to the complexity analysis of short heart period variability series (∼300 cardiac beats) is proposed and applied to healthy subjects during the sympathetic activation induced by head-up tilt and during the driving action produced by controlled respiration (10, 15, and 20 breaths/min, CR10, CR15, and CR20 respectively). The approach relies on: 1) the calculation of Shannon entropy (SE) of the distribution of patterns lasting three beats; 2) the calculation of a regularity index based on an entropy rate (i.e., the conditional entropy); 3) the classification of frequent deterministic patterns (FDPs) lasting three beats. A redundancy reduction criterion is proposed to group FDPs in four categories according to the number and type or of heart period changes: a) no variation (0V); b) one variation (1V); and c) two like variations (2LV); 4) two unlike variations (2UV). The authors found that: 1) the SE decreased during tilt due to the increased percentage of missing patterns; 2) the regularity index increased during tilt and CR10 as patterns followed each other according to a more repetitive scheme; and 3) during CR10, SE and regularity index were not redundant as the regularity index significantly decreased while SE remained unchanged. Concerning pattern analysis the authors found that: a) at rest mainly three classes (0V, 1V, and 2LV) were detected; b) 0V patterns were more likely during tilt; c) 1V and 2LV patterns were more frequent during CR10; and d) 2UV patterns were more likely during CR20. The proposed approach based on quantification of complexity allows a full characterization of heart period dynamics and the identification of experimental conditions known to differently perturb cardiovascular regulation. View full abstract»

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  • Precise onset detection of human motor responses using a whitening filter and the log-likelihood-ratio test

    Page(s): 1292 - 1305
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (385 KB) |  | HTML iconHTML  

    Investigation of the human motor system frequently requires precise determination of the motor response onset indicating the time of movement initiation (e.g., in reaction time experiments). This paper presents a new model-based algorithm for computerized response onset detection in kinematic signals (e.g., joint angle). The response onset is identified as an abrupt change in the (time-varying) parameters of a statistical process model adapted to the measured signal. The accuracy of the algorithm is assessed by statistical simulations, and the performance of the method is compared to the performance of conventional onset detection methods using simulated as well as real kinematic signals. Results show that onset detection can substantially be improved by including a priori knowledge on the physiological background of the measured signals to the decision process. View full abstract»

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  • A sensor array processing approach to object region detection

    Page(s): 1319 - 1325
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    This paper presents a new approach for medical image analysis. It translates the object region-detection problem into a sensor array processing framework and detects the number of object regions based on the signal eigenstructure of the converted array system. The theoretical and experimental results obtained by using this approach on various medical images were in good agreement. View full abstract»

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  • Concentric-ring electrode systems for noninvasive detection of single motor unit activity

    Page(s): 1326 - 1334
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (218 KB) |  | HTML iconHTML  

    New recording techniques for detecting surface electromyographic (EMG) signals based on concentric-ring electrodes are proposed in this paper. A theoretical study of the two-dimensional (2-D) spatial transfer function of these recording systems is developed both in case of rings with a physical dimension and in case of line rings. Design criteria for the proposed systems are presented in relation to spatial selectivity. It is shown that, given the radii of the rings, the weights of the spatial filter can be selected in order to improve the rejection of low spatial frequencies, thus increasing spatial selectivity. The theoretical transfer functions of concentric systems are obtained and compared with those of other detection systems. Signals detected with the ring electrodes and with traditional one-dimensional and 2-D systems are compared. The concentric-ring systems show higher spatial selectivity with respect to the traditional detection systems and reduce the problem of electrode location since they are invariant to rotations. The results shown are very promising for the noninvasive detection of single motor unit (MU) activities and decomposition of the surface EMG signal into the constituent MU action potential trains. View full abstract»

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  • Nanoporous biocapsules for the encapsulation of insulinoma cells: biotransport and biocompatibility considerations

    Page(s): 1335 - 1341
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (121 KB) |  | HTML iconHTML  

    This study investigates whether nanoporous micromachined biocapsules, with uniform membrane pore sizes of 24.5-nm, can be used to encapsulate insulin-secreting cells in vitro. This approach to cell encapsulation is based on microfabrication technology whereby immunoisolation membranes are bulk and surface micromachined to present uniform and well-controlled pore sizes as small as 10 nm, tailored surface chemistries, and precise microarchitectures. This study evaluates the behavior of insulinoma cells with micromachined membranes, the effect of matrix configurations within the biocapsule on cell behavior, as well as insulin and glucose transport through the biocapsule membranes. View full abstract»

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  • Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability?

    Page(s): 1342 - 1347
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (132 KB) |  | HTML iconHTML  

    Heart rate variability (HRV) is concerned with the analysis of the intervals between heartbeats. An emerging analysis technique is the Poincare plot, which takes a sequence of intervals and plots each interval against the following interval. The geometry of this plot has been shown to distinguish between healthy and unhealthy subjects in clinical settings. The Poincare plot is a valuable HRV analysis technique due to its ability to display nonlinear aspects of the interval sequence. The problem is, how does one quantitatively characterize the plot to capture useful summary descriptors that are independent of existing HRV measures? Researchers have investigated a number of techniques: converting the two-dimensional plot into various one-dimensional views; the fitting of an ellipse to the plot shape; and measuring the correlation coefficient of the plot. The authors investigate each of these methods in detail and show that they are all measuring linear aspects of the intervals which existing HRV indexes already specify. The fact that these methods appear insensitive to the nonlinear characteristics of the intervals is an important finding because the Poincare plot is primarily a nonlinear technique. Therefore, further work is needed to determine if better methods of characterizing Poincare plot geometry can be found. View full abstract»

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  • Parametric modeling of somatosensory evoked potentials using discrete cosine transform

    Page(s): 1347 - 1351
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    This paper introduces a parametric method for identifying the somatosensory evoked potentials (SEPs). The identification was carried out by using pole-zero modeling of the SEPs in the discrete cosine transform (DCT) domain, It was found that the DCT coefficients of a monophasic signal can be sufficiently approximated by a second-order transfer function with a conjugate pole pair. The averaged SEP signal was modeled by the sum of several second-order transfer functions with appropriate zeros and poles estimated using the least square method in the DCT domain. Results of the estimation demonstrated that the model output was in an excellent agreement with the raw SEPs both qualitatively and quantitatively. Comparing with the common autoregressive model with exogenous input modeling in the time domain, the DCT domain modeling achieves a high goodness of fitting with a very low model order. Applications of the proposed method are possible in clinical practice for feature extraction, noise cancellation and individual component decomposition of the SEPs as well as other evoked potentials. View full abstract»

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  • Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method

    Page(s): 1352 - 1354
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    Reconstructing insulin secretion rate (ISR) after a glucose stimulus by deconvolution is difficult because of its biphasic pattern, i.e., a rapid secretion peak is followed by a slower release. Here, the authors refine a recently proposed stochastic deconvolution method by modeling ISR as the multiple integration of a white noise process with time-varying statistics. The unknown parameters are estimated from the data by employing a maximum likelihood criterion. A fast computational scheme implementing the method is presented. Monte Carlo simulation results are developed which numerically show a more reliable ISR profile reconstructed by the new method. View full abstract»

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  • Feature extraction of chromosomes from 3-D confocal microscope images

    Page(s): 1306 - 1318
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    An investigation of local energy surface detection integrated with neural network techniques for image segmentation is presented, as applied in the feature extraction of chromosomes from image datasets obtained using an experimental confocal microscope. Use of the confocal microscope enables biologists to observe dividing cells (living or preserved) within a three-dimensional (3-D) volume, that can be visualised from multiple aspects, allowing for increased structural insight. The Nomarski differential interference contrast mode used for imaging translucent specimens, such as chromosomes, produces images not suitable for volume rendering. Segmentation of the chromosomes from this data is, thus, necessary. A neural network based on competitive learning, known as Kohonen's self-organizing feature map (SOFM) was used to perform segmentation, using a collection of statistics or features defining the image. The authors' past investigation showed that standard features such as the localized mean and variance of pixel intensities provided reasonable extraction of objects such as mitotic chromosomes, but surface detail was only moderately resolved. In this current work, a biologically inspired feature known as local energy is investigated as an alternative image statistic based on phase congruency in the image. This, along with different combinations of other image statistics, is applied in a SOFM, producing 3-D images exhibiting vast improvement in the level of detail and clearly isolating the chromosomes from the background View full abstract»

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  • ECG beat recognition using fuzzy hybrid neural network

    Page(s): 1265 - 1271
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    Presents the application of the fuzzy neural network for electrocardiographic (ECG) beat recognition and classification. The new classification algorithm of the ECG beats, applying the fuzzy hybrid neural network and the features drawn from the higher order statistics has been proposed in the paper. The cumulants of the second, third, and fourth orders have been used for the feature selection. The hybrid fuzzy neural network applied in the solution consists of the fuzzy self-organizing subnetwork connected in cascade with the multilayer perceptron, working as the final classifier. The c-means and Gustafson-Kessel algorithms for the self-organization of the neural network have been applied. The results of experiments of recognition of different types of beats on the basis of the ECG waveforms have confirmed good efficiency of the proposed solution. The investigations show that the method may find practical application in the recognition and classification of different type heart beats View full abstract»

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Aims & Scope

IEEE Transactions on Biomedical Engineering contains basic and applied papers dealing with biomedical engineering. Papers range from engineering development in methods and techniques with biomedical applications to experimental and clinical investigations with engineering contributions.

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Editor-in-Chief
Bin He
Department of Biomedical Engineering