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Biomedical Engineering, IEEE Transactions on

Issue 2  Part 1 • Date Feb. 2008

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Displaying Results 1 - 25 of 56
  • [Front cover]

    Page(s): C1
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    Freely Available from IEEE
  • IEEE Transactions on Biomedical Engineering publication information

    Page(s): C2
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    Freely Available from IEEE
  • Table of contents

    Page(s): 385 - 387
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    Freely Available from IEEE
  • A Model for Idiopathic Intracranial Hypertension and Associated Pathological ICP Wave-Forms

    Page(s): 388 - 398
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (294 KB) |  | HTML iconHTML  

    Idiopathic intracranial hypertension (IIH) is a syndrome of unknown cause characterized by elevated intracranial pressure (ICP). While imaging often reveals a stenosis of the transverse sinuses, the role of this feature in IIH has been in dispute. Many patients with chronic daily headache have been found to actually be suffering from a milder form of IIH without papilledema (IIHWOP). These patients often demonstrate hypertensive B-waves and plateau-like waves upon continuous ICP monitoring. Recently, we presented modeling studies which suggest that the sinus stenosis and hypertension of IIH are physiological manifestations of a stable state of elevated pressures that exists when the transverse sinus is sufficiently collapsible. Many of the features of IIH were explained by this model but the prevalence of pathological ICP wave-forms observed in IIHWOP remained unresolved. The model presented here is a modified version of a previous model with a semi-collapsible sinus represented by a refined downstream Starling-like resistor based on experimental data. The qualitative behavior of this model is presented in terms of the collapsibility of the transverse sinus. For a sufficiently rigid sinus, there is a unique stable state of normal pressures. As the degree of collapsibility increases, there is a Hopf bifurcation, the normal state becomes unstable, low-frequency, high-amplitude ICP waves prevail, and small perturbations can lead to hypertensive ICP spikes. As the collapsibility increases further, so does the duration of the waves, until they are replaced by two stable states: one of normal pressures and one of elevated pressures. In this parameter domain, temporary perturbations can now cause permanent transitions between states. The model presented here retains the capability of our previous model to elucidate many features of IIH and additionally provides insight into the prevalence of the low-frequency, high-amplitude waves observed in IIHWOP. View full abstract»

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  • Preventive Ablation Strategies in a Biophysical Model of Atrial Fibrillation Based on Realistic Anatomical Data

    Page(s): 399 - 406
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1189 KB) |  | HTML iconHTML  

    Ablation strategies to prevent episodes of paroxysmal atrial fibrillation (AF) have been subject to many clinical studies. The issues mainly concern pattern and transmurality of the lesions. This paper investigates ten different ablation strategies on a multilayered 3-D anatomical model of the atria with respect to 23 different setups of AF initiation in a biophysical computer model. There were 495 simulations carried out showing that circumferential lesions around the pulmonary veins (PVs) yield the highest success rate if at least two additional linear lesions are carried out. The findings compare with clinical studies as well as with other computer simulations. The anatomy and the setup of ectopic beats play an important role in the initiation and maintenance of AF as well as the resulting therapy. The computer model presented in this paper is a suitable tool to investigate different ablation strategies. By including individual patient anatomy and electrophysiological measurement, the model could be parameterized to yield an effective tool for future investigation of tailored ablation strategies and their effects on atrial fibrillation. View full abstract»

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  • A Large-Scale, Energetic Model of Cardiovascular Homeostasis Predicts Dynamics of Arterial Pressure in Humans

    Page(s): 407 - 418
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1237 KB) |  | HTML iconHTML  

    The energetic balance of forces in the cardiovascular system is vital to the stability of blood flow to all physiological systems in mammals. Yet, a large-scale, theoretical model, summarizing the energetic balance of major forces in a single, mathematically closed system has not been described. Although a number of computer simulations have been successfully performed with the use of analog models, the analysis of energetic balance of forces in such models is obscured by a big number of interacting elements. Hence, the goal of our study was to develop a theoretical model that represents large-scale, energetic balance in the cardiovascular system, including the energies of arterial pressure wave, blood flow, and the smooth muscle tone of arterial walls. Because the emphasis of our study was on tracking beat-to-beat changes in the balance of forces, we used a simplified representation of the blood pressure wave as a trapezoidal pressure-pulse with a strong-discontinuity leading front. This allowed significant reduction in the number of required parameters. Our approach has been validated using theoretical analysis, and its accuracy has been confirmed experimentally. The model predicted the dynamics of arterial pressure in human subjects undergoing physiological tests and provided insights into the relationships between arterial pressure and pressure wave velocity. View full abstract»

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  • Performance Prediction of a Percutaneous Ventricular Assist System Using Nonlinear Circuit Analysis Techniques

    Page(s): 419 - 429
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1048 KB) |  | HTML iconHTML  

    A percutaneous ventricular assist device (pVAD) is an extracorporeal cardiac assist system that supports the failing ventricle in advanced stage heart failure by bypassing blood from the venous to the arterial circulation through a blood pump. The system can be implanted in a Cath lab using standard interventional techniques, and typically consists of a venous or atrial drainage cannula, the VAD (or blood pump), and an arterial perfusion cannula. Because the device allows clinicians the freedom of choosing the configuration and size of the cannulae based on the patient's body size and the size of the artery, it is extremely difficult but important to be able to predict the amount of blood flow that the device can provide before it is implanted to support the patient. In this paper, we develop a novel method that can be used to accurately predict the mean flow rate that the device can provide to the patient based on the size and configuration of the arterial cannula, the pump speed, and the patient's left atrial and mean arterial pressures. To do this, we first develop a nonlinear electric circuit model for the pVAD. This model includes a speed dependent voltage source and flow dependent resistors to simulate the pressure-flow relationship in the various cannulae in the device. We show that the flow rate through the device can be determined by solving a quadratic equation whose coefficients are scaled depending on the size and configuration of the arterial cannula. The model and prediction method were tested experimentally on a test loop supported by the TandemHeart pVAD (Cardiacassist, Inc., Pittsburgh, PA). A comparison of the predicted flow rates obtained from our method with experimental data shows that our method can predict the flow rates accurately with error indices less than 6% for all test conditions over the entire range of intended use of the device. Computer simulations of the pVAD model coupled to a cardiovascular model showed that the accuracy of the- - method in estimating the mean flow rate is consistent over the normal range of operation of the device regardless of the pulsatility introduced by the cardiovascular system. This method can be used as an additional too to assist cardiologists in choosing a proper arterial cannulae configurations and sizes for pVAD patients. It can also be used as a tool to train clinical personnel to operate the device under different physiological conditions. View full abstract»

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  • Estimating Effective Degrees of Freedom in Motor Systems

    Page(s): 430 - 442
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1511 KB) |  | HTML iconHTML  

    Studies of the degrees of freedom and "synergies" in musculoskeletal systems rely critically on algorithms to estimate the "dimension" of kinematic or neural data. Linear algorithms such as principal component analysis (PCA) are the most popular. However, many biological data (or realistic experimental data) may be better represented by nonlinear sets than linear subspaces. We evaluate the performance of PCA and compare it to two nonlinear algorithms [Isomap and our novel pointwise dimension estimation (PD-E)] using synthetic and motion capture data from a robotic arm with known kinematic dimensions, as well as motion capture data from human hands. We find that PCA can lead to more accurate dimension estimates when considering additional properties of the PCA residuals, instead of the dominant method of using a threshold of variance captured. In contrast to the single integer dimension estimates of PCA and Isomap, PD-E provides a distribution and range of estimates of fractal dimension that identify the heterogeneous geometric structure in the experimental data. A strength of the PD-E method is that it associates a distribution of dimensions to the data. Since there is no a priori reason to assume that the sets of interest have a single dimension, these distributions incorporate more information than a single summary statistic. Our preliminary findings suggest that fewer than ten DOFs are involved in some hand motion tasks. Contrary to common opinion regarding fractal dimension methods, PD-E yielded reasonable results with reasonable amounts of data. Given the complex nature of experimental and biological data, we conclude that it is necessary and feasible to complement PCA with methods that take into consideration the nonlinear properties of biological systems for a more robust estimation of their DOFs. View full abstract»

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  • A Time-Dependent Adaptive Remeshing for Electrical Waves of the Heart

    Page(s): 443 - 452
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2295 KB) |  | HTML iconHTML  

    In this work, a time-dependent remeshing strategy and a numerical method are presented for the simulation of the action potential propagation of the human heart. The main purpose of these simulations is to accurately predict the depolarization-repolarization front position, which is essential to the understanding of the electrical activity in the myocardium. A bidomain model, which is commonly used for studying electrophysiological waves in the cardiac tissue, will be employed for the numerical simulations. Numerical results are enhanced by the introduction of an anisotropic remeshing strategy. The illustration of the performance and the accuracy of the proposed method are presented using a 2-D analytical solution and a test case with re-entrant waves. View full abstract»

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  • Detection of Uterine MMG Contractions Using a Multiple Change Point Estimator and the K-Means Cluster Algorithm

    Page(s): 453 - 467
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2027 KB) |  | HTML iconHTML  

    We propose a single channel two-stage time-segment discriminator of uterine magnetomyogram (MMG) contractions during pregnancy. We assume that the preprocessed signals are piecewise stationary having distribution in a common family with a fixed number of parameters. Therefore, at the first stage, we propose a model-based segmentation procedure, which detects multiple change-points in the parameters of a piecewise constant time-varying autoregressive model using a robust formulation of the Schwarz information criterion (SIC) and a binary search approach. In particular, we propose a test statistic that depends on the SIC, derive its asymptotic distribution, and obtain closed-form optimal detection thresholds in the sense of the Neyman-Pearson criterion; therefore, we control the probability of false alarm and maximize the probability of change-point detection in each stage of the binary search algorithm. We compute and evaluate the relative energy variation [root mean squares (RMS)] and the dominant frequency component [first order zero crossing (FOZC)] in discriminating between time segments with and without contractions. The former consistently detects a time segment with contractions. Thus, at the second stage, we apply a nonsupervised K-means cluster algorithm to classify the detected time segments using the RMS values. We apply our detection algorithm to real MMG records obtained from ten patients admitted to the hospital for contractions with gestational ages between 31 and 40 weeks. We evaluate the performance of our detection algorithm in computing the detection and false alarm rate, respectively, using as a reference the patients' feedback. We also analyze the fusion of the decision signals from all the sensors as in the parallel distributed detection approach. View full abstract»

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  • QRS Slopes for Detection and Characterization of Myocardial Ischemia

    Page(s): 468 - 477
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (631 KB) |  | HTML iconHTML  

    In this study, the upward (IUS) and downward (IDS) slopes of the QRS complex are proposed as indices for quantifying ischemia-induced electrocardiogram (ECG) changes. Using ECG recordings acquired before and during percutaneous transluminal coronary angioplasty (PTCA), it is found that the QRS slopes are considerably less steep during artery occlusion, in particular for IDS. With respect to ischemia detection, the slope indices outperform the often used high-frequency index (defined as the root mean square (rms) of the bandpass-filtered QRS signal for the frequency band 150-250 Hz) as the mean relative factors of change are much larger for IUS and IDS than for the high-frequency index (6.9 and 7.3 versus 3.7). The superior performance of the slope indices is equally valid when other frequency bands of the high-frequency index are investigated (the optimum one is found to be 125-175 Hz). Employing a simulation model in which the slopes of a template QRS are altered by different techniques, it is found that the slope changes observed during PTCA are mostly due to a widening of the QRS complex or a decrease of its amplitudes, but not a reduction of its high-frequency content or a combination of this and the previous effects. It is concluded that QRS slope information can be used as an adjunct to the conventional ST segment analysis in the monitoring of myocardial ischemia. View full abstract»

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  • Analysis of First-Derivative Based QRS Detection Algorithms

    Page(s): 478 - 484
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (243 KB) |  | HTML iconHTML  

    Accurate QRS detection is an important first step for the analysis of heart rate variability. Algorithms based on the differentiated ECG are computationally efficient and hence ideal for real-time analysis of large datasets. Here, we analyze traditional first-derivative based squaring function (Hamilton-Tompkins) and Hilbert transform-based methods for QRS detection and their modifications with improved detection thresholds. On a standard ECG dataset, the Hamilton-Tompkins algorithm had the highest detection accuracy (99.68% sensitivity, 99.63% positive predictivity) but also the largest time error. The modified Hamilton-Tompkins algorithm as well as the Hilbert transform-based algorithms had comparable, though slightly lower, accuracy; yet these automated algorithms present an advantage for real-time applications by avoiding human intervention in threshold determination. The high accuracy of the Hilbert transform-based method compared to detection with the second derivative of the ECG is ascribable to its inherently uniform magnitude spectrum. For all algorithms, detection errors occurred mainly in beats with decreased signal slope, such as wide arrhythmic beats or attenuated beats. For best performance, a combination of the squaring function and Hilbert transform-based algorithms can be applied such that differences in detection will point to abnormalities in the signal that can be further analyzed. View full abstract»

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  • Analog CMOS Design for Optical Coherence Tomography Signal Detection and Processing

    Page(s): 485 - 489
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1050 KB) |  | HTML iconHTML  

    A CMOS circuit was designed and fabricated for optical coherence tomography (OCT) signal detection and processing. The circuit includes a photoreceiver, differential gain stage and lock-in amplifier based demodulator. The photoreceiver consists of a CMOS photodetector and low noise differential transimpedance amplifier which converts the optical interference signal into a voltage. The differential gain stage further amplifies the signal. The in-phase and quadrature channels of the lock-in amplifier each include an analog mixer and switched-capacitor low-pass filter with an external mixer reference signal. The interferogram envelope and phase can be extracted with this configuration, enabling Doppler OCT measurements. A sensitivity of -80 dB is achieved with faithful reproduction of the interferometric signal envelope. A sample image of finger tip is presented. View full abstract»

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  • Brain Source Localization Using a Fourth-Order Deflation Scheme

    Page(s): 490 - 501
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (885 KB) |  | HTML iconHTML  

    In this paper, a high-resolution method for solving potentially ill-posed inverse problems is proposed. This method named FO-D-MUSIC allows for localization of brain current sources with unconstrained orientations from surface electroencephalographic (EEG) or magnetoencephalographic (MEG) data using spherical or realistic head geometries. The FO-D-MUSIC method is based on the following: 1) the separability of the data transfer matrix as a function of location and orientation parameters, 2) the fourth-order (FO) virtual array theory, and 3) the deflation concept extended to FO statistics accounting for the presence of potentially but not completely statistically dependent sources. Computer results display the superiority of the FO-D-MUSIC approach in different situations (very closed sources, small number of electrodes, additive Gaussian noise with unknown spatial covariance, etc.) compared to classical algorithms. View full abstract»

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  • Frequency Tracking of Atrial Fibrillation Using Hidden Markov Models

    Page(s): 502 - 511
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (556 KB) |  | HTML iconHTML  

    A hidden Markov model (HMM) is employed to improve noise robustness when tracking the dominant frequency of atrial fibrillation (AF) in the electrocardiogram (ECG). Following QRST cancellation, a sequence of observed frequency states is obtained from the residual ECG, using the short-time Fourier transform. Based on the observed state sequence, the Viterbi algorithm retrieves the optimal state sequence by exploiting the state transition matrix, incorporating knowledge on AF characteristics, and the observation matrix, incorporating knowledge of the frequency estimation method and signal-to-noise ratio (SNR). The tracking method is evaluated with simulated AF signals to which noise, obtained from ECG recordings, has been added at different SNRs. The results show that the use of HMM improves performance considerably by reducing the rms error associated with frequency tracking: at 4-dB SNR, the rms error drops from 0.2 to 0.04 Hz. View full abstract»

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  • Principal Component Analysis-Enhanced Cosine Radial Basis Function Neural Network for Robust Epilepsy and Seizure Detection

    Page(s): 512 - 518
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (485 KB) |  | HTML iconHTML  

    A novel principal component analysis (PCA)-enhanced cosine radial basis function neural network classifier is presented. The two-stage classifier is integrated with the mixed-band wavelet-chaos methodology, developed earlier by the authors, for accurate and robust classification of electroencephalogram (EEGs) into healthy, ictal, and interictal EEGs. A nine-parameter mixed-band feature space discovered in previous research for effective EEG representation is used as input to the two-stage classifier. In the first stage, PCA is employed for feature enhancement. The rearrangement of the input space along the principal components of the data improves the classification accuracy of the cosine radial basis function neural network (RBFNN) employed in the second stage significantly. The classification accuracy and robustness of the classifier are validated by extensive parametric and sensitivity analysis. The new wavelet-chaos-neural network methodology yields high EEG classification accuracy (96.6%) and is quite robust to changes in training data with a low standard deviation of 1.4%. For epilepsy diagnosis, when only normal and interictal EEGs are considered, the classification accuracy of the proposed model is 99.3%. This statistic is especially remarkable because even the most highly trained neurologists do not appear to be able to detect interictal EEGs more than 80% of the times. View full abstract»

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  • Experimental System Prototype of a Portable, Low-Cost, C-Scan Ultrasound Imaging Device

    Page(s): 519 - 530
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5019 KB) |  | HTML iconHTML  

    A system prototype of a future compact, low-cost medical ultrasound device is described and presented with experimental results. The prototype system consists of a 32 x 32 element, fully sampled 2-D transducer array and a printed circuit board (PCB) containing 16 custom "front-end" receive channel integrated circuits (ICs) with analog multiplexing and programmable logic. A PC that included a commercially available data acquisition card is used for data collection and analysis. Beamforming is performed offline using the direct sampled in-phase/quadrature (DSIQ) algorithm. Pulse-echo images obtained with the prototype are presented. Results from this prototype support the feasibility of a low-cost, pocket-sized, C-scan imaging device. View full abstract»

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  • Three-Dimensional Electrical Impedance Tomography: A Topology Optimization Approach

    Page(s): 531 - 540
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1103 KB) |  | HTML iconHTML  

    Electrical impedance tomography is a technique to estimate the impedance distribution within a domain, based on measurements on its boundary. In other words, given the mathematical model of the domain, its geometry and boundary conditions, a nonlinear inverse problem of estimating the electric impedance distribution can be solved. Several impedance estimation algorithms have been proposed to solve this problem. In this paper, we present a three-dimensional algorithm, based on the topology optimization method, as an alternative. A sequence of linear programming problems, allowing for constraints, is solved utilizing this method. In each iteration, the finite element method provides the electric potential field within the model of the domain. An electrode model is also proposed (thus, increasing the accuracy of the finite element results). The algorithm is tested using numerically simulated data and also experimental data, and absolute resistivity values are obtained. These results, corresponding to phantoms with two different conductive materials, exhibit relatively well-defined boundaries between them, and show that this is a practical and potentially useful technique to be applied to monitor lung aeration, including the possibility of imaging a pneumothorax. View full abstract»

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  • Mosaicing of Bladder Endoscopic Image Sequences: Distortion Calibration and Registration Algorithm

    Page(s): 541 - 553
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2448 KB) |  | HTML iconHTML  

    Cancers located on the internal wall of bladders can be detected in image sequences acquired with endoscopes. The clinical diagnosis and follow-up can be facilitated by building a unique panoramic image of the bladder with the images acquired from different viewpoints. This process, called image mosaicing, consists of two steps. In the first step, consecutive images are pairwise registered to find the local transformation matrices linking geometrically consecutive images. In the second step, all images are placed in a common and global coordinate system. In this contribution, a mutual information-based similarity measure and a stochastic gradient optimization method were implemented in the registration process. However, the images have to be preprocessed in order to register the data in a robust way. Thus, a simple correction method of the distortions affecting endoscopic images is presented. After the placement of all images in the global coordinate system, the parameters of the local transformation matrices are all adjusted to improve the visual aspect of the panoramic images. Phantoms are used to evaluate the global mosaicing accuracy and the limits of the registration algorithm. The mean distances between ground truth positions in the mosaiced image range typically in 1-3 pixels. Results given for in vivo patient data illustrate the ability of the algorithm to give coherent panoramic images in the case of bladders. View full abstract»

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  • A Computational Investigation of Microwave Breast Imaging Using Deformable Reflector

    Page(s): 554 - 562
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1854 KB) |  | HTML iconHTML  

    In recent years, active microwave breast imaging is increasingly being viewed as a promising complementary imaging modality for cancer detection. In this paper, we present a novel deformable reflector microwave tomography technique for noninvasive characterization of the breast tissue. In contrast to conventional multitransceiver designs, the proposed technique utilizes a continuously deformable reflector with metallic coating to acquire field measurements for imaging. Computational feasibility of the proposed technique to image heterogeneous dielectric tissue property is evaluated using simplified 2-D breast models. The robustness of the deformable reflector-based tomography technique in imaging the spatial distribution of the tissue dielectric property in the presence of measurement noise is investigated using first-order Tikhonov regularization. Preliminary results obtained for the 2-D breast models appear promising and indicate further investigation of the new microwave tomography technique for breast imaging. View full abstract»

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  • Validation of Non-Rigid Registration Between Functional and Anatomical Magnetic Resonance Brain Images

    Page(s): 563 - 571
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1153 KB) |  | HTML iconHTML  

    This paper presents a set of validation procedures for nonrigid registration of functional EPI to anatomical MRI brain images. Although various registration techniques have been developed and validated for high-resolution anatomical MRI images, due to a lack of quantitative and qualitative validation procedures, the use of nonrigid registration between functional EPI and anatomical MRI images has not yet been deployed in neuroimaging studies. In this paper, the performance of a robust formulation of a nonrigid registration technique is evaluated in a quantitative manner based on simulated data and is further evaluated in a quantitative and qualitative manner based on in vivo data as compared to the commonly used rigid and affine registration techniques in the neuroimaging software packages. The nonrigid registration technique is formulated as a second-order constrained optimization problem using a free-form deformation model and mutual information similarity measure. Bound constraints, resolution level and cross-validation issues have been discussed to show the degree of accuracy and effectiveness of the nonrigid registration technique. The analyses performed reveal that the nonrigid approach provides a more accurate registration, in particular when the functional regions of interest lie in regions distorted by susceptibility artifacts. View full abstract»

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  • A Soft-Computing Methodology for Noninvasive Time-Spatial Temperature Estimation

    Page(s): 572 - 580
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (616 KB) |  | HTML iconHTML  

    The safe and effective application of thermal therapies is restricted due to lack of reliable noninvasive temperature estimators. In this paper, the temporal echo-shifts of backscattered ultrasound signals, collected from a gel-based phantom, were tracked and assigned with the past temperature values as radial basis functions neural networks input information. The phantom was heated using a piston-like therapeutic ultrasound transducer. The neural models were assigned to estimate the temperature at different intensities and points arranged across the therapeutic transducer radial line (60 mm apart from the transducer face). Model inputs, as well as the number of neurons were selected using the multiobjective genetic algorithm (MOGA). The best attained models present, in average, a maximum absolute error less than 0.5 C, which is pointed as the borderline between a reliable and an unreliable estimator in hyperthermia/diathermia. In order to test the spatial generalization capacity, the best models were tested using spatial points not yet assessed, and some of them presented a maximum absolute error inferior to 0.5 C, being ldquoelectedrdquo as the best models. It should be also stressed that these best models present implementational low-complexity, as desired for real-time applications. View full abstract»

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  • Development of an Implantable Pulse Oximeter

    Page(s): 581 - 588
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1229 KB) |  | HTML iconHTML  

    A long-term implantable photoplethysmographic sensor system is proposed. The system employs an elastic cuff which is directly wrapped around an arterial blood vessel. The optically transparent cuff is equipped with light emitting diodes and a photo transistor including the technology of pulse oximetry. The sensor will permit real-time, continuous monitoring of important vital parameters such as arterial blood oxygen saturation and pulse rate over a long-term period in vivo. We emphasize on the specific requirements for design and instrumentation of the implantable sensor and discuss first in vitro data acquired with that new photonics-based sensor. View full abstract»

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  • Electrical Characteristics of the Sparks Produced by Electrosurgical Devices

    Page(s): 589 - 593
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (679 KB) |  | HTML iconHTML  

    The electrical characteristics of the sparks produced between the active electrode and the biological tissue during electrosurgical procedures have been experimentally investigated. The results have shown that the minimum voltage required to initiate a spark depends on the applied voltage polarity resulting in electrosurgical voltage asymmetry. This voltage asymmetry is capable of producing DC levels that can result in tissue electrostimulation or direct current burns as discussed in this paper. The experimental setup and the conditions, under which the results have been obtained, including the techniques used to improve experimental reproducibility, are reported in detail. View full abstract»

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  • A New Geometric Factor for In Situ Resistivity Measurement Using Four Slender Cylindrical Electrodes

    Page(s): 594 - 602
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (874 KB) |  | HTML iconHTML  

    The four-electrode method is commonly used for in situ measurement of the electrical resistivity of biological tissues. In this paper, a new geometric factor between the resistivity and measured resistance using the four-electrode interface is derived in the prolate spheroidal coordinates and experimentally validated. Evaluation of the experimental results shows that the resistivities determined using both the derived geometric factor and a commercial conductivity meter are in close agreement even when the length of the immersed electrodes becomes long with respect to the inter-electrode spacing. The evaluation also shows the effect of the relative size of the sample volume when the limitation to semi-infinite volume begins to result in poor accuracy. 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.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Bin He
Department of Biomedical Engineering