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Biomedical Engineering, IEEE Transactions on

Issue 5 • Date May 2011

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Displaying Results 1 - 25 of 48
  • Table of contents

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

    Page(s): C2
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  • Table of contents

    Page(s): 1133 - 1134
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  • A Novel Method for the 3-D Reconstruction of Scoliotic Ribs From Frontal and Lateral Radiographs

    Page(s): 1135 - 1146
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (889 KB) |  | HTML iconHTML  

    Among the external manifestations of scoliosis, the rib hump, which is associated with the ribs' deformities and rotations, constitutes the most disturbing aspect of the scoliotic deformity for patients. A personalized 3-D model of the rib cage is important for a better evaluation of the deformity, and hence, a better treatment planning. A novel method for the 3-D reconstruction of the rib cage, based only on two standard radiographs, is proposed in this paper. For each rib, two points are extrapolated from the reconstructed spine, and three points are reconstructed by stereo radiography. The reconstruction is then refined using a surface approximation. The method was evaluated using clinical data of 13 patients with scoliosis. A comparison was conducted between the reconstructions obtained with the proposed method and those obtained by using a previous reconstruction method based on two frontal radiographs. A first comparison criterion was the distances between the reconstructed ribs and the surface topography of the trunk, considered as the reference modality. The correlation between ribs axial rotation and back surface rotation was also evaluated. The proposed method successfully reconstructed the ribs of the 6th-12th thoracic levels. The evaluation results showed that the 3-D configuration of the new rib reconstructions is more consistent with the surface topography and provides more accurate measurements of ribs axial rotation. View full abstract»

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  • Development of a Flexible System for Measuring Muscle Area Using Ultrasonography

    Page(s): 1147 - 1155
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (871 KB) |  | HTML iconHTML  

    Muscular strength can be estimated by quantification of muscle area. For this purpose, we developed a flexible measuring system for muscle area using ultrasonography. This method is completely safe and is particularly suitable for elderly people because the subjects are not required to perform any muscular contraction during measurement. The ultrasound probe is installed on a mechanical arm, and continuously scans fragmental images along the body surface. A wide-area cross-sectional image is then constructed using the measured images. The link mechanism is very flexible, enabling the operator to measure images for any body posture and body site. Use of the spatial compounding method reduces speckle and artifact noise in the resultant cross-sectional images. The operator can observe individual muscles (extensor, flexor muscle, etc.) in detail. We conducted experiments to evaluate the performance of the system. In the experiments, the position of the ultrasound probe was calculated with high accuracy according to the link posture. In addition, a high degree of correlation was verified between MR images and those of the developed system. We observed a reduction in noise due to use of the spatial compounding method, and propose a new calibration method for correcting the measured muscle area, which were slightly deformed by the contact pressure of the ultrasound probe. Finally, we examined the relation between muscular area and muscular strength in young and middle-aged subjects. The results of these experiments confirm that the developed system can estimate muscular strength based on muscular area. View full abstract»

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  • Automatic and Unsupervised Snore Sound Extraction From Respiratory Sound Signals

    Page(s): 1156 - 1162
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (356 KB) |  | HTML iconHTML  

    In this paper, an automatic and unsupervised snore detection algorithm is proposed. The respiratory sound signals of 30 patients with different levels of airway obstruction were recorded by two microphones: one placed over the trachea (the tracheal microphone), and the other was a freestanding microphone (the ambient microphone). All the recordings were done simultaneously with full-night polysomnography during sleep. The sound activity episodes were identified using the vertical box (V-Box) algorithm. The 500-Hz subband energy distribution and principal component analysis were used to extract discriminative features from sound episodes. An unsupervised fuzzy C-means clustering algorithm was then deployed to label the sound episodes as either snore or no-snore class, which could be breath sound, swallowing sound, or any other noise. The algorithm was evaluated using manual annotation of the sound signals. The overall accuracy of the proposed algorithm was found to be 98.6% for tracheal sounds recordings, and 93.1% for the sounds recorded by the ambient microphone. View full abstract»

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  • Detecting Spatial Variations of Erythrocytes by Ultrasound Backscattering Statistical Parameters Under Pulsatile Flow

    Page(s): 1163 - 1171
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1217 KB) |  | HTML iconHTML  

    The echogenicity of whole blood is known to vary during the flow cycle under pulsatile flow both in vitro and in vivo. However, the fundamental underlying mechanisms remain uncertain. The combined effects of flow acceleration and the shear rate were recently used to explain the cyclic variations of signals backscattered from flowing blood. However, testing this hypothesis requires determination of the spatial distributions of red blood cells (RBCs) in flowing blood. Recently, the Nakagami (m) and scaling (Ω) parameters have been used, respectively, to detect the spatial distributions of RBCs and the intensity of backscattering signal from blood under steady flow. For a better understanding of the relationship between the spatial distributions of RBCs and erythrocyte aggregation under pulsatile flow condition, these ultrasound backscattering statistical parameters were used, in this study, to characterize signals backscattered from both whole blood and RBC suspensions at different peak flow velocities (from 10 to 30 cm/s) and hematocrits (20% and 40%). The experiments were carried out by a 35-MHz ultrasound transducer. The m and Ω parameters were calculated for different blood properties and conditions, and the flow velocity in the center of blood flowing through a tube was measured synchronously. In whole blood, the results demonstrated that most RBCs were aggregated progressively toward the center of tube as the flow velocity started to accelerate, and that the increase in the intensity of the backscattered signal envelope to a maximum was attributable to larger rouleaux being formed in the center of tube. This phenomenon became apparent at a lower peak flow velocity with 40% hematocrit. However, there were no cyclic and spatial variations of the backscattering signal over a pulsatile cycle in RBC suspensions. View full abstract»

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  • Quantification of Restitution Dispersion From the Dynamic Changes of the T -Wave Peak to End, Measured at the Surface ECG

    Page(s): 1172 - 1182
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1097 KB) |  | HTML iconHTML  

    Action potential duration restitution (APDR) curves present spatial variations due to the electrophysiological heterogeneities present in the heart. Enhanced spatial APDR dispersion in ventricle has been suggested as an arrhythmic risk marker. In this study, we propose a method to noninvasively quantify dispersion of APDR slopes at tissue level by making only use of the surface electrocardiogram (ECG). The proposed estimate accounts for rate normalized differences in the steady-state T-wave peak to T-wave end interval (Tpe). A methodology is developed for its computation, which includes compensation for the Tpe memory lag after heart-rate (HR) changes. The capability of the proposed estimate to reflect APDR dispersion is assessed using a combination of ECG signal processing, and computational modeling and simulation. Specifically, ECG recordings of control subjects undergoing a tilt test trial are used to measure that estimate, while its capability to provide a quantification of APDR dispersion at tissue level is assessed by using a 2-D ventricular tissue simulation. From this simulation, APDR dispersion, denoted as ΔαSIM, is calculated, and pseudo-ECGs are derived. Estimates of APDR dispersion measured from the pseudo-ECGs show to correlate with ΔαSIM, being the mean relative error below 5%. A comparison of the ECG estimates obtained from tilt test recordings and the ΔαSIM values measured in silico simulations at tissue level show that differences between them are below 20%, which is within physiological variability limits. Our results provide evidence that the proposed estimate is a noninvasive measurement of APDR dispersion in ventricle. Additional results from this study confirm that Tpe adapts to HR changes much faster than the QT interval. View full abstract»

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  • Retinal Image Analysis Using Curvelet Transform and Multistructure Elements Morphology by Reconstruction

    Page(s): 1183 - 1192
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (902 KB) |  | HTML iconHTML  

    Retinal images can be used in several applications, such as ocular fundus operations as well as human recognition. Also, they play important roles in detection of some diseases in early stages, such as diabetes, which can be performed by comparison of the states of retinal blood vessels. Intrinsic characteristics of retinal images make the blood vessel detection process difficult. Here, we proposed a new algorithm to detect the retinal blood vessels effectively. Due to the high ability of the curvelet transform in representing the edges, modification of curvelet transform coefficients to enhance the retinal image edges better prepares the image for the segmentation part. The directionality feature of the multistructure elements method makes it an effective tool in edge detection. Hence, morphology operators using multistructure elements are applied to the enhanced image in order to find the retinal image ridges. Afterward, morphological operators by reconstruction eliminate the ridges not belonging to the vessel tree while trying to preserve the thin vessels unchanged. In order to increase the efficiency of the morphological operators by reconstruction, they were applied using multistructure elements. A simple thresholding method along with connected components analysis (CCA) indicates the remained ridges belonging to vessels. In order to utilize CCA more efficiently, we locally applied the CCA and length filtering instead of considering the whole image. Experimental results on a known database, DRIVE, and achieving to more than 94% accuracy in about 50 s for blood vessel detection, proved that the blood vessels can be effectively detected by applying our method on the retinal images. View full abstract»

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  • Laser Surface Estimation for Microwave Breast Imaging Systems

    Page(s): 1193 - 1199
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (636 KB) |  | HTML iconHTML  

    Microwave breast imaging techniques involve collecting measurements from a breast that is positioned in a scanner. While the patient interface typically includes a hole through which the breast is placed when the patient lies in the prone position, the exact location and shape of breast are not known. In this paper, we explore the addition of a laser sensor and associated algorithms in order to provide a rapid and accurate estimate of the breast surface location. We demonstrate that the laser is capable of estimating surfaces with improved accuracy compared to microwave measurements. The impact of accurate surface estimation on images is shown, and results obtained from human scans are presented. View full abstract»

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  • Novel Dry Polymer Foam Electrodes for Long-Term EEG Measurement

    Page(s): 1200 - 1207
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1135 KB) |  | HTML iconHTML  

    A novel dry foam-based electrode for long-term EEG measurement was proposed in this study. In general, the conventional wet electrodes are most frequently used for EEG measurement. However, they require skin preparation and conduction gels to reduce the skin-electrode contact impedance. The aforementioned procedures when wet electrodes were used usually make trouble to users easily. In order to overcome the aforesaid issues, a novel dry foam electrode, fabricated by electrically conductive polymer foam covered by a conductive fabric, was proposed. By using conductive fabric, which provides partly polarizable electric characteristic, our dry foam electrode exhibits both polarization and conductivity, and can be used to measure biopotentials without skin preparation and conduction gel. In addition, the foam substrate of our dry electrode allows a high geometric conformity between the electrode and irregular scalp surface to maintain low skin-electrode interface impedance, even under motion. The experimental results presented that the dry foam electrode performs better for long-term EEG measurement, and is practicable for daily life applications. View full abstract»

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  • Odor Discrimination Using Neural Decoding of the Main Olfactory Bulb in Rats

    Page(s): 1208 - 1215
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1210 KB) |  | HTML iconHTML  

    This paper presents a novel method for inferring the odor based on neural activities observed from rats' main olfactory bulbs. Multichannel extracellular single unit recordings were done by microwire electrodes (tungsten, 50 μm, 32 channels) implanted in the mitral/tufted cell layers of the main olfactory bulb of anesthetized rats to obtain neural responses to various odors. Neural response as a key feature was measured by subtraction of neural firing rate before stimulus from after. For odor inference, we have developed a decoding method based on the maximum likelihood estimation. The results have shown that the average decoding accuracy is about 100.0%, 96.0%, 84.0%, and 100.0% with four rats, respectively. View full abstract»

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  • Depth of Anesthesia During Multidrug Infusion: Separating the Effects of Propofol and Remifentanil Using the Spectral Features of EEG

    Page(s): 1216 - 1223
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (561 KB) |  | HTML iconHTML  

    General anesthesia is usually induced with a combination of drugs. In addition to the hypnotic agent, such as propofol, opioids are often used due to their synergistic hypnotic and analgesic properties. However, the effects of opioids on the EEG changes and the clinical state of the patient during anesthesia are complex and hinder the interpretation of the EEG-based depth of anesthesia indexes. In this paper, a novel technology for separating the anesthetic effects of propofol and an ultrashort-acting opioid, remifentanil, using the spectral features of EEG is proposed. By applying a floating search method, a well-performing feature set is achieved to estimate the effects of propofol during induction of anesthesia and to classify whether or not remifentanil has been coadministered. It is shown that including the detection of the presence of opioids to the estimated effect of propofol significantly improves the determination of the clinical state of the patient, i.e., if the patient will respond to a painful stimulation. View full abstract»

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  • Modified Kinematic Technique for Measuring Pathological Hyperextension and Hypermobility of the Interphalangeal Joints

    Page(s): 1224 - 1231
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (622 KB) |  | HTML iconHTML  

    Dynamic finger joint motion is difficult to measure using optical motion analysis techniques due to the limited surface area allowed for adequate marker placement. This paper describes an extension of a previously validated kinematic measurement technique using a reduced surface marker set and outlines the required calculations based on a specific surface marker placement to calculate flexion/extension and hyperextension of the metacarpophalangeal, proximal interphalangeal, and distal interphalangeal joints. The modified technique has been assessed for accuracy using a series of static reference frames (absolute residual error = ±3.7°, cross correlation between new method and reference frames; r = 0.99). The method was then applied to a small group of participants with rheumatoid arthritis (seven females, one male; mean age = 62.8 years ± 12.04) and illustrated congruent strategies of movement for a participant and a large range of finger joint movement over the sample (5.8-71.1°, smallest to largest active range of motion). This method used alongside the previous paper provides a comprehensive, validated method for calculating 3-D wrist, hand, fingers, and thumb kinematics to date and provides a valuable measurement tool for clinical research. View full abstract»

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  • Continuous Intra-Arterial Blood pH Monitoring by a Fiber-Optic Fluorosensor

    Page(s): 1232 - 1238
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (553 KB) |  | HTML iconHTML  

    Continuous intra-arterial blood pH monitoring is highly desirable in clinical practice. However, devices with appreciable accuracy are still not commercially available to date. In this study, we present a fiber-optic fluorosensor that can be used to continuously and accurately measure blood pH changes. The pH sensor is developed based on a proton-sensitive fluorescence dye, N-allyl-4-(4'-methyl-piperazinyl)-1,8-naphthalimide, which is bonded covalently to an optical fiber through heat polymerization. Fluorescence intensity was recorded after the sensor was exposed to different pH buffer solutions or intra-arterial blood in rabbits. Fluorescence intensity with emission peak at 510 nm decreased immediately as the blood pH increased. Linear and reproducible responses were observed when pH ranges from 6.8 to 8.0 with res olution of 0.03 pH units. The correlation coefficient between the pH sensor and the conventional blood gas analyzer was 0.93 in vivo (n = 75, p <; 0.001) with a bias and precision of -0.02 ± 0.08 pH units. The pH sensor was stable during measurement for at least 72 h. The pH sensor is not sensitive to fluctuations of vari ous ions' concentrations and plasma osmosis at pathophysiological limits, suggesting that it is useful for the continuous measurement of blood pH at various clinical settings. View full abstract»

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  • Subnanosecond Electric Pulses Cause Membrane Permeabilization and Cell Death

    Page(s): 1239 - 1245
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (517 KB) |  | HTML iconHTML  

    Subnanosecond electric pulses (200 ps) at electric field intensities on the order of 20 kV/cm cause the death of B16.F10 murine melanoma cells when applied for minutes with a pulse repetition rate of 10 kHz. The lethal effect of the ultrashort pulses is found to be caused by a combination of thermal effects and electrical effects. Studies on the cellular level show increased transport across the membrane at much lower exposure times or number of pulses. Exposed to 2000 pulses, NG108 cells exhibit an increase in membrane conductance, but only allow transmembrane currents to flow, if the medium is positively biased with respect to the cell interior. This means that the cell membrane behaves like a rectifying diode. This increase in membrane conductance is a nonthermal process, since the temperature rise due to the pulsing is negligible. View full abstract»

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  • Incremental Fuzzy Mining of Gene Expression Data for Gene Function Prediction

    Page(s): 1246 - 1252
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (321 KB) |  | HTML iconHTML  

    Due to the complexity of the underlying biological processes, gene expression data obtained from DNA microarray technologies are typically noisy and have very high dimensionality and these make the mining of such data for gene function prediction very difficult. To tackle these difficulties, we propose to use an incremental fuzzy mining technique called incremental fuzzy mining (IFM). By transforming quantitative expression values into linguistic terms, such as highly or lowly expressed, IFM can effectively capture heterogeneity in expression data for pattern discovery. It does so using a fuzzy measure to determine if interesting association patterns exist between the linguistic gene expression levels. Based on these patterns, IFM can make accurate gene function predictions and these predictions can be made in such a way that each gene can be allowed to belong to more than one functional class with different degrees of membership. Gene function prediction problem can be formulated both as classification and clustering problems, and IFM can be used either as a classification technique or together with existing clustering algorithms to improve the cluster groupings discovered for greater prediction accuracies. IFM is characterized also by its being an incremental data mining technique so that the discovered patterns can be continually refined based only on newly collected data without the need for retraining using the whole dataset. For performance evaluation, IFM has been tested with real expression datasets for both classification and clustering tasks. Experimental results show that it can effectively uncover hidden patterns for accurate gene function predictions. View full abstract»

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  • Modeling Nonsteady-State Metabolism From Arteriovenous Data

    Page(s): 1253 - 1259
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (482 KB) |  | HTML iconHTML  

    The use of arteriovenous (AV) concentration differences to measure the production of a substance at organ/tissue level by Fick principle is limited to steady state. Out of steady state, there is the need, as originally proposed by Zierler, to account for the nonnegligible transit time of the substance through the system. Based on this theory, we propose a modeling approach that adopts a parametric description for production and transit time. Once the unknown parameters are estimated on AV data, the transition time of the substance can be assessed and production can be reconstructed. As a case study, we discuss the estimation of pancreatic insulin secretion during a meal from C-peptide concentrations measured in femoral artery and hepatic vein in 12 subjects. Results support the importance of accounting for nonnegligible transit times, even if C-peptide mean transit time across the splanchnic bed is rather limited (3.3 ± 1.3 min), it affects the estimation of pancreatic insulin secretion which shows a significantly different profile in the early portion of the postprandial period when estimated either with the novel modeling approach or with the simplified steady state equation. View full abstract»

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  • Intervention in Biological Phenomena Modeled by S-Systems

    Page(s): 1260 - 1267
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (778 KB) |  | HTML iconHTML  

    Recent years have witnessed extensive research activity in modeling biological phenomena as well as in developing intervention strategies for such phenomena. S-systems, which offer a good compromise between accuracy and mathematical flexibility, are a promising framework for modeling the dynamical behavior of biological phenomena. In this paper, two different intervention strategies, namely direct and indirect, are proposed for the S-system model. In the indirect approach, the prespecified desired values for the target variables are used to compute the reference values for the control inputs, and two control algorithms, namely simple sampled-data control and model predictive control (MPC), are developed for transferring the control variables from their initial values to the computed reference ones. In the direct approach, a MPC algorithm is developed that directly guides the target variables to their desired values. The proposed intervention strategies are applied to the glycolytic-glycogenolytic pathway and the simulation results presented demonstrate the effectiveness of the proposed schemes. View full abstract»

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  • Triboelectricity in Capacitive Biopotential Measurements

    Page(s): 1268 - 1277
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (665 KB) |  | HTML iconHTML  

    Capacitive biopotential measurements suffer from strong motion artifacts, which may result in long time periods during which a reliable measurement is not possible. This study examines contact electrification and triboelectricity as possible reasons for these artifacts and discusses local triboelectric effects on the electrode-body interface as well as global electrostatic effects as common-mode interferences. It will be shown that most probably the triboelectric effects on the electrode-body interface are the main reason for artifacts, and a reduction of artifacts can only be achieved with a proper design of the electrode-body interface. For a deeper understanding of the observed effects, a mathematical model for triboelectric effects in highly isolated capacitive biopotential measurements is presented and verified with experiments. Based on these analyses of the triboelectric effects on the electrode-body interface, different electrode designs are developed and analyzed in order to minimize artifacts due to triboelectricity on the electrode-body interface. View full abstract»

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  • Head and Trunk Segment Moments of Inertia Estimation Using Angular Momentum Technique: Validity and Sensitivity Analysis

    Page(s): 1278 - 1285
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (330 KB) |  | HTML iconHTML  

    Classical models to estimate the head and trunk (HT) moments of inertia (I) are limited to populations from which the anthropometric measures were obtained. The purposes of this study were to determine if the angular momentum technique can be used to estimate subject-specific HT's I values and test its validity and sensitivity. Twenty-three adults who participated in this study were divided into three morphological groups according to their body mass index (BMI). Using the proposed technique, the HT's I values were estimated for the whole sample and compared to three well-known methods to test its validity. The sensitivity of the proposed method was verified while applied to individuals with different BMI (i.e., lean, normal, and obese). The angular momentum technique gave I values within the range of those of the three methods for the entire sample. Statistical differences were identified between the lean and obese groups in relative radii of gyration for the anteroposterior and mediolateral axes (P <; 0.05). Since the proposed technique makes no assumption on the mass distribution and segments' geometry, it appeared to be more sensitive to body morphology changes in estimating the HT's I values in lean and obese subjects compared to the classical methods. View full abstract»

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  • Modeling Cellular Lysis in Skeletal Muscle Due to Electric Shock

    Page(s): 1286 - 1293
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (823 KB) |  | HTML iconHTML  

    High-voltage electrical trauma frequently results in injury patterns that cannot be completely attributed to Joule heating. An electrical-injury model describing cellular lysis damage caused by supraphysiological electric fields is introduced, and used to evaluate the effects of high-voltage electric shock on the skeletal muscle of a human upper limb in a configuration that simulates hand-to-hand contact. A novel multiresolution admittance method, capable of efficiently handling large computational models while maintaining excellent accuracy, was used to perform the numerical computations. Values for the computed current through the arm and the upper limb impedance are reported. View full abstract»

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  • Microdosimetry for Nanosecond Pulsed Electric Field Applications: A Parametric Study for a Single Cell

    Page(s): 1294 - 1302
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    A microdosimetric study of nanosecond pulsed electric fields, including dielectric dispersivity of cell compartments, is proposed in our paper. A quasi-static solution based on the Laplace equation was adapted to wideband signals and used to address the problem of electric field estimation at cellular level. The electric solution was coupled with an asymptotic electroporation model able to predict membrane pore density. An initial result of our paper is the relevance of the dielectric dispersivity, providing evidence that both the transmembrane potential and the pore density are strongly influenced by the choice of modeling used. We note the crucial role played by the dielectric properties of the membrane that can greatly impact on the poration of the cell. This can partly explain the selective action reported on cancerous cells in mixed populations, if one considers that tumor cells may present different dielectric responses. Moreover, these kinds of studies can be useful to determine the appropriate setting of nsPEF generators as well as for the design and optimization of new-generation devices. View full abstract»

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  • Nonlinear Dynamic Modeling of Synaptically Driven Single Hippocampal Neuron Intracellular Activity

    Page(s): 1303 - 1313
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1075 KB) |  | HTML iconHTML  

    A high-order nonlinear dynamic model of the input-output properties of single hippocampal CA1 pyramidal neurons was developed based on synaptically driven intracellular activity. The purpose of this study is to construct a model that: 1) can capture the nonlinear dynamics of both subthreshold activities [postsynaptic potentials (PSPs)] and suprathreshold activities (action potentials) in a single formalism; 2) is sufficiently general to be applied to any spike-input and spike-output neurons (point process input and point process output neural systems); and 3) is computationally efficient. The model consisted of three major components: 1) feedforward kernels (up to third order) that transform presynaptic action potentials into PSPs; 2) a constant threshold, above which action potentials are generated; and 3) a feedback kernel (first order) that describes spike-triggered after-potentials. The model was applied to CA1 pyramidal cells, as they were electrically stimulated with broadband Poisson random impulse trains through the Schaffer collaterals. The random impulse trains used here have physiological properties similar to spiking patterns observed in CA3 hippocampal neurons. PSPs and action potentials were recorded from the soma of CA1 pyramidal neurons using whole-cell patch-clamp recording. We evaluated the model performance separately with respect to PSP waveforms and the occurrence of spikes. The average normalized mean square error of PSP prediction is 14.4%. The average spike prediction error rate is 18.8%. In summary, although prediction errors still could be reduced, the model successfully captures the majority of high-order nonlinear dynamics of the single-neuron intracellular activity. The model captures the general biophysical processes with a small set of open parameters that are directly constrained by the intracellular recording, and thus, can be easily applied to any spike-input and spike-output neuron. View full abstract»

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  • Rayleigh Mixture Model for Plaque Characterization in Intravascular Ultrasound

    Page(s): 1314 - 1324
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (858 KB) |  | HTML iconHTML  

    Vulnerable plaques are the major cause of carotid and coronary vascular problems, such as heart attack or stroke. A correct modeling of plaque echomorphology and composition can help the identification of such lesions. The Rayleigh distribution is widely used to describe (nearly) homogeneous areas in ultrasound images. Since plaques may contain tissues with heterogeneous regions, more complex distributions depending on multiple parameters are usually needed, such as Rice, K or Nakagami distributions. In such cases, the problem formulation becomes more complex, and the optimization procedure to estimate the plaque echomorphology is more difficult. Here, we propose to model the tissue echomorphology by means of a mixture of Rayleigh distributions, known as the Rayleigh mixture model (RMM). The problem formulation is still simple, but its ability to describe complex textural patterns is very powerful. In this paper, we present a method for the automatic estimation of the RMM mixture parameters by means of the expectation maximization algorithm, which aims at characterizing tissue echomorphology in ultrasound (US). The performance of the proposed model is evaluated with a database of in vitro intravascular US cases. We show that the mixture coefficients and Rayleigh parameters explicitly derived from the mixture model are able to accurately describe different plaque types and to significantly improve the characterization performance of an already existing methodology. 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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Meet Our Editors

Editor-in-Chief
Bin He
Department of Biomedical Engineering