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Biomedical Engineering, IEEE Transactions on

Issue 1 • Date Jan. 2012

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Displaying Results 1 - 25 of 48
  • Table of contents

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  • IEEE Transactions on Biomedical Engineering publication information

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  • Table of contents

    Page(s): 1 - 2
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  • Editorial: Introducing TBME Letters Special Section on Multiscale Biomedical Signal and Image Modeling and Analysis

    Page(s): 3
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  • Editorial: TBME Letters Special Section on Multiscale Biomedical Signal and Image Modeling and Analysis

    Page(s): 4 - 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (203 KB) |  | HTML iconHTML  

    The 11 papers in this special section focus on multiscale biomedical signal and image modeling and analysis. This issue is the third part dedicated to the topic. View full abstract»

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  • Multivariate Phase–Amplitude Cross-Frequency Coupling in Neurophysiological Signals

    Page(s): 8 - 11
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (518 KB) |  | HTML iconHTML  

    Phase-amplitude cross-frequency coupling (CFC)-where the phase of a low-frequency signal modulates the amplitude or power of a high-frequency signal-is a topic of increasing interest in neuroscience. However, existing methods of assessing CFC are inherently bivariate and cannot estimate CFC between more than two signals at a time. Given the increase in multielectrode recordings, this is a strong limitation. Furthermore, the phase coupling between multiple low-frequency signals is likely to produce a high rate of false positives when CFC is evaluated using bivariate methods. Here, we present a novel method for estimating the statistical dependence between one high-frequency signal and N low-frequency signals, termed multivariate phase-coupling estimation (PCE). Compared to bivariate methods, the PCE produces sparser estimates of CFC and can distinguish between direct and indirect coupling between neurophysiological signals-critical for accurately estimating coupling within multiscale brain networks. View full abstract»

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  • Adaptive Multiscale Entropy Analysis of Multivariate Neural Data

    Page(s): 12 - 15
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (309 KB) |  | HTML iconHTML  

    Multiscale entropy (MSE) has been widely used to quantify a system's complexity by taking into account the multiple time scales inherent in physiologic time series. The method, however, is biased toward the coarse scale, i.e., low-frequency components due to the progressive smoothing operations. In addition, the algorithm for extracting the different scales is not well adapted to nonlinear/nonstationary signals. In this letter, we introduce adaptive multiscale entropy (AME) measures in which the scales are adaptively derived directly from the data by virtue of recently developed multivariate empirical mode decomposition. Depending on the consecutive removal of low-frequency or high-frequency components, our AME can be estimated at either coarse-to-fine or fine-to-coarse scales over which the sample entropy is performed. Computer simulations are performed to verify the effectiveness of AME for analysis of the highly nonstationary data. Local field potentials collected from the visual cortex of macaque monkey while performing a generalized flash suppression task are used as an example to demonstrate the usefulness of our AME approach to reveal the underlying dynamics in complex neural data. View full abstract»

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  • Multiscale Modeling and Simulation of the Cardiac Fiber Architecture for DMRI

    Page(s): 16 - 19
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (470 KB) |  | HTML iconHTML  

    Cardiac fiber architecture plays an important role in the study of mechanical and electrical properties of the wall of the human heart, but still remains to be elucidated. This paper proposes to investigate, in a multiscale manner, how the arrangement patterns and morphological heterogeneity of cardiac myocytes influence the fibers orientation. To this end, different virtual cardiac fiber structures are modeled, and diffusion tensor imaging at multiple scales are simulated using the Monte Carlo method. The results show that the proposed modeling and simulation allow us to quantitatively describe the variation of the measured tissue properties (fiber orientation and fractional anisotropy) as a function of the observation scale. View full abstract»

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  • Personalization of Cardiac Motion and Contractility From Images Using Variational Data Assimilation

    Page(s): 20 - 24
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (349 KB) |  | HTML iconHTML  

    Personalization is a key aspect of biophysical models in order to impact clinical practice. In this paper, we propose a personalization method of electromechanical models of the heart from cine-MR images based on the adjoint method. After estimation of electrophysiological parameters, the cardiac motion is estimated based on a proactive electromechanical model. Then cardiac contractilities on two or three regions are estimated by minimizing the discrepancy between measured and simulation motion. Evaluation of the method on three patients with infarcted or dilated myocardium is provided. View full abstract»

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  • Multiscale Modeling for Image Analysis of Brain Tumor Studies

    Page(s): 25 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (321 KB) |  | HTML iconHTML  

    Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multiscale, multiphysics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlas-based segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression. View full abstract»

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  • Multiscale Evolving Complex Network Model of Functional Connectivity in Neuronal Cultures

    Page(s): 30 - 34
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (296 KB) |  | HTML iconHTML  

    Cultures of cortical neurons grown on multielectrode arrays exhibit spontaneous, robust, and recurrent patterns of highly synchronous activity called bursts. These bursts play a crucial role in the development and topological self-organization of neuronal networks. Thus, understanding the evolution of synchrony within these bursts could give insight into network growth and the functional processes involved in learning and memory. Functional connectivity networks can be constructed by observing patterns of synchrony that evolve during bursts. To capture this evolution, a modeling approach is adopted using a framework of emergent evolving complex networks and, through taking advantage of the multiple time scales of the system, aims to show the importance of sequential and ordered synchronization in network function. View full abstract»

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  • A Multiscale Parallel Computing Architecture for Automated Segmentation of the Brain Connectome

    Page(s): 35 - 38
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (416 KB) |  | HTML iconHTML  

    Several groups in neurobiology have embarked into deciphering the brain circuitry using large-scale imaging of a mouse brain and manual tracing of the connections between neurons. Creating a graph of the brain circuitry, also called a connectome, could have a huge impact on the understanding of neurodegenerative diseases such as Alzheimer's disease. Although considerably smaller than a human brain, a mouse brain already exhibits one billion connections and manually tracing the connectome of a mouse brain can only be achieved partially. This paper proposes to scale up the tracing by using automated image segmentation and a parallel computing approach designed for domain experts. We explain the design decisions behind our parallel approach and we present our results for the segmentation of the vasculature and the cell nuclei, which have been obtained without any manual intervention. View full abstract»

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  • Automated Multiscale Morphometry of Muscle Disease From Second Harmonic Generation Microscopy Using Tensor-Based Image Processing

    Page(s): 39 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (544 KB) |  | HTML iconHTML  

    Practically, all chronic diseases are characterized by tissue remodeling that alters organ and cellular function through changes to normal organ architecture. Some morphometric alterations become irreversible and account for disease progression even on cellular levels. Early diagnostics to categorize tissue alterations, as well as monitoring progression or remission of disturbed cytoarchitecture upon treatment in the same individual, are a new emerging field. They strongly challenge spatial resolution and require advanced imaging techniques and strategies for detecting morphological changes. We use a combined second harmonic generation (SHG) microscopy and automated image processing approach to quantify morphology in an animal model of inherited Duchenne muscular dystrophy ( mdx mouse) with age. Multiphoton XYZ image stacks from tissue slices reveal vast morphological deviation in muscles from old mdx mice at different scales of cytoskeleton architecture: cell calibers are irregular, myofibrils within cells are twisted, and sarcomere lattice disruptions (detected as “verniers”) are larger in number compared to samples from healthy mice. In young mdx mice, such alterations are only minor. The boundary-tensor approach, adapted and optimized for SHG data, is a suitable approach to allow quick quantitative morphometry in whole tissue slices. The overall detection performance of the automated algorithm compares very well with manual “ by eye” detection, the latter being time consuming and prone to subjective errors. Our algorithm outperfoms manual detection by time with similar reliability. This approach will be an important prerequisite for the implementation of a clinical image databases to diagnose and monitor specific morphological alterations in chronic (muscle) diseases. View full abstract»

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  • In Vivo Imaging and Spectroscopy of Dynamic Metabolism Using Simultaneous ^{13} C and ^1 H MRI

    Page(s): 45 - 49
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (579 KB) |  | HTML iconHTML  

    Hyperpolarized (HP) 13C-labeled pyruvate studies with magnetic resonance (MR) have been used to observe the kinetics of metabolism in vivo. Kinetic modeling to measure metabolic rates in vivo is currently limited because of nonspecific hyperpolarized signals mixing between vascular, extravascular, and intracellular compartments. In this study, simultaneous acquisition of both 1H and 13 C signals after contrast agent injection is used to resolve specific compartments to improve the accuracy of the modeling. We demonstrate a novel technique to provide contrast to the intracellular compartments by sequential injection of HP [1-13C] pyruvate followed by gadolinium-chelate to provide T1-shortening to extra-cellular compartments. A kinetic model that distinguishes the intracellular space and includes the T1-shortening effect of the gadolinium chelate can then be used to directly measure the intracellular 13C kinetics. View full abstract»

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  • Multiscale Modeling of Circular and Elliptical Particles in Laminar Shear Flow

    Page(s): 50 - 53
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (473 KB) |  | HTML iconHTML  

    Drug delivery systems for cancer prevention and pain management have been improved related to classical cancer chemotherapy. Nanotechnology with nanoparticles offers new ways in transport of drug molecules and contrast agents by the blood flow through the circulatory system. In this study, we use multiscale mesoscopic bridging procedure of the finite elements (FE) coupled with dissipative particle dynamics (DPD) and lattice Boltzmann (LB) method to model the motion of circular and elliptical particles in a 2-D laminar flow. Four examples are considered: 1) one sedimenting cylinder in a channel, 2) two sedimenting cylinders in a channel, 3) motion of four elliptical particles in a linear shear flow, and 4) motion of circular and elliptical particle in the arterial bifurcation geometry. A good agreement with solution from the literature available was found. These results show that the multiscale approach with coupled FE and DPD/LB methods can effectively be applied to model motion of micro/nanoparticles for a drug delivery system. View full abstract»

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  • In Silico Evaluation of Glucose Control Protocols for Critically Ill Patients

    Page(s): 54 - 57
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB) |  | HTML iconHTML  

    This letter presents an in silico evaluation method of glucose control protocols for critically ill patients with hyperglycemia. Although various glucose control protocols were introduced and investigated in clinical trials, development and validation of a novel glucose control protocol for critically ill patients require too much time and resources in clinical evaluation. We employed a virtual patient model of the critically ill patient with hyperglycemia and evaluated the clinically investigated glucose control protocols in a computational environment. The three-day simulation results presented the time profiles of glucose and insulin concentrations, the amount of enteral feed and intravenous bolus of glucose, and the intravenous insulin infusion rate. The hyperglycemia and hypoglycemia index, blood glucose concentrations, insulin doses, intravenous glucose infusion rates, and glucose feed rates were compared between different protocols. It is shown that a similar hypoglycemia incidence exists in simulation and clinical results. We concluded that this in silico simulation method using a virtual patient model could be useful for predicting hypoglycemic incidence of novel glucose control protocols for critically ill patients, prior to clinical trials. View full abstract»

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  • A Sparse and Spatially Constrained Generative Regression Model for fMRI Data Analysis

    Page(s): 58 - 67
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1010 KB) |  | HTML iconHTML  

    In this study, we present an advanced Bayesian framework for the analysis of functional magnetic resonance imaging (fMRI) data that simultaneously employs both spatial and sparse properties. The basic building block of our method is the general linear regression model that constitutes a well-known probabilistic approach. By treating regression coefficients as random variables, we can apply an enhanced Gibbs distribution function that captures spatial constrains and at the same time allows sparse representation of fMRI time series. The proposed scheme is described as a maximum a posteriori approach, where the known expectation maximization algorithm is applied offering closed-form update equations for the model parameters. We have demonstrated that our method produces improved performance and functional activation detection capabilities in both simulated data and real applications. View full abstract»

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  • Diamagnetic Levitation Causes Changes in the Morphology, Cytoskeleton, and Focal Adhesion Proteins Expression in Osteocytes

    Page(s): 68 - 77
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (898 KB) |  | HTML iconHTML  

    Diamagnetic levitation technology is a novel simulated weightless technique and has recently been applied in life-science research. We have developed a superconducting magnet platform with large gradient high magnetic field (LG-HMF), which can provide three apparent gravity levels, namely, μg (diamagnetic levitation), 1g, and 2g for diamagnetic materials. In this study, the effects of LG-HMF on the activity, morphology, and cytoskeleton (actin filament, microtubules, and vimentin intermediate filaments) in osteocyte - like cell line MLO-Y4 were detected by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) methods, hematoxylin-eosin (HE) staining, and laser scanning confocal microscopy (LSCM), respectively. The changes induced by LG-HMF in distribution and expression of focal adhesion (FA) proteins, including vinculin, paxillin, and talin in MLO-Y4 were determined by LSCM and Western blotting. The results showed that LG-HMF produced by superconducting magnet had no lethal effects on MLO-Y4. Compared to control, diamagnetic levitation (μg) affected MLO-Y4 morphology, nucleus size, cytoskeleton architecture, and FA proteins distribution and expression. The study indicates that osteocytes are sensitive to altered gravity and FA proteins (vinculin, paxillin, and talin) may be involved in osteocyte mechanosensation. The diamagnetic levitation may be a novel ground-based space-gravity simulator and can be used for biological experiment at cellular level. View full abstract»

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  • An Algorithm Used for Ventricular Fibrillation Detection Without Interrupting Chest Compression

    Page(s): 78 - 86
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (647 KB) |  | HTML iconHTML  

    Ventricular fibrillation (VF) is the primary arrhythmic event in the majority of patients suffering from sudden cardiac arrest. Attention has been focused on this particular rhythm since it is recognized that prompt therapy, especially electrical defibrillation, may lead to a successful outcome. However, current versions of automated external defibrillators (AEDs) mandate repetitive interruptions of chest compression for rhythm analyses since artifacts produced by chest compression during cardiopulmonary resuscitation (CPR) preclude reliable electrocardiographic (ECG) rhythm analysis. Yet, repetitive interruptions in chest compression are detrimental to the success of defibrillation. The capability for rhythm analysis without requiring “hands-off” intervals will allow for more effective resuscitation. In this paper, a novel continuous-wavelet-transformation-based morphology consistency evaluation algorithm was developed for the detection of disorganized VF from organized sinus rhythm (SR) without interrupting the ongoing chest compression. The performance of this method was evaluated on both uncorrupted and corrupted ECG signals recorded from AEDs obtained from out-of-hospital victims of cardiac arrest. A total of 232 patients and 31 092 episodes of either VF or SR were accessed, in which 8195 episodes were corrupted by artifacts produced by chest compressions. We also compared the performance of this method with three other established algorithms, including VF filter, spectrum analysis, and complexity measurement. Even though there was a modest decrease in specificity and accuracy when chest compression artifact was present, the performance of this method was still superior to other reported methods for VF detection during uninterrupted CPR. View full abstract»

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  • Diffuse Optical Multipatch Technique for Tissue Oxygenation Monitoring: Clinical Study in Intensive Care Unit

    Page(s): 87 - 94
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (597 KB) |  | HTML iconHTML  

    Diffuse optical multipatch technique is used to assess spatial variations in absorption and scattering in biological tissue, by monitoring changes in the concentration of oxyhemoglobin and deoxyhemoglobin. In our preliminary study, the temporal tracings of tissue oxygenation are measured using diffuse optical multipatch measurement and a venous occlusion test, employing normal subjects and ICU patients suffering from sepsis and heart failure. In experiments, obvious differences in tissue oxygenation signals were observed among all three groups. This paper discusses the physiological relevance of tissue oxygenation with respect to disease. View full abstract»

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  • Realtime Control of Multiple-focus Phased Array Heating Patterns Based on Noninvasive Ultrasound Thermography

    Page(s): 95 - 105
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (894 KB) |  | HTML iconHTML  

    A system for the realtime generation and control of multiple-focus ultrasound phased-array heating patterns is presented. The system employs a 1-MHz, 64-element array and driving electronics capable of fine spatial and temporal control of the heating pattern. The driver is integrated with a realtime 2-D temperature imaging system implemented on a commercial scanner. The coordinates of the temperature control points are defined on B-mode guidance images from the scanner, together with the temperature set points and controller parameters. The temperature at each point is controlled by an independent proportional, integral, and derivative controller that determines the focal intensity at that point. Optimal multiple-focus synthesis is applied to generate the desired heating pattern at the control points. The controller dynamically reallocates the power available among the foci from the shared power supply upon reaching the desired temperature at each control point. Furthermore, anti-windup compensation is implemented at each control point to improve the system dynamics. In vitro experiments in tissue-mimicking phantom demonstrate the robustness of the controllers for short (2-5 s) and longer multiple-focus high-intensity focused ultrasound exposures. Thermocouple measurements in the vicinity of the control points confirm the dynamics of the temperature variations obtained through noninvasive feedback. View full abstract»

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  • High-Frequency and Low-Frequency Chest Compression: Effects on Lung Water Secretion, Mucus Transport, Heart Rate, and Blood Pressure Using a Trapezoidal Source Pressure Waveform

    Page(s): 106 - 114
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (513 KB) |  | HTML iconHTML  

    High-frequency chest compression (HFCC), using an appropriate source (pump) waveform for frequencies at or above 3 Hz, can enhance pulmonary clearance for patients with cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD). Using a trapezoidal HFCC source pressure waveform, secretion of water from epithelial tissue and transport of mucus through lung airways can be enhanced for patients with CF and COPD. At frequencies below 3 Hz, low-frequency chest compression (LFCC) appears to have a significant impact on the cardiovascular system. For a trapezoidal source pressure waveform at frequencies close to 1 Hz, LFCC produces amplitude or intensity variations in various components of the electrocardiogram time-domain waveform, produces changes at very low frequencies associated with the electrocardiogram frequency spectra (indicating enhanced parasympathetic nervous system activity), and promotes a form of heart rate synchronization. It appears that LFCC can also provide additional cardiovascular benefits by reducing peak and average systolic and diastolic blood pressure for patients with hypertension. View full abstract»

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  • Tissue Dielectric Measurement Using an Interstitial Dipole Antenna

    Page(s): 115 - 121
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1194 KB) |  | HTML iconHTML  

    The purpose of this study was to develop a technique to measure the dielectric properties of biological tissues with an interstitial dipole antenna based upon previous efforts for open-ended coaxial probes. The primary motivation for this technique is to facilitate treatment monitoring during microwave tumor ablation by utilizing the heating antenna without additional intervention or interruption of the treatment. The complex permittivity of a tissue volume surrounding the antenna was calculated from reflection coefficients measured after high-temperature microwave heating by using a rational function model of the antenna's input admittance. Three referencing liquids were needed for measurement calibration. The dielectric measurement technique was validated ex vivo in normal and ablated bovine livers. Relative permittivity and effective conductivity were lower in the ablation zone when compared to normal tissue, consistent with previous results. The dipole technique demonstrated a mean 10% difference of permittivity values when compared to open-ended coaxial cable measurements in the frequency range of 0.5-20 GHz. Variability in measured permittivities could be smoothed by fitting to a Cole-Cole dispersion model. Further development of this technique may facilitate real-time monitoring of microwave ablation treatments through the treatment applicator. View full abstract»

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  • Clinical Evaluation of Respiratory Motion Compensation for Anatomical Roadmap Guided Cardiac Electrophysiology Procedures

    Page(s): 122 - 131
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (552 KB) |  | HTML iconHTML  

    X-ray fluoroscopically guided cardiac electrophysiological procedures are routinely carried out for diagnosis and treatment of cardiac arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of static 3-D roadmaps derived from preprocedural volumetric data can be used to add anatomical information. However, the registration between the 3-D roadmap and the 2-D X-ray image can be compromised by patient respiratory motion. Three methods were designed and evaluated to correct for respiratory motion using features in the 2-D X-ray images. The first method is based on tracking either the diaphragm or the heart border using the image intensity in a region of interest. The second method detects the tracheal bifurcation using the generalized Hough transform and a 3-D model derived from 3-D preoperative volumetric data. The third method is based on tracking the coronary sinus (CS) catheter. This method uses blob detection to find all possible catheter electrodes in the X-ray image. A cost function is applied to select one CS catheter from all catheter-like objects. All three methods were applied to X-ray images from 18 patients undergoing radiofrequency ablation for the treatment of atrial fibrillation. The 2-D target registration errors (TRE) at the pulmonary veins were calculated to validate the methods. A TRE of 1.6 mm ± 0.8 mm was achieved for the diaphragm tracking; 1.7 mm ± 0.9 mm for heart border tracking, 1.9 mm ± 1.0 mm for trachea tracking, and 1.8 mm ± 0.9 mm for CS catheter tracking. We present a comprehensive comparison between the techniques in terms of robustness, as computed by tracking errors, and accuracy, as computed by TRE using two independent approaches. View full abstract»

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  • Target Selection With Hybrid Feature for BCI-Based 2-D Cursor Control

    Page(s): 132 - 140
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (543 KB) |  | HTML iconHTML  

    To control a cursor on a monitor screen, a user generally needs to perform two tasks sequentially. The first task is to move the cursor to a target on the monitor screen (termed a 2-D cursor movement), and the second task is either to select a target of interest by clicking on it or to reject a target that is not of interest by not clicking on it. In a previous study, we implemented the former function in an EEG-based brain-computer interface system using motor imagery and the P300 potential to control the horizontal and vertical cursor movements, respectively. In this study, the target selection or rejection functionality is implemented using a hybrid feature from motor imagery and the P300 potential. Specifically, to select the target of interest, the user must focus his or her attention on a flashing button to evoke the P300 potential, while simultaneously maintaining an idle state of motor imagery. Otherwise, the user performs left-/right-hand motor imagery without paying attention to any buttons to reject the target. Our data analysis and online experimental results validate the effectiveness of our approach. The proposed hybrid feature is shown to be more effective than the use of either the motor imagery feature or the P300 feature alone. Eleven subjects attended our online experiment, in which a trial involved sequential 2-D cursor movement and target selection. The average duration of each trial and average accuracy of target selection were 18.19 s and 93.99% , respectively, and each target selection or rejection event was performed within 2 s. 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