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Biomedical Engineering, IEEE Transactions on

Issue 9 • Date Sept. 2008

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Displaying Results 1 - 25 of 27
  • 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): 2113 - 2114
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  • Acoustic fMRI Noise: Linear Time-Invariant System Model

    Page(s): 2115 - 2123
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (706 KB) |  | HTML iconHTML  

    Functional magnetic resonance imaging (fMRI) enables sites of brain activation to be localized in human subjects. For auditory system studies, however, the acoustic noise generated by the scanner tends to interfere with the assessments of this activation. Understanding and modeling fMRI acoustic noise is a useful step to its reduction. To study acoustic noise, the MR scanner is modeled as a linear electroacoustical system generating sound pressure signals proportional to the time derivative of the input gradient currents. The transfer function of one MR scanner is determined for two different input specifications: 1) by using the gradient waveform calculated by the scanner software and 2) by using a recording of the gradient current. Up to 4 kHz, the first method is shown as reliable as the second one, and its use is encouraged when direct measurements of gradient currents are not possible. Additionally, the linear order and average damping properties of the gradient coil system are determined by impulse response analysis. Since fMRI is often based on echo planar imaging (EPI) sequences, a useful validation of the transfer function prediction ability can be obtained by calculating the acoustic output for the EPI sequence. We found a predicted sound pressure level (SPL) for the EPI sequence of 104 dB SPL compared to a measured value of 102 dB SPL. As yet, the predicted EPI pressure waveform shows similarity as well as some differences with the directly measured EPI pressure waveform. View full abstract»

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  • Boundary Element Computations in the Forward and Inverse Problems of Electrocardiography: Comparison of Collocation and Galerkin Weightings

    Page(s): 2124 - 2133
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (530 KB) |  | HTML iconHTML  

    In electrocardiographic imaging, epicardial potentials are reconstructed computationally from electrocardiographic measurements. The reconstruction is typically done with the help of the boundary element method (BEM), using the point collocation weighting and constant or linear basis functions. In this paper, we evaluated the performance of constant and linear point collocation and Galerkin BEMs in the epicardial potential problem. The integral equations and discretizations were formulated in terms of the single- and double-layer operators. All inner element integrals were calculated analytically. The computational methods were validated against analytical solutions in a simplified geometry. On the basis of the validation, no method was optimal in all testing scenarios. In the forward computation of the epicardial potential, the linear Galerkin (LG) method produced the smallest errors. The LG method also produced the smallest discretization error on the epicardial surface. In the inverse computation of epicardial potential, the electrode-specific transfer matrix performed better than the full transfer matrix. The Tikhonov 2 regularization outperformed the Tikhonov 0. In the optimal modeling conditions, the best BEM technique depended on electrode positions and chosen error measure. When large modeling errors such as omission of the lungs were present, the choice of the basis and weighting functions was not significant. View full abstract»

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  • Modeling of Prosthetic Limb Rotation Control by Sensing Rotation of Residual Arm Bone

    Page(s): 2134 - 2142
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (554 KB) |  | HTML iconHTML  

    We proposed a new approach to improve the control of prosthetic arm rotation in amputees. Arm rotation is sensed by implanting a small permanent magnet into the distal end of the residual bone, which produces a magnetic field. The position of the bone rotation can be derived from magnetic field distribution detected with magnetic sensors on the arm surface, and then conveyed to the prosthesis controller to manipulate the rotation of the prosthesis. Proprioception remains intact for residual limb skeletal structures; thus, this control system should be natural and easy-to-use. In this study, simulations have been conducted in an upper arm model to assess the feasibility and performance of sensing the voluntary rotation of residual humerus with an implanted magnet. A sensitivity analysis of the magnet size and arm size was presented. The influence of relative position of the magnet to the magnetic sensors, orientation of the magnet relative to the limb axis, and displacement of the magnetic sensors on the magnetic field was evaluated. The performance of shielding external magnetostatic interference was also investigated. The simulation results suggest that the direction and angle of rotation of residual humerus could be obtained by decoding the magnetic field signals with magnetic sensors built into a prosthetic socket. This pilot study provides important guidelines for developing a practical interface between the residual bone rotation and the prosthesis for control of prosthetic rotation. View full abstract»

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  • Gaussian Process Robust Regression for Noisy Heart Rate Data

    Page(s): 2143 - 2151
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (531 KB) |  | HTML iconHTML  

    Heart rate data collected during nonlaboratory conditions present several data-modeling challenges. First, the noise in such data is often poorly described by a simple Gaussian; it has outliers and errors come in bursts. Second, in large-scale studies the ECG waveform is usually not recorded in full, so one has to deal with missing information. In this paper, we propose a robust postprocessing model for such applications. Our model to infer the latent heart rate time series consists of two main components: unsupervised clustering followed by Bayesian regression. The clustering component uses auxiliary data to learn the structure of outliers and noise bursts. The subsequent Gaussian process regression model uses the cluster assignments as prior information and incorporates expert knowledge about the physiology of the heart. We apply the method to a wide range of heart rate data and obtain convincing predictions along with uncertainty estimates. In a quantitative comparison with existing postprocessing methodology, our model achieves a significant increase in performance. View full abstract»

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  • Speckle Noise Reduction of Medical Ultrasound Images in Complex Wavelet Domain Using Mixture Priors

    Page(s): 2152 - 2160
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (555 KB) |  | HTML iconHTML  

    Speckle noise is an inherent nature of ultrasound images, which may have negative effect on image interpretation and diagnostic tasks. In this paper, we propose several multiscale nonlinear thresholding methods for ultrasound speckle suppression. The wavelet coefficients of the logarithm of image are modeled as the sum of a noise-free component plus an independent noise. Assuming that the noise-free component has some local mixture distribution (MD), and the noise is either Gaussian or Rayleigh, we derive the minimum mean squared error (MMSE) and the averaged maximum (AMAP) estimators for noise reduction. We use Gaussian and Laplacian MD for each noise-free wavelet coefficient to characterize their heavy-tailed property. Since we estimate the parameters of the MD using the expectation maximization (EM) algorithm and local neighbors, the proposed MD incorporates some information about the intrascale dependency of the wavelet coefficients. To evaluate our spatially adaptive despeckling methods, we use both real medical ultrasound and synthetically introduced speckle images for speckle suppression. The simulation results show that our method outperforms several recently and the state-of-the-art techniques qualitatively and quantitatively. View full abstract»

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  • Robust Predictive Control Strategy Applied for Propofol Dosing Using BIS as a Controlled Variable During Anesthesia

    Page(s): 2161 - 2170
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (793 KB) |  | HTML iconHTML  

    This paper presents the application of predictive control to drug dosing during anesthesia in patients undergoing surgery. The performance of a generic predictive control strategy in drug dosing control, with a previously reported anesthesia-specific control algorithm, has been evaluated. The robustness properties of the predictive controller are evaluated with respect to inter- and intrapatient variability. A single-input (propofol) single-output (bispectral index, BIS) model of the patient has been assumed for prediction as well as for simulation. A set of 12 patient models were studied and interpatient variability and disturbances are used to assess robustness of the controller. Furthermore, the controller guarantees the stability in a desired range. The applicability of the predictive controller in a real-life environment via simulation studies has been assessed. View full abstract»

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  • A Study on the Possible Usefulness of Detrended Fluctuation Analysis of the Electroencephalogram Background Activity in Alzheimer's Disease

    Page(s): 2171 - 2179
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (360 KB) |  | HTML iconHTML  

    We studied the EEG background activity of Alzheimer's disease (AD) patients with detrended fluctuation analysis (DFA). DFA provides an estimation of the scaling information and long-range correlations in time series. We recorded the EEG in 11 AD patients and 11 age-matched controls. Our results showed two scaling regions in all subjects' channels (for limited time scales from 0.01 to 0.04 s and from 0.08 to 0.43 s, respectively), with a clear bend when their corresponding slopes (alpha1 and alpha2) were different. No significant differences between groups were found with alpha1. However, alpha2 values were significantly lower in control subjects at electrodes T5, T6, and O1 ( p <0.01, Student's -test). These findings suggest that the scaling behavior of the EEG is sensitive to AD. Although values allowed us to separate AD patients and controls, accuracies were lower than with spectral analysis. However, a forward stepwise linear discriminant analysis with a leave-one-out cross-validation procedure showed that the combined use of DFA and spectral analysis could improve the diagnostic accuracy of each individual technique. Thus, although spectral analysis outperforms DFA, the combined use of both techniques may increase the insight into brain dysfunction in AD. View full abstract»

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  • Decomposition of Intramuscular EMG Signals Using a Heuristic Fuzzy Expert System

    Page(s): 2180 - 2189
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (722 KB) |  | HTML iconHTML  

    Although increasingly sophisticated algorithms have been proposed to decompose intramuscular electromyography signals into the concurrent activities of individual motor units (MUs), the human operator is still able to improve decomposition results by visual inspection. The rationale for this paper was to combine components from previous decomposition procedures in an expert systems approach utilizing fuzzy logic and attempting to replicate the thought process of an accomplished decomposer in order to minimize the user interaction subsequently needed to enhance decomposition results. The decomposition procedure is discussed and examples are given of the type of information it can yield. The method has been used to identify the discharge activities of up to 15 MUs with up to 95% accuracy. View full abstract»

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  • Integrated Approach for Fetal QRS Detection

    Page(s): 2190 - 2197
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (477 KB) |  | HTML iconHTML  

    Fetal magnetocardiography provides reliable signals of the fetal heart dynamics with high temporal resolution that can be used in a clinical setting. We present a robust Hilbert transform method for extraction of the fetal heart rate. Our method may be applied to signals derived from a single channel or an array of channels. In the case of multichannel data, the channels can be combined to improve signal-to-noise ratio for the extraction of fetal heart data. The method is inherently insensitive to fetal position or movement and, in addition, can be automated. We demonstrate that the determination of R-wave timing is relatively insensitive to waveform morphology. The method can also be applied if the data were preprocessed by independent component analysis (ICA). We compared the Hilbert method, ICA, ICA + Hilbert, and raw signals and found that the Hilbert method gave the best overall performance. We demonstrated that there were approximately 171 errors in 46 789 fetal heart beats. View full abstract»

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  • A Comparison of the Effects of Electrode Implantation and Targeting on Pattern Classification Accuracy for Prosthesis Control

    Page(s): 2198 - 2211
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (785 KB) |  | HTML iconHTML  

    The use of surface versus intramuscular electrodes as well as the effect of electrode targeting on pattern-recognition- based multifunctional prosthesis control was explored. Surface electrodes are touted for their ability to record activity from relatively large portions of muscle tissue. Intramuscular electromyograms (EMGs) can provide focal recordings from deep muscles of the forearm and independent signals relatively free of crosstalk. However, little work has been done to compare the two. Additionally, while previous investigations have either targeted electrodes to specific muscles or used untargeted (symmetric) electrode arrays, no work has compared these approaches to determine if one is superior. The classification accuracies of pattern-recognition-based classifiers utilizing surface and intramuscular as well as targeted and untargeted electrodes were compared across 11 subjects. A repeated-measures analysis of variance revealed that when only EMG amplitude information was used from all available EMG channels, the targeted surface, targeted intramuscular, and untargeted surface electrodes produced similar classification accuracies while the untargeted intramuscular electrodes produced significantly lower accuracies. However, no statistical differences were observed between any of the electrode conditions when additional features were extracted from the EMG signal. It was concluded that the choice of electrode should be driven by clinical factors, such as signal robustness/stability, cost, etc., instead of by classification accuracy. View full abstract»

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  • Multilevel Statistical Inference From Functional Near-Infrared Spectroscopy Data During Stroop Interference

    Page(s): 2212 - 2220
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (918 KB) |  | HTML iconHTML  

    Functional near-infrared spectroscopy (fNIRS) is an emerging technique for monitoring the concentration changes of oxy- and deoxy-hemoglobin (oxy-Hb and deoxy-Hb) in the brain. An important consideration in fNIRS-based neuroimaging modality is to conduct group-level analysis from a set of time series measured from a group of subjects. We investigate the feasibility of multilevel statistical inference for fNIRS. As a case study, we search for hemodynamic activations in the prefrontal cortex during Stroop interference. Hierarchical general linear model (GLM) is used for making this multilevel analysis. Activation patterns both at the subject and group level are investigated on a comparative basis using various classical and Bayesian inference methods. All methods showed consistent left lateral prefrontal cortex activation for oxy-Hb during interference condition, while the effects were much less pronounced for deoxy-Hb. Our analysis showed that mixed effects or Bayesian models are more convenient for faithful analysis of fNIRS data. We arrived at two important conclusions. First, fNIRS has the capability to identify activations at the group level, and second, the mixed effects or Bayesian model is the appropriate mechanism to pass from subject to group-level inference. View full abstract»

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  • Removal of the Eye-Blink Artifacts From EEGs via STF-TS Modeling and Robust Minimum Variance Beamforming

    Page(s): 2221 - 2231
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (993 KB) |  | HTML iconHTML  

    A novel scheme for the removal of eye-blink (EB) artifacts from electroencephalogram (EEG) signals based on a novel space--time--frequency (STF) model of EEGs and robust minimum variance beamformer (RMVB) is proposed. In this method, in order to remove the artifact, the RMVB is provided with a priori information, namely, an estimation of the steering vector corresponding to the point source EB artifact. The artifact-removed EEGs are subsequently reconstructed by deflation. The a priori knowledge, the vector corresponding to the spatial distribution of the EB factor, is identified using the STF model of EEGs, provided by the parallel factor analysis (PARAFAC) method. In order to reduce the computational complexity present in the estimation of the STF model using the three-way PARAFAC, the time domain is subdivided into a number of segments, and a four-way array is then set to estimate the STF-time/segment (TS) model of the data using the four-way PARAFAC. The correct number of the factors of the STF model is effectively estimated by using a novel core consistency diagnostic- (CORCONDIA-) based measure. Subsequently, the STF-TS model is shown to closely approximate the classic STF model, with significantly lower computational cost. The results confirm that the proposed algorithm effectively identifies and removes the EB artifact from raw EEG measurements. View full abstract»

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  • Source Localization of Event-Related Potentials Incorporating Spatial Notch Filters

    Page(s): 2232 - 2239
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (584 KB) |  | HTML iconHTML  

    A novel algorithm for the localization of event-related potential (ERP) sources within the brain is proposed here. In this technique, spatial notch filters are developed to exploit the multichannel electroencephalogram data together with a model of ERP with variable parameters in order to accurately localize the corresponding ERP signal sources. The algorithm is robust in the presence of reasonably high noise. The performance of the proposed system has been compared to that of linear constrained minimum variance (LCMV) beamformer for different noise and correlation levels and its superiority has been demonstrated. View full abstract»

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  • ECG Denoising and Compression Using a Modified Extended Kalman Filter Structure

    Page(s): 2240 - 2248
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (739 KB) |  | HTML iconHTML  

    This paper presents efficient denoising and lossy compression schemes for electrocardiogram (ECG) signals based on a modified extended Kalman filter (EKF) structure. We have used a previously introduced two-dimensional EKF structure and modified its governing equations to be extended to a 17-dimensional case. The new EKF structure is used not only for denoising, but also for compression, since it provides estimation for each of the new 15 model parameters. Using these specific parameters, the signal is reconstructed with regard to the dynamical equations of the model. The performances of the proposed method are evaluated using standard denoising and compression efficiency measures. For denosing, the SNR improvement criterion is used, while for compression, we have considered the compression ratio (CR), the percentage area difference (PAD), and the weighted diagnostic distortion (WDD) measure. Several Massachusetts Institute of Technology-Beth Israel Deaconess Medical Center (MIT-BIH) ECG databases are used for performance evaluation. Simulation results illustrate that both applications can contribute to and enhance the clinical ECG data denoising and compression performance. For denoising, an average SNR improvement of 10.16 dB was achieved, which is 1.8 dB more than the next benchmark methods such as MAB WT or EKF2. For compression, the algorithm was extended to include more than five Gaussian kernels. Results show a typical average CR of 11.37:1 with WDD < 1.73 %. Consequently, the proposed framework is suitable for a hybrid system that integrates these algorithmic approaches for clean ECG data storage or transmission scenarios with high output SNRs, high CRs, and low distortions. View full abstract»

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  • Preliminary Feasibility Study of an In-line Phase Contrast X-Ray Imaging Prototype

    Page(s): 2249 - 2257
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (903 KB) |  | HTML iconHTML  

    In this study, a series of imaging experiments on biological specimens, including human breast core biopsies, lumpectomy, and chicken tissues, as well as standard phantoms, were performed in an effort to investigate the feasibility of an in-line phase contrast X-ray imaging prototype. The prototype system employed in the study consists of a microfocus X-ray source with tungsten target and a digital flat panel detector, and it can be operated in both conventional attenuation-based imaging mode and in-line phase contrast imaging mode. Biological specimens were imaged in the conventional mode and phase contrast mode with the same source-to-image-detector distance (SID), and phase contrast images exhibited both improved image quality compared with conventional images, and the overshooting patterns along the boundaries in the specimens, which revealed the occurrence of the edge enhancement effect provided by the phase contrast technique. In addition, the performance of the phase contrast mode and conventional mode was compared based on the American College of Radiology (ACR) phantom imaging and contrast detail mammography (CDMAM) phantom-based contrast detail analysis with two experimental settings: one with the same SID and the other with the same object entrance exposure. In both pairs of comparison under our experimental conditions, the phase contrast imaging mode exhibited improved image quality as compared to the conventional mode, which further supported the feasibility of the prototype. View full abstract»

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  • Collagenase-Aided Intracortical Microelectrode Array Insertion: Effects on Insertion Force and Recording Performance

    Page(s): 2258 - 2267
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (824 KB) |  | HTML iconHTML  

    Intracortical microelectrodes puncture the intact pia mater membrane during insertion, a process that can cause brain dimpling and trauma. To ensure that the device is able to withstand forces during implantation without buckling, the selection of acceptable implant materials and geometries is limited to rigid designs with large cross-sectional areas. Such designs likely increase insertion trauma and potentially exacerbate the chronic tissue response. In this paper, a technique that may relax the mechanical requirements of implanted microelectrodes through enzymatic (collagenase mediated) manipulation of the pia mater is quantified experimentally. Measurements of the insertion force profiles were obtained with a load cell during computer controlled ( m/s) insertion of microwire arrays into the cortex of rats. It was observed that collagenase application reduced the peak insertion force experienced by the microwire arrays by almost 40% on average (4.04 plusmn 2.03 mN versus 2.36 plusmn 1.17 mN; control versus treated sites). Peak insertion force magnitudes were highly dependent on implant location with anterior sites registering lower peaks than more posterior sites. Chronic neural recording performance (up to one month) did not appear to be adversely affected by the collagenase treatment, suggesting the overall safety of the technique. Our data suggest that controlled application of collagenase is a useful method in enabling implantation of thinner microelectrodes, potentially facilitating reduced insertion trauma and lower immune response. Furthermore, due to dependence of insertion force on anatomical location, the intended target region should be considered in implant design. View full abstract»

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  • Irreversible Electroporation Attenuates Neointimal Formation After Angioplasty

    Page(s): 2268 - 2274
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (635 KB) |  | HTML iconHTML  

    Restenosis following coronary angioplasty represents a major clinical problem. Irreversible electroporation (IRE) is a nonthermal, nonpharmacological cell ablation method. IRE utilizes a sequence of electrical pulses that produce permanent damage to tissue within a few seconds. The left carotid arteries of eight rats underwent in vivo intimal damage using two Fogarty angioplasty catheters. The procedure was immediately followed by IRE ablation in four rats, while the remaining four were used as the control group. The IRE ablation was performed using a sequence of ten dc pulses of 3800 V/cm, 100 mus each, at a frequency of ten pulses per second, applied across the blood vessel between two parallel electrodes. The electrical conductance of the treated tissue was measured during the electroporation to provide real-time feedback of the process. Left carotid arteries were excised and fixated after a 28-day follow-up period. Neointimal formation was evaluated histologically. The use of IRE was successful in three out of four animals in a way that is consistent with the measurements of blood vessel electrical properties. The integrity of the endothelial layer was recovered in the IRE-treated animals, compared with control. Successful IRE reduced neointima to media ratio (0.57 plusmn 0.4 versus 1.88 plusmn 1.0, P = 0.02). Conclusions: We report for the first time the in vivo results of attenuation of neointimal formation using IRE. Our study shows that IRE might be able to attenuate neointimal formation after angioplasty damage in a rodent model of restenosis. This approach may open new venues in the treatment of coronary artery restenosis after balloon angioplasty. View full abstract»

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  • An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms

    Page(s): 2275 - 2285
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB) |  | HTML iconHTML  

    This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature- extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic system was applied on 100 intracardiac AF signal strips and on a selection of 11 representative features, demonstrating: a) the possibility to properly identify the most significant features for the discrimination of AF types; b) higher accuracy (97.7% using the seven most informative features) than the traditional maximum likelihood classifier; and c) effectiveness in AF classification also with few training samples (accuracy = 88.3% with only five training signals). Finally, the system identifies a combination of indices characterizing changes of morphology of atrial activation waves and perturbation of the isoelectric line as the most effective in separating the AF types. View full abstract»

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  • Correlation Between Structure and Resistivity Variations of the Live Human Skull

    Page(s): 2286 - 2292
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (467 KB) |  | HTML iconHTML  

    A study on correlation between structure and resistivity variations was performed for live adult human skull. The resistivities of 388 skull samples, excised from 48 skull flaps of patients undergoing surgery, were measured at body temperature (36.5degC) using the well-known four-electrode method in the frequency range of 1-4 MHz. According to different structures of the skull samples, all the 388 samples were classified into six categories and measured their resistivities: standard trilayer skull (7943 1752 Omegaldrcm, 58 samples), quasi-trilayer skull (14471 3061 Omegaldrcm, 110 samples), standard compact skull (26546 5374 Omegaldr, 62 samples), quasi-compact skull (19824 3232 Omegaldr, 53 samples), dentate suture skull (5782 1778 Omegaldr, 41 samples), and squamous suture skull (12747 4120 Omegaldr, 64 samples). The results showed that the skull resistivities were not homogenous and were significantly influenced by local structural variations. The presence of sutures appeared to decrease the overall resistivity of particular regions largely and dentate suture decreased the resistivity more than squamous suture. The absence of diploe appeared to increase skull resistivity. The percentage on thickness of diploe would be the primary factor in determining the resistivity of the skull sample without suture. From resistivity spectra results, an inverse relationship between skull resistivity and signal frequency was found. View full abstract»

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  • Investigation of the Cross-Ratios Method for Point-of-Gaze Estimation

    Page(s): 2293 - 2302
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (322 KB) |  | HTML iconHTML  

    The cross-ratios method for point-of-gaze (PoG) estimation uses the invariance property of cross-ratios in projective transformations. The inherent causes of the subject-dependent PoG estimation bias exhibited by this method have not been well characterized in the literature. Using a model of the eye and the components of a system (camera, light sources) that estimates PoG, a theoretical framework for the cross-ratios method is developed. The analysis of the cross-ratios method within this framework shows that the subject-dependent estimation bias is caused mainly by: 1) the angular deviation of the visual axis from the optic axis and 2) the fact that the virtual image of the pupil center is not coplanar with the virtual images of the light sources that illuminate the eye (corneal reflections). The theoretical framework provides a closed-form analytical expression that predicts the estimation bias as a function of subject-specific eye parameters. The theoretical framework also provides a clear physical interpretation for an existing empirically derived two-step procedure that compensates for the estimation bias and shows that the first step of this procedure is equivalent to moving the corneal reflections to a new plane that minimizes the distance from this plane to the virtual image of the pupil center. View full abstract»

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  • Rigorous Mathematical Modeling Techniques for Optimal Delivery of Macromolecules to the Brain

    Page(s): 2303 - 2313
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (913 KB) |  | HTML iconHTML  

    Several treatment modalities for neurodegenerative diseases or tumors of the central nervous system involve invasive delivery of large molecular weight drugs to the brain. Despite the ample record of experimental studies, accurate drug targeting for the human brain remains a challenge. This paper proposes a systematic design method of administering drugs to specific locations in the human brain based on first principles transport in porous media. The proposed mathematical framework predicts achievable treatment volumes in target regions as a function of brain anatomy and infusion catheter position. A systematic procedure to determine the optimal infusion and catheter design parameters that maximize the penetration depth and volumes of distribution will be discussed. The computer simulations are validated with agarose gel phantom experiments and rat data. The rigorous computational approach will allow physicians and scientists to better plan the administration of therapeutic drugs to the central nervous system. View full abstract»

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  • Electrode Position Scaling in Realistic Laplacian Computation

    Page(s): 2314 - 2316
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (228 KB) |  | HTML iconHTML  

    This note discusses the effects of the electrode position scaling on the realistic Laplacian (RL) computation. It is shown that when the RL is estimated with the help of Tikhonov regularization and the generalized cross-validation (GCV) criterion, improper electrode position scaling may influence the GCV criterion, which results in the decrease of RL precision. We identify what the proper scaling should be, and we provide a closer examination of how the GCV criterion is affected by the electrode position scaling. 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