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Biomedical Engineering, IEEE Transactions on

Issue 3 • Date March 2008

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Displaying Results 1 - 25 of 57
  • [Front cover]

    Publication Year: 2008 , Page(s): C1
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    Freely Available from IEEE
  • IEEE Transactions on Biomedical Engineering publication information

    Publication Year: 2008 , Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (40 KB)  
    Freely Available from IEEE
  • Table of contents

    Publication Year: 2008 , Page(s): 845 - 847
    Save to Project icon | Request Permissions | PDF file iconPDF (130 KB)  
    Freely Available from IEEE
  • Modeling the Forces of Cutting With Scissors

    Publication Year: 2008 , Page(s): 848 - 856
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1053 KB) |  | HTML iconHTML  

    Modeling forces applied to scissors during cutting of biological materials is useful for surgical simulation. Previous approaches to haptic display of scissor cutting are based on recording and replaying measured data. This paper presents an analytical model based on the concepts of contact mechanics and fracture mechanics to calculate forces applied to scissors during cutting of a slab of material. The model considers the process of cutting as a sequence of deformation and fracture phases. During deformation phases, forces applied to the scissors are calculated from a torque-angle response model synthesized from measurement data multiplied by a ratio that depends on the position of the cutting crack edge and the curve of the blades. Using the principle of conservation of energy, the forces of fracture are related to the fracture toughness of the material and the geometry of the blades of the scissors. The forces applied to scissors generally include high-frequency fluctuations. We show that the analytical model accurately predicts the average applied force. The cutting model is computationally efficient, so it can be used for real-time computations such as haptic rendering. Experimental results from cutting samples of paper, plastic, cloth, and chicken skin confirm the model, and the model is rendered in a haptic virtual environment. View full abstract»

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  • An Improved PID Switching Control Strategy for Type 1 Diabetes

    Publication Year: 2008 , Page(s): 857 - 865
    Cited by:  Papers (40)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1089 KB) |  | HTML iconHTML  

    In order for an "artificial pancreas" to become a reality for ambulatory use, a practical closed-loop control strategy must be developed and validated. In this paper, an improved PID control strategy for blood glucose control is proposed and critically evaluated in silico using a physiologic model of Hovorka et al. The key features of the proposed control strategy are: 1) a switching strategy for initiating PID control after a meal and insulin bolus; 2) a novel time-varying setpoint trajectory; 3) noise and derivative filters to reduce sensitivity to sensor noise; and 4) a practical controller tuning strategy. Simulation results demonstrate that proposed control strategy compares favorably to alternatives for realistic conditions that include meal challenges, incorrect carbohydrate meal estimates, changes in insulin sensitivity, and measurement noise. View full abstract»

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  • Understanding Perceptual Boundaries in Laparoscopic Surgery

    Publication Year: 2008 , Page(s): 866 - 873
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1262 KB) |  | HTML iconHTML  

    Human perceptual capabilities related to the laparoscopic interaction paradigm are not well known. Its study is important for the design of virtual reality simulators, and for the specification of augmented reality applications that overcome current limitations and provide a supersensing to the surgeon. As part of this work, this article addresses the study of laparoscopic pulling forces. Two definitions are proposed to focalize the problem: the perceptual fidelity boundary, limit of human perceptual capabilities, and the Utile fidelity boundary, that encapsulates the perceived aspects actually used by surgeons to guide an operation. The study is then aimed to define the perceptual fidelity boundary of laparoscopic pulling forces. This is approached with an experimental design in which surgeons assess the resistance against pulling of four different tissues, which are characterized with both in vivo interaction forces and ex vivo tissue biomechanical properties. A logarithmic law of tissue consistency perception is found comparing subjective valorizations with objective parameters. A model of this perception is developed identifying what the main parameters are: the grade of fixation of the organ, the tissue stiffness, the amount of tissue bitten, and the organ mass being pulled. These results are a clear requirement analysis for the force feedback algorithm of a virtual reality laparoscopic simulator. Finally, some discussion is raised about the suitability of augmented reality applications around this surgical gesture. View full abstract»

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  • A Model-Predictive Hypnosis Control System Under Total Intravenous Anesthesia

    Publication Year: 2008 , Page(s): 874 - 887
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1326 KB) |  | HTML iconHTML  

    In ambulatory surgery, anesthetic drugs must be administered at a suitable rate to prevent adverse reactions after discharge from the hospital. To realize more appropriate anesthesia, we have developed a hypnosis control system, which administers propofol as an anesthetic drug to regulate the bispectral index (BIS), an electroencephalography (EEG)-derived index reflecting the hypnosis of a patient. This system consists of three functions: 1) a feedback controller using a model-predictive control method, which can adequately accommodate the effects of time delays; 2) a parameter estimation function of individual differences; and 3) a risk control function for preventing undesirable states such as drug overinfusion or intraoperative arousal. With the approval of the ethics committee of our institute, 79 clinical trials took place since July 2002. The results show that our system can reduce the total amount of propofol infusion and maintain the BIS more accurately than anesthesiologist's manual adjustment. View full abstract»

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  • A Fully Automatic CAD-CTC System Based on Curvature Analysis for Standard and Low-Dose CT Data

    Publication Year: 2008 , Page(s): 888 - 901
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1462 KB) |  | HTML iconHTML  

    Computed tomography colonography (CTC) is a rapidly evolving noninvasive medical investigation that is viewed by radiologists as a potential screening technique for the detection of colorectal polyps. Due to the technical advances in CT system design, the volume of data required to be processed by radiologists has increased significantly, and as a consequence the manual analysis of this information has become an increasingly time consuming process whose results can be affected by inter- and intrauser variability. The aim of this paper is to detail the implementation of a fully integrated CAD-CTC system that is able to robustly identify the clinically significant polyps in the CT data. The CAD-CTC system described in this paper is a multistage implementation whose main system components are: 1) automatic colon segmentation; 2) candidate surface extraction; 3) feature extraction; and 4) classification. Our CAD-CTC system performs at 100% sensitivity for polyps larger than 10 mm, 92% sensitivity for polyps in the range 5 to 10 mm, and 57.14% sensitivity for polyps smaller than 5 mm with an average of 3.38 false positives per dataset. The developed system has been evaluated on synthetic and real patient CT data acquired with standard and low-dose radiation levels. View full abstract»

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  • Tracking the Time-Varying Cortical Connectivity Patterns by Adaptive Multivariate Estimators

    Publication Year: 2008 , Page(s): 902 - 913
    Cited by:  Papers (34)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1062 KB) |  | HTML iconHTML  

    The directed transfer function (DTF) and the partial directed coherence (PDC) are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods is based on the multivariate autoregressive modelling (MVAR) of time series, which requires the stationarity of the signals. In this way, transient pathways of information transfer remains hidden. The objective of this study is to test a time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR) and to apply it to a set of real high resolution EEG data. This approach will allow the observation of rapidly changing influences between the cortical areas during the execution of a task. The simulation results indicated that time-varying DTF and PDC are able to estimate correctly the imposed connectivity patterns under reasonable operative conditions of signal-to-noise ratio (SNR) ad number of trials. An SNR of Ave and a number of trials of at least 20 provide a good accuracy in the estimation. After testing the method by the simulation study, we provide an application to the cortical estimations obtained from high resolution EEG data recorded from a group of healthy subject during a combined foot-lips movement and present the time-varying connectivity patterns resulting from the application of both DTF and PDC. Two different cortical networks were detected with the proposed methods, one constant across the task and the other evolving during the preparation of the joint movement. View full abstract»

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  • Entropy-Based Optimization of Wavelet Spatial Filters

    Publication Year: 2008 , Page(s): 914 - 922
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (500 KB) |  | HTML iconHTML  

    A new class of spatial filters for surface electromyographic (EMG) signal detection is proposed. These filters are based on the 2-D spatial wavelet decomposition of the surface EMG recorded with a grid of electrodes and inverse transformation after zeroing a subset of the transformation coefficients. The filter transfer function depends on the selected mother wavelet in the two spatial directions. Wavelet parameterization is proposed with the aim of signal-based optimization of the transfer function of the spatial filter. The optimization criterion was the minimization of the entropy of the time samples of the output signal. The optimized spatial filter is linear and space invariant. In simulated and experimental recordings, the optimized wavelet filter showed increased selectivity with respect to previously proposed filters. For example, in simulation, the ratio between the peak-to-peak amplitude of action potentials generated by motor units 20deg apart in the transversal direction was 8.58% (with monopolar recording), 2.47% (double differential), 2.59% (normal double differential), and 0.47% (optimized wavelet filter). In experimental recordings, the duration of the detected action potentials decreased from (mean plusmn SD) 6.9 plusmn 0.3 ms (monopolar recording), to 4.5 plusmn 0.2 ms (normal double differential), 3.7 plusmn 0.2 ms (double differential), and 3.0 plusmn 0.1 ms (optimized wavelet filter). In conclusion, the new class of spatial filters with the proposed signal-based optimization of the transfer function allows better discrimination of individual motor unit activities in surface EMG recordings than it was previously possible. View full abstract»

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  • Error-Related EEG Potentials Generated During Simulated Brain–Computer Interaction

    Publication Year: 2008 , Page(s): 923 - 929
    Cited by:  Papers (47)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1692 KB) |  | HTML iconHTML  

    Brain-computer interfaces (BCIs) are prone to errors in the recognition of subject's intent. An elegant approach to improve the accuracy of BCIs consists in a verification procedure directly based on the presence of error-related potentials (ErrP) in the electroencephalogram (EEG) recorded right after the occurrence of an error. Several studies show the presence of ErrP in typical choice reaction tasks. However, in the context of a BCI, the central question is: ldquoAre ErrP also elicited when the error is made by the interface during the recognition of the subject's intent?rdquo We have thus explored whether ErrP also follow a feedback indicating incorrect responses of the simulated BCI interface. Five healthy volunteer subjects participated in a new human-robot interaction experiment, which seem to confirm the previously reported presence of a new kind of ErrP. However, in order to exploit these ErrP, we need to detect them in each single trial using a short window following the feedback associated to the response of the BCI. We have achieved an average recognition rate of correct and erroneous single trials of 83.5% and 79.2%, respectively, using a classifier built with data recorded up to three months earlier. View full abstract»

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  • EMG-Based Speech Recognition Using Hidden Markov Models With Global Control Variables

    Publication Year: 2008 , Page(s): 930 - 940
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (974 KB) |  | HTML iconHTML  

    It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model. View full abstract»

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  • Multiplicative Correction of Subject Effect as Preprocessing for Analysis of Variance

    Publication Year: 2008 , Page(s): 941 - 948
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (750 KB) |  | HTML iconHTML  

    The procedure of repeated-measures ANOVA assumes the linear model in which effects of both subjects and experimental conditions are additive. However, in electroencephalography and magnetoencephalography, there may be situations where subject effects should be considered to be multiplicative in amplitude. We propose a simple method to normalize such data by multiplying each subject's response by a subject-specific constant. This paper derives ANOVA tables for such normalized data. Present simulations show that this method performs ANOVA effectively including multiple comparisons provided that the data follows the multiplicative model. View full abstract»

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  • Fractional Delay Estimation for Blind Source Separation and Localization of Temporomandibular Joint Sounds

    Publication Year: 2008 , Page(s): 949 - 956
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (562 KB) |  | HTML iconHTML  

    Temporomandibular joint (TMJ) sound sources are generated from the two joints connecting the lower jaw to the temporal bone. Such sounds are important diagnostic signs in patients suffering from temporomandibular disorder (TMD). In this study, we address the problem of source separation of the TMJ sounds. In particular, we examine patients with only one TMJ generating ldquoclicks.rdquo Thereafter, we consider the TMJ sounds recorded from the two auditory canals as mixtures of clicks from the TMD joint and the noise produced by the other healthy/normal TMJ. We next exploit the statistical nonstationary nature of the TMJ signals by employing the degenerate unmixing estimation technique (DUET) algorithm, a time-frequency (T-F) approach to separate the sources. As the DUET algorithm requires the sensors to be closely spaced, which is not satisfied by our recording setup, we have to estimate the delay between the recorded TMJ sounds to perform an alignment of the mixtures. Thus, the proposed extension of DUET enables an essentially arbitrary separation of the sensors. It is also shown that DUET outperforms the convolutive Infomax algorithm in this particular TMJ source separation scenario. The spectra of both separated TMJ sources with our method are comparable to those available in existing literature. Examination of both spectra suggests that the click source has a better audible prominence than the healthy TMJ source. Furthermore, we address the problem of source localization. This can be achieved automatically by detecting the sign of our proposed mutual information estimator which exhibits a maximum at the delay between the two mixtures. As a result, the localized separated TMJ sources can be of great clinical value to dental specialists. View full abstract»

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  • Exploring the Variability of Single Trials in Somatosensory Evoked Responses Using Constrained Source Extraction and RMT

    Publication Year: 2008 , Page(s): 957 - 969
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1311 KB) |  | HTML iconHTML  

    This paper describes the theoretical background of a new data-driven approach to encephalographic single-trial (ST) data analysis. Temporal constrained source extraction using sparse decomposition identifies signal topographies that closely match the shape characteristics of a reference signal, one response for each ST. The correlations between these ST topographies are computed for formal correlation matrix analysis (CMA) based on random matrix theory (RMT). The RMT-CMA provides clusters of similar ST topologies in a completely unsupervised manner. These patterns are then classified into deterministic set and noise using well established RMT results. The efficacy of the method is applied to EEG and MEG data of somatosensory evoked responses (SERs). The results demonstrate that the method can recover brain signals with time course resembling the reference signal and follow changes in strength and/or topography in time by simply stepping the reference signal through time. View full abstract»

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  • Fast Nonlinear Image Reconstruction for Scanning Impedance Imaging

    Publication Year: 2008 , Page(s): 970 - 977
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1051 KB) |  | HTML iconHTML  

    Scanning (electrical) impedance imaging (SII) is a novel high-resolution imaging modality that has the potential of imaging the electrical properties of thin biological tissues. In this paper, we apply the reciprocity principle to the modeling of the SII system and develop a fast nonlinear inverse method for image reconstruction. The method is fast because it uses convolution to eliminate the requirement of a numerical solver for the 3-D electrostatic field in the SII system. Numerical results show that our approach can accurately reveal the exact conductivity distribution from the measured current map for different 2-D simulation phantoms. Experiments were also performed using our SII system for a piece of butterfly wing and breast cancer cells. Two-dimensional current images were measured and corresponding quantitative conductivity images were restored using our approach. The reconstructed images are quantitative and reveal details not present in the measured images. View full abstract»

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  • Validation of Finite Element Models of Liver Tissue Using Micro-CT

    Publication Year: 2008 , Page(s): 978 - 984
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (810 KB) |  | HTML iconHTML  

    In this work, the authors aim at validating some soft tissue deformation models using high-resolution micro-computed tomography (micro-CT) images. The imaging technique plays a key role in detecting the tissue deformation details in the contact region between the tissue and the surgical tool (probe) for small force loads and provides good capabilities of creating accurate 3D models of soft tissues. Surgical simulations rely on accurate representation of the mechanical response of soft tissues subjected to surgical manipulations. Several finite-element models have been suggested to characterize soft tissues. However, validating these models for specific tissues still remain a challenge. In this study, ex vivo lamb liver tissue is chosen to validate the linear elastic model (LEM), the linear viscoelastic model (LVEM), and the neo-Hooke hyperelastic model (NHM). We find that the LEM is more applicable to lamb liver than the LVEM for smaller force loads (<20 g) and that the NHM is closer to reality than the LVEM for the range of force loads from 5 to 40 g. View full abstract»

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  • Quantification of Regional Left Ventricular Dyssynchrony by Magnetic Resonance Imaging

    Publication Year: 2008 , Page(s): 985 - 995
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (815 KB) |  | HTML iconHTML  

    Cardiac resynchronization therapy is an established treatment in patients with symptomatic heart failure and intraventricular conduction delay. Electrical dyssynchrony is typically adopted to represent myocardial activation dyssynchrony, which should be compensated by cardiac resynchronization therapy. One third of the patients, however, does not respond to the therapy. Therefore, imaging modalities aimed at the mechanical dyssynchrony estimation have been recently proposed to improve patient selection criteria. This paper presents a novel fully automated method for regional mechanical left ventricular dyssynchrony quantification in short-axis magnetic resonance imaging. The endocardial movement is described by time-displacement curves with respect to an automatically determined reference point. Different methods are proposed for time-displacement curve analysis aimed at the regional contraction timing estimation. These methods were evaluated in two groups of subjects with (nine patients) and without (six patients) left bundle branch block. The contraction timing standard deviation showed a significant increase for left bundle branch block patients with all the methods. A novel method based on phase spectrum analysis may be however preferred due to a better specificity (99.7%) and sensitivity (99.0%). In conclusion, this method provides a valuable prognostic indicator for heart failure patients with dyssynchronous ventricular contraction and it opens new possibilities for regional timing analysis. View full abstract»

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  • A Novel Angiographic Methodology for the Quantification of Angiogenesis

    Publication Year: 2008 , Page(s): 996 - 1003
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1672 KB) |  | HTML iconHTML  

    The objective is to develop a method to quantify the dynamic information of contrast transport using angiography for investigating angiogenic treatments. In the rabbit hindlimb ischemia model, contrast media transport was examined for both arteries and the microvasculature. Time histories of image intensity were constructed and modeled. The differences in contrast transport quantified by the parameters of the mathematical model were statistically compared between animals treated with an adenoviral vector that expressed vascular endothelial growth factor and untreated animals. The data reveal that after one week of ischemia, treated animals have a statistical increase in the number of large vessels that convect blood more efficiently. This analysis further shows a statistically significant increase in the angiographic blush in the treated animals. A methodology is described that offers the capability of examining the number and geometry of large arteries, the dynamics of contrast transport, and the amount of angiographic blush that is related to microvascular density. In therapeutic angiogenesis, numerous techniques are used to measure variables such as the angiographic score, capillary density, and regional blood flow. The analysis presented herein can offer information of these variables, and is transferable from the laboratory to the clinical arena. View full abstract»

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  • Dynamics of MRI-Guided Thermal Ablation of VX2 Tumor in Paraspinal Muscle of Rabbits

    Publication Year: 2008 , Page(s): 1004 - 1014
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2587 KB) |  | HTML iconHTML  

    This study combines fast magnetic resonance imaging (MRI) and model simulation of tissue thermal ablation for monitoring and predicting the dynamics of lesion size for tumor destruction. In vivo experiments were conducted using radiofrequency (RF) thermal ablation in paraspinal muscle of rabbit with a VX2 tumor. Before ablation, turbo-spin echo (TSE) images visualized the 3-D tumor (necrotic core and tumor periphery) and surrounding normal tissue. MR gradient-recalled echo (GRE) phase and magnitude images were acquired repeatedly in 3.3 s at 30-s intervals during and after thermal ablation to follow tissue temperature distribution dynamics and lesion development in tumor and surrounding normal tissue. Final lesion sizes estimated from GRE magnitude, post-ablation TSE, and stained histologic images were compared. Model simulations of temperature distribution and lesion development dynamics closely corresponded to the experimental data from MR images in tumor and normal tissue. The combined use of MR image monitoring and model simulation has the potential for improving pretreatment planning and real-time prediction of lesion-size dynamics for guidance of thermal ablation of tumors. View full abstract»

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  • Multiple-Instance Learning Algorithms for Computer-Aided Detection

    Publication Year: 2008 , Page(s): 1015 - 1021
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (631 KB) |  | HTML iconHTML  

    Many computer-aided diagnosis (CAD) problems can be best modelled as a multiple-instance learning (MIL) problem with unbalanced data, i.e., the training data typically consists of a few positive bags, and a very large number of negative instances. Existing MIL algorithms are much too computationally expensive for these datasets. We describe CH, a framework for learning a convex hull representation of multiple instances that is significantly faster than existing MIL algorithms. Our CH framework applies to any standard hyperplane-based learning algorithm, and for some algorithms, is guaranteed to find the global optimal solution. Experimental studies on two different CAD applications further demonstrate that the proposed algorithm significantly improves diagnostic accuracy when compared to both MIL and traditional classifiers. Although not designed for standard MIL problems (which have both positive and negative bags and relatively balanced datasets), comparisons against other MIL methods on benchmark problems also indicate that the proposed method is competitive with the state-of-the-art. View full abstract»

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  • Multiscale Penalized Weighted Least-Squares Sinogram Restoration for Low-Dose X-Ray Computed Tomography

    Publication Year: 2008 , Page(s): 1022 - 1031
    Cited by:  Papers (10)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1093 KB) |  | HTML iconHTML  

    In this paper, we propose a novel multiscale penalized weighted least-squares (PWLS) method for restoration of low-dose computed tomography (CT) sinogram. The method utilizes wavelet transform for the multiscale or multiresolution analysis on the sinogram. Specifically, the Mallat-Zhong's wavelet transform is applied to decompose the sinogram to different resolution levels. At each decomposed resolution level, a PWLS criterion is applied to restore the noise-contaminated wavelet coefficients, where the penalty is adaptive to each resolution scale and the weight is updated by an exponential relationship between the data variance and mean at each scale and location. The proposed PWLS method is based on the observations that 1) noise in the CT sinogram after logarithm transform and calibration can be modeled as signal-dependent variables and the sample variance depends on the sample mean by an exponential relationship; and 2) noise reduction can be more effective when it is adaptive to different resolution levels. The effectiveness of the proposed multiscale PWLS method is validated by both computer simulations and experimental studies. The gain by multiscale approach over single scale means is quantified by noise-resolution tradeoff measures. View full abstract»

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  • Tethered Capsule Endoscopy, A Low-Cost and High-Performance Alternative Technology for the Screening of Esophageal Cancer and Barrett's Esophagus

    Publication Year: 2008 , Page(s): 1032 - 1042
    Cited by:  Papers (23)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1468 KB) |  | HTML iconHTML  

    Esophageal cancer is currently the fastest growing cancer in the United States. To help combat the recent rise in morbidity, our laboratory has developed a low-cost tethered capsule endoscope system (TCE) aimed at improving early detection of esophageal cancer. The TCE contains a resonant fiberoptic laser scanner (1.6 mm O.D.) which fits into 6.4-mm easy-to-swallow capsule at the distal tip. The tethered portion contains a single mode optical fiber multiplexed to three laser diodes at the proximal end. This design offers two main advantages over current endoscope technology. First, because of its small size, the TCE can be swallowed with minimal patient discomfort, thereby obviating sedation. Second, by imaging via directed laser light, the TCE is strategically positioned to employ several burgeoning laser-based diagnostic technologies, such as narrow-band, hyperspectral, and fluorescence imaging. It is believed that the combination of such imaging techniques with novel biomarkers of dysplasia will greatly assist in identifying precancerous conditions such as Barrett's esophagus (BE). As the probe is swallowed, the fiber scanner captures high resolution, wide-field color images of the gastroesophageal junction (500 lines at 0.05-mm resolution) currently at 15-Hz frame rate. Video images are recorded as the capsule is slowly retracted by its tether. Accompanying software generates panoramic images from the video output by mosaicing individual frames to aid in pattern recognition. This initial report describes the rationale for the unique TCE system design, results from preliminary testing in vitro and in vivo, and discussion on the merits of this new platform technology as a basis for developing a low-cost screening program for esophageal cancer. View full abstract»

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  • User-Modulated Impedance Control of a Prosthetic Elbow in Unconstrained, Perturbed Motion

    Publication Year: 2008 , Page(s): 1043 - 1055
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1483 KB) |  | HTML iconHTML  

    Humans use the agonist-antagonist structure of their muscles to simultaneously determine both the motion and the stiffness of their joints. Designing this feature into an artificial limb may prove advantageous. To evaluate the performance of an artificial limb capable of modulating its impedance, we have created a compact series elastic actuator that has the same size and similar weight as commercially available electric prosthetic elbows. The inherent compliance in series elastic actuators ensure their safety to the user, even at high speeds, while creating a high-fidelity force actuator ideally suited for impedance control. This paper describes three serial studies that build on each other. The first study presents modeling of the actuator to ensure stability in the range of impedance modulation and empirically tests the actuator to validate its ability to modulate impedance. The actuator is found to be stable and accurate over a wide range of impedances. In the second study, four subjects are tested in a preliminary experiment to answer basic questions necessary to implement user-modulated impedance control. Findings include the superiority of velocity control over position control as the underlying motion paradigm and the preference for high stiffness and non-negative inertia. Based on the findings of the second study, the third study evaluates the performance of 15 able-bodied subjects for two tasks, using five different impedance paradigms. Impedance modulation, speed, and error were compared across paradigms. The results indicate that subjects do not actively modulate impedance if it is near a preferred baseline. Fixed impedance and viscosity modulation provide the most accurate control. View full abstract»

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  • Dynamic Current Density of the Disk Electrode Double-Layer

    Publication Year: 2008 , Page(s): 1056 - 1062
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (533 KB) |  | HTML iconHTML  

    With applied potential, the current distribution at the surface of a disk electrode is spatially nonuniform and time dependent. This distribution is important to control in applications that desire a uniform current density profile or minimal corrosion. We examine the current density profile of a capacitive disk electrode subjected to a voltage-step using finite element analysis software to solve the system of partial differential equations. In detailed analyses we show quantitatively that the current density shifts from peripheral enhancement to near-uniformity following 1/2 of the lumped element time constant. As charging continues, the current density is slightly enhanced in the central region. We present curves for the evolution of local ldquotime constantsrdquo as time progresses and calculate their effective values. The model is intended to be the basis of future work to control the corrosion profile of biologically implantable electrodes of arbitrary shape. Data suggest a means to control corrosion by retarding the edges of a stimulus pulse. Additionally, smaller electrodes may be more effective in fully utilizing surface area for charge transfer due to their shorter time constants. 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