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Biomedical Engineering, IEEE Transactions on

Issue 4 • Date April 2012

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Displaying Results 1 - 25 of 41
  • [Front cover]

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

    Page(s): C2
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  • Table of contents

    Page(s): 897 - 898
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  • Discovering Functional Interdependence Relationship in PPI Networks for Protein Complex Identification

    Page(s): 899 - 908
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1376 KB) |  | HTML iconHTML  

    Protein molecules interact with each other in protein complexes to perform many vital functions, and different computational techniques have been developed to identify protein complexes in protein-protein interaction (PPI) networks. These techniques are developed to search for subgraphs of high connectivity in PPI networks under the assumption that the proteins in a protein complex are highly interconnected. While these techniques have been shown to be quite effective, it is also possible that the matching rate between the protein complexes they discover and those that are previously determined experimentally be relatively low and the “false-alarm” rate can be relatively high. This is especially the case when the assumption of proteins in protein complexes being more highly interconnected be relatively invalid. To increase the matching rate and reduce the false-alarm rate, we have developed a technique that can work effectively without having to make this assumption. The name of the technique called protein complex identification by discovering functional interdependence (PCIFI) searches for protein complexes in PPI networks by taking into consideration both the functional interdependence relationship between protein molecules and the network topology of the network. The PCIFI works in several steps. The first step is to construct a multiple-function protein network graph by labeling each vertex with one or more of the molecular functions it performs. The second step is to filter out protein interactions between protein pairs that are not functionally interdependent of each other in the statistical sense. The third step is to make use of an information-theoretic measure to determine the strength of the functional interdependence between all remaining interacting protein pairs. Finally, the last step is to try to form protein complexes based on the measure of the strength of functional interdependence and the connectivity between proteins. For perfor- ance evaluation, PCIFI was used to identify protein complexes in real PPI network data and the protein complexes it found were matched against those that were previously known in MIPS. The results show that PCIFI can be an effective technique for the identification of protein complexes. The protein complexes it found can match more known protein complexes with a smaller false-alarm rate and can provide useful insights into the understanding of the functional interdependence relationships between proteins in protein complexes. View full abstract»

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  • Semiautomatic Detection of Scoliotic Rib Borders From Posteroanterior Chest Radiographs

    Page(s): 909 - 919
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1832 KB) |  | HTML iconHTML  

    3-D assessment of scoliotic deformities relies on an accurate 3-D reconstruction of bone structures from biplanar X-rays, which requires a precise detection and matching of anatomical structures in both views. In this paper, we propose a novel semiautomated technique for detecting complete scoliotic rib borders from PA-0° and PA-20° chest radiographs, by using an edge-following approach with multiple-path branching and oriented filtering. Edge-following processes are initiated from user starting points along upper and lower rib edges and the final rib border is obtained by finding the most parallel pair among detected edges. The method is based on a perceptual analysis leading to the assumption that no matter how bent a scoliotic rib is, it will always present relatively parallel upper and lower edges. The proposed method was tested on 44 chest radiographs of scoliotic patients and was validated by comparing pixels from all detected rib borders against their reference locations taken from the associated manually delineated rib borders. The overall 2-D detection accuracy was 2.64 ± 1.21 pixels. Comparing this accuracy level to reported results in the literature shows that the proposed method is very well suited for precisely detecting borders of scoliotic ribs from PA-0° and PA-20° chest radiographs. View full abstract»

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  • Multiclass Brain–Computer Interface Classification by Riemannian Geometry

    Page(s): 920 - 928
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (586 KB) |  | HTML iconHTML  

    This paper presents a new classification framework for brain-computer interface (BCI) based on motor imagery. This framework involves the concept of Riemannian geometry in the manifold of covariance matrices. The main idea is to use spatial covariance matrices as EEG signal descriptors and to rely on Riemannian geometry to directly classify these matrices using the topology of the manifold of symmetric and positive definite (SPD) matrices. This framework allows to extract the spatial information contained in EEG signals without using spatial filtering. Two methods are proposed and compared with a reference method [multiclass Common Spatial Pattern (CSP) and Linear Discriminant Analysis (LDA)] on the multiclass dataset IIa from the BCI Competition IV. The first method, named minimum distance to Riemannian mean (MDRM), is an implementation of the minimum distance to mean (MDM) classification algorithm using Riemannian distance and Riemannian mean. This simple method shows comparable results with the reference method. The second method, named tangent space LDA (TSLDA), maps the covariance matrices onto the Riemannian tangent space where matrices can be vectorized and treated as Euclidean objects. Then, a variable selection procedure is applied in order to decrease dimensionality and a classification by LDA is performed. This latter method outperforms the reference method increasing the mean classification accuracy from 65.1% to 70.2%. View full abstract»

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  • High Time-Resolved Cardiac Functional Imaging Using Temporal Regularization for Small Animal on a Clinical 3T Scanner

    Page(s): 929 - 935
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (819 KB) |  | HTML iconHTML  

    Accurate assessment of mice cardiac function with magnetic resonance imaging is essential for longitudinal studies and for drug development related to cardiovascular diseases. Whereas dedicated small animal MR scanners are not readily available, it would be a great advantage to be able to perform cardiac assessment on clinical systems, in particular, in the context of translational research. However, mouse imaging remains challenging since it requires both high spatial and temporal resolutions, while gradient performances of clinical scanners often limit the reachable parameters. In this study, we propose a new cine sequence, named “interleaved cine,” which combines two repetitions of a standard cine sequence shifted in time in order to reach resolution parameters compatible with mice imaging. More precisely, this sequence allows temporal resolution to be reduced to 6.8 ms instead of 13.5 ms initially imposed by the system's hardware. We also propose a two-step denoising algorithm to suppress some artifacts inherent to the new interleaved cine thus allowing an efficient enhancement of the image quality. In particular, we model and suppress the periodic intensity pattern and further denoise the sequence by soft thresholding of the temporal Fourier coefficients. This sequence was successfully validated with mass and function measurements on relevant mice models of cardiovascular diseases. View full abstract»

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  • A TSVD Analysis of Microwave Inverse Scattering for Breast Imaging

    Page(s): 936 - 945
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4262 KB) |  | HTML iconHTML  

    A variety of methods have been applied to the inverse scattering problem for breast imaging at microwave frequencies. While many techniques have been leveraged toward a microwave imaging solution, they are all fundamentally dependent on the quality of the scattering data. Evaluating and optimizing the information contained in the data are, therefore, instrumental in understanding and achieving optimal performance from any particular imaging method. In this paper, a method of analysis is employed for the evaluation of the information contained in simulated scattering data from a known dielectric profile. The method estimates optimal imaging performance by mapping the data through the inverse of the scattering system. The inverse is computed by truncated singular-value decomposition of a system of scattering equations. The equations are made linear by use of the exact total fields in the imaging volume, which are available in the computational domain. The analysis is applied to anatomically realistic numerical breast phantoms. The utility of the method is demonstrated for a given imaging system through the analysis of various considerations in system design and problem formulation. The method offers an avenue for decoupling the problem of data selection from the problem of image formation from that data. View full abstract»

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  • Automated Quantification of the Synchrogram by Recurrence Plot Analysis

    Page(s): 946 - 955
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (916 KB) |  | HTML iconHTML  

    Recently, the concept of phase synchronization of two weakly coupled oscillators has raised a great research interest and has been applied to characterize synchronization phenomenon in physiological data. Phase synchronization of cardiorespiratory coupling is often studied by a synchrogram analysis, a graphical tool investigating the relationship between instantaneous phases of two signals. Although several techniques have been proposed to automatically quantify the synchrogram, most of them require a preselection of a phase-locking ratio by trial and error. One technique does not require this information; however, it is based on the power spectrum of phase's distribution in the synchrogram, which is vulnerable to noise. This study aims to introduce a new technique to automatically quantify the synchrogram by studying its dynamic structure. Our technique exploits recurrence plot analysis, which is a well-established tool for characterizing recurring patterns and nonstationarities in experiments. We applied our technique to detect synchronization in simulated and measured infants' cardiorespiratory data. Our results suggest that the proposed technique is able to systematically detect synchronization in noisy and chaotic data without preselecting the phase-locking ratio. By embedding phase information of the synchrogram into phase space, the phase-locking ratio is automatically unveiled as the number of attractors. View full abstract»

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  • Estimation and Modeling of QT-Interval Adaptation to Heart Rate Changes

    Page(s): 956 - 965
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1276 KB) |  | HTML iconHTML  

    This paper introduces a new method for QT-interval estimation. It consists in a batch processing mode of the improved Woody's method. Performance of this methodology is evaluated using synthetic data. In parallel, a new model of QT-interval dynamics behavior related to heart rate changes is presented. Since two kinds of QT response have been pointed out, the main idea is to split the modeling process into two steps: 1) the modeling of the fast adaptation, which is inspired by the electrical behavior at the cellular level relative to the electrical restitution curve, and 2) the modeling of the slow adaptation, inspired by experimental works at the cellular level. Both approaches are based on a low-complexity autoregressive process whose parameters are estimated using an unbiased estimator. This new modeling of QT adaptation, combined with the presented QT-estimation process, is applied to several ECG recordings with various heart rate variability dynamics. Its potential is then illustrated on ECG recorded during rest, atrial fibrillation episodes, and exercise. Meaningful results in agreement with physiological knowledge at the cellular level are obtained. View full abstract»

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  • A Framework for the Recognition of High-Level Surgical Tasks From Video Images for Cataract Surgeries

    Page(s): 966 - 976
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (717 KB) |  | HTML iconHTML  

    The need for a better integration of the new generation of computer-assisted-surgical systems has been recently emphasized. One necessity to achieve this objective is to retrieve data from the operating room (OR) with different sensors, then to derive models from these data. Recently, the use of videos from cameras in the OR has demonstrated its efficiency. In this paper, we propose a framework to assist in the development of systems for the automatic recognition of high-level surgical tasks using microscope videos analysis. We validated its use on cataract procedures. The idea is to combine state-of-the-art computer vision techniques with time series analysis. The first step of the framework consisted in the definition of several visual cues for extracting semantic information, therefore, characterizing each frame of the video. Five different pieces of image-based classifiers were, therefore, implemented. A step of pupil segmentation was also applied for dedicated visual cue detection. Time series classification algorithms were then applied to model time-varying data. Dynamic time warping and hidden Markov models were tested. This association combined the advantages of all methods for better understanding of the problem. The framework was finally validated through various studies. Six binary visual cues were chosen along with 12 phases to detect, obtaining accuracies of 94%. View full abstract»

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  • Endovascular Magnetically Guided Robots: Navigation Modeling and Optimization

    Page(s): 977 - 987
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (993 KB) |  | HTML iconHTML  

    This paper deals with the benefits of using a nonlinear model-based approach for controlling magnetically guided therapeutic microrobots in the cardiovascular system. Such robots used for minimally invasive interventions consist of a polymer binded aggregate of nanosized ferromagnetic particles functionalized by drug-conjugated micelles. The proposed modeling addresses wall effects (blood velocity in minor and major vessels' bifurcations, pulsatile blood flow and vessel walls, and effect of robot-to-vessel diameter ratio), wall interactions (contact, van der Waals, electrostatic, and steric forces), non-Newtonian behavior of blood, and different driving designs as well. Despite nonlinear and thorough, the resulting model can both be exploited to improve the targeting ability and be controlled in closed-loop using nonlinear control theory tools. In particular, we infer from the model an optimization of both the designs and the reference trajectory to minimize the control efforts. Efficiency and robustness to noise and model parameter's uncertainties are then illustrated through simulations results for a bead pulled robot of radius in a small artery. View full abstract»

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  • Assessment of Cognitive Decline Through Quantitative Analysis of the Timed Up and Go Test

    Page(s): 988 - 995
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (471 KB) |  | HTML iconHTML  

    Cognitive decline and dementia have emerged as major challenges in modern healthcare with enormous associated societal and economic costs. Shifting demographics, owing to increasing numbers of people aged over 65 have greatly increased the potential scale of this problem in years to come. We report a novel quantitative method for assessment of cognitive decline (defined as a decline in mini mental state examination (MMSE) score of three or more) using quantitative parameters derived from body-worn inertial sensors. We sought to determine if baseline quantitative parameters and changes from baseline at follow-up, in those parameters could be used to automatically classify participants as cognitively declined or intact. Quantitative movement parameters were obtained at a baseline clinical assessment and in a follow-up assessment approximately 2 years later, using shank mounted triaxial gyroscopes. Data were obtained from 189 community dwelling older adults (aged over 60, 59 male, 130 female, mean age: 70.43 ± 6.57) while performing the timed up and go test. Nine participants who were deemed to be cognitively impaired at baseline (MMSE <; 24) were excluded from analysis. Results suggest that quantitative parameters measured at baseline are 75.94% accurate in predicting cognitive decline in participants who were cognitively intact at baseline. A combination of baseline quantitative movement parameters and the change at follow-up (compared to baseline) in these parameters were 88.78% accurate in classifying final cognitive status in participants deemed cognitively intact at baseline. The reported method may be suitable for use as a portable cognitive screening tool, prompting further specialist clinical investigation and may also form part of a tool for longitudinal monitoring of cognitive function. View full abstract»

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  • Fully Automated Colon Segmentation for the Computation of Complete Colon Centerline in Virtual Colonoscopy

    Page(s): 996 - 1004
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1500 KB) |  | HTML iconHTML  

    Virtual colonoscopy detects polyps by navigating along a colon centerline. Complete colon segmentation based on computed tomography (CT) data is a prerequisite to the computation of complete colon centerline. There are two main problems impeding complete segmentation: overdistention/underdistention of colon and the use of oral contrast agents. Overdistention produces loops in the segmented colon, while underdistention may cause the segmented colon collapse into a series of disconnected segments. Use of oral contrast agents, which have high attenuation on CT, may add redundant structures (bones and small bowels) to the segmented colon. A fully automated colon segmentation method is proposed in this paper to address the two problems. We tested the proposed method in 170 cases, including 37 “moderate” and 133 “challenging” cases. Computer-generated centerlines were compared with human-generated centerlines (plotted by three radiologists). The proposed method achieved a 90.56% correct coverage rate with respect to the human-generated centerlines. We also compared the proposed method with two existing colon segmentation methods: Uitert's method and Nappi's method. The results of these two methods were 75.16% and 72.59% correct coverage rates, respectively. Our experimental results indicate that the proposed method could yield more complete colon centerlines than the existing methods. View full abstract»

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  • A Design of a High-Speed and High-Efficiency Capsule Endoscopy System

    Page(s): 1005 - 1011
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (857 KB) |  | HTML iconHTML  

    This paper presents a high-speed and high-efficiency capsule endoscopy system. Both a transmitter and a receiver were optimized for its application through an analysis of the human body channel. ON-OFF keying modulation is utilized to achieve low power consumption of the in-body transmitter. A low drop output regulator is adopted to prevent performance degradation in the event of a voltage drop in the battery. The receiver adopts superheterodyne structure to obtain high sensitivity, considering the link budget from the previous analysis. The receiver and transmitter were fabricated using the CMOS 0.13-μm process. The output power of the transmitter is -1.6 dB·m and its efficiency is 27.7%. The minimum sensitivity of the receiver is -80 dB·m at a bit error ratio (BER) of 3 × 10 . An outer wall loop antenna is adopted for the capsule system to ensure a small size. The integrated system is evaluated using a liquid human phantom and a living pig, resulting in clean captured images. View full abstract»

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  • Single-Channel Blind Estimation of Arterial Input Function and Tissue Impulse Response in DCE-MRI

    Page(s): 1012 - 1021
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (593 KB) |  | HTML iconHTML  

    Multipass dynamic MRI and pharmacokinetic modeling are used to estimate perfusion parameters of leaky capillaries. Curve fitting and nonblind deconvolution are the established methods to derive the perfusion estimates from the observed arterial input function (AIF) and tissue tracer concentration function. These nonblind methods are sensitive to errors in the AIF, measured in some nearby artery or estimated by multichannel blind deconvolution. Here, a single-channel blind deconvolution algorithm is presented, which only uses a single tissue tracer concentration function to estimate the corresponding AIF and tissue impulse response function. That way, many errors affecting these functions are reduced. The validity of the algorithm is supported by simulations and tests on real data from mouse. The corresponding nonblind and multichannel methods are also presented. View full abstract»

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  • Automatic Bifurcation Detection in Coronary IVUS Sequences

    Page(s): 1022 - 1031
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (739 KB) |  | HTML iconHTML  

    In this paper, we present a fully automatic method which identifies every bifurcation in an intravascular ultrasound (IVUS) sequence, the corresponding frames, the angular orientation with respect to the IVUS acquisition, and the extension. This goal is reached using a two-level classification scheme: first, a classifier is applied to a set of textural features extracted from each image of a sequence. A comparison among three state-of-the-art discriminative classifiers (AdaBoost, random forest, and support vector machine) is performed to identify the most suitable method for the branching detection task. Second, the results are improved by exploiting contextual information using a multiscale stacked sequential learning scheme. The results are then successively refined using a-priori information about branching dimensions and geometry. The proposed approach provides a robust tool for the quick review of pullback sequences, facilitating the evaluation of the lesion at bifurcation sites. The proposed method reaches an F-Measure score of 86.35%, while the F-Measure scores for inter- and intraobserver variability are 71.63% and 76.18%, respectively. The obtained results are positive. Especially, considering the branching detection task is very challenging, due to high variability in bifurcation dimensions and appearance. View full abstract»

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  • Controlled Aspiration and Positioning of Biological Cells in a Micropipette

    Page(s): 1032 - 1040
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (751 KB) |  | HTML iconHTML  

    Manipulating single cells with a micropipette is the oldest, yet still a widely used technique. This paper discusses the aspiration of a single cell into a micropipette and positioning the cell accurately to a target position inside the micropipette. Due to the small volume of a single cell (picoliter) and nonlinear dynamics involved, these tasks have high skill requirements and are labor intensive in manual operation that is solely based on trial and error and has high failure rates. We present automated techniques in this paper for achieving these tasks via computer vision microscopy and closed-loop motion control. Computer vision algorithms were developed to detect and track a single cell outside and inside a micropipette for automated single-cell aspiration. A closed-loop robust controller integrating the dynamics of cell motion was designed to accurately and efficiently position the cell to a target position inside the micropipette. The system achieved high success rates of 98% for cell detection and 97% for cell tracking (n = 100). The automated system also demonstrated its capability of aspirating a single cell into a micropipette within 2 s (versus 10 s by highly skilled operators) and accurately positioning the cell inside the micropipette within 8 s (versus 25 s by highly skilled operators). View full abstract»

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  • Assurance of Energy Efficiency and Data Security for ECG Transmission in BASNs

    Page(s): 1041 - 1048
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (497 KB) |  | HTML iconHTML  

    With the technological advancement in body area sensor networks (BASNs), low cost high quality electrocardiographic (ECG) diagnosis systems have become important equipment for healthcare service providers. However, energy consumption and data security with ECG systems in BASNs are still two major challenges to tackle. In this study, we investigate the properties of compressed ECG data for energy saving as an effort to devise a selective encryption mechanism and a two-rate unequal error protection (UEP) scheme. The proposed selective encryption mechanism provides a simple and yet effective security solution for an ECG sensor-based communication platform, where only one percent of data is encrypted without compromising ECG data security. This part of the encrypted data is essential to ECG data quality due to its unequally important contribution to distortion reduction. The two-rate UEP scheme achieves a significant additional energy saving due to its unequal investment of communication energy to the outcomes of the selective encryption, and thus, it maintains a high ECG data transmission quality. Our results show the improvements in communication energy saving of about 40%, and demonstrate a higher transmission quality and security measured in terms of wavelet-based weighted percent root-mean-squared difference. View full abstract»

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  • Three-Dimensional Rotation of Mouse Embryos

    Page(s): 1049 - 1056
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (701 KB) |  | HTML iconHTML  

    Research and clinical applications, such as microinjection and polar-body biopsy involve 3-D rotation of mammalian oocytes/embryos. In these cell manipulation tasks, the polar body of an embryo/oocyte must be made visible and properly oriented under optical microscopy. Cell rotation in conventional manual operation by skilled professionals is based on trial and error, such as through repeated vacuum aspiration and release. The randomness of this manual procedure, its poor reproducibility, and inconsistency across operators entail a systematic technique for automated, noninvasive, 3-D rotational control of single cells. This paper reports a system that tracks the polar body of mouse embryos in real time and controls multiple motion control devices to conduct automated 3-D rotational control of mouse embryos. Experimental results demonstrated the system's capability for polar-body orientation with a high success rate of 90%, an accuracy of 1.9, and an average speed of 22.8 s/cell (versus averagely 40 s/cell in manual operation). View full abstract»

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  • Conditions for Worm-Robot Locomotion in a Flexible Environment: Theory and Experiments

    Page(s): 1057 - 1067
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (836 KB) |  | HTML iconHTML  

    Biological vessels are characterized by their substantial compliance and low friction that present a major challenge for crawling robots for minimally invasive medical procedures. Quite a number of studies considered the design and construction of crawling robots; however, very few focused on the interaction between the robots and the flexible environment. In a previous study, we derived the analytical efficiency of worm locomotion as a function of the number of cells, friction coefficients, normal forces, and local (contact) tangential compliance. In this paper, we introduce the structural effects of environment compliance, generalize our previous analysis to include dynamic and static coefficients of friction, determine the conditions of locomotion as function of the external resisting forces, and experimentally validate our previous and newly obtained theoretical results. Our experimental setup consists of worm robot prototypes, flexible interfaces with known compliance and a Vicon motion capture system to measure the robot positioning. Separate experiments were conducted to measure the tangential compliance of the contact interface that is required for computing the analytical efficiency. The validation experiments were performed for both types of compliant conditions, local and structural, and the results are shown to be in clear match with the theoretical predictions. Specifically, the convergence of the tangential deflections to an arithmetic series and the partial and overall loss of locomotion verify the theoretical predictions. View full abstract»

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  • Electromechanical Design and Construction of a Rotating Radio-Frequency Coil System for Applications in Magnetic Resonance

    Page(s): 1068 - 1075
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (754 KB) |  | HTML iconHTML  

    While recent studies have shown that rotating a single radio-frequency (RF) coil during the acquisition of magnetic resonance (MR) images provides a number of hardware advantages (i.e., requires only one RF channel, avoids coil-coil coupling and facilitates large-scale multinuclear imaging), they did not describe in detail how to build a rotating RF coil system. This paper presents detailed engineering information on the electromechanical design and construction of a MR-compatible RRFC system for human head imaging at 2 T. A custom-made (bladeless) pneumatic Tesla turbine was used to rotate the RF coil at a constant velocity, while an infrared optical encoder measured the selected frequency of rotation. Once the rotating structure was mechanically balanced and the compressed air supply suitably regulated, the maximum frequency of rotation measured ~14.5 Hz with a 2.4% frequency variation over time. MR images of a water phantom and human head were obtained using the rotating RF head coil system. View full abstract»

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  • Experimental Characterization and Numerical Modeling of Tissue Electrical Conductivity during Pulsed Electric Fields for Irreversible Electroporation Treatment Planning

    Page(s): 1076 - 1085
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (849 KB) |  | HTML iconHTML  

    Irreversible electroporation is a new technique to kill cells in targeted tissue, such as tumors, through a nonthermal mechanism using electric pulses to irrecoverably disrupt the cell membrane. Treatment effects relate to the tissue electric field distribution, which can be predicted with numerical modeling for therapy planning. Pulse effects will change the cell and tissue properties through thermal and electroporation (EP)-based processes. This investigation characterizes these changes by measuring the electrical conductivity and temperature of ex vivo renal porcine tissue within a single pulse and for a 200 pulse protocol. These changes are incorporated into an equivalent circuit model for cells and tissue with a variable EP-based resistance, providing a potential method to estimate conductivity as a function of electric field and pulse length for other tissues. Finally, a numerical model using a human kidney volumetric mesh evaluated how treatment predictions vary when EP- and temperature-based electrical conductivity changes are incorporated. We conclude that significant changes in predicted outcomes will occur when the experimental results are applied to the numerical model, where the direction and degree of change varies with the electric field considered. View full abstract»

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  • Three-Dimensional Statistical Model for Gingival Contour Reconstruction

    Page(s): 1086 - 1093
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (6590 KB) |  | HTML iconHTML  

    Optimal gingival contours around restored teeth and implants are of critical importance for restorative success and esthetics. This paper describes a novel computer-aided methodology for building a 3-D statistical model of gingival contours from a 3-D scan dental dataset and reconstructing missing gingival contours in partially edentulous patients. The gingival boundaries were first obtained from the 3-D dental model through a discrete curvature analysis and shortest path searching algorithm. Based on the gingival shape differential characteristics, the boundaries were demarcated to construct the gingival contour of each individual tooth. Through B-spline curve approximation to each gingival contour, the control points of the B-spline curves are used as the shape vector for training the model. Statistical analysis results demonstrate that the method can give a simple but compact model that effectively capture the most important variations in arch width and shape as well as gingival morphology and position. Within this statistical model, the morphologically plausible missing contours can be inferred based on a nonlinear optimization fitting from the global similarity transformation, the model shape deformation and a Mahalanobis prior. The reconstruction performance is evaluated through large simulated experimental data and a real patient case, which demonstrates the effectiveness of this approach. View full abstract»

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  • Invariant Density Analysis: Modeling and Analysis of the Postural Control System Using Markov Chains

    Page(s): 1094 - 1100
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (483 KB) |  | HTML iconHTML  

    In this paper, a novel analysis technique, invariant density analysis (IDA), is introduced. IDA quantifies steady-state behavior of the postural control system using center of pressure (COP) data collected during quiet standing. IDA relies on the analysis of a reduced-order finite Markov model to characterize stochastic behavior observed during postural sway. Five IDA parameters characterize the model and offer physiological insight into the long-term dynamical behavior of the postural control system. Two studies were performed to demonstrate the efficacy of IDA. Study 1 showed that multiple short trials can be concatenated to create a dataset suitable for IDA. Study 2 demonstrated that IDA was effective at distinguishing age-related differences in postural control behavior between young, middle-aged, and older adults. These results suggest that the postural control system of young adults converges more quickly to their steady-state behavior while maintaining COP nearer an overall centroid than either the middle-aged or older adults. Additionally, larger entropy values for older adults indicate that their COP follows a more stochastic path, while smaller entropy values for young adults indicate a more deterministic path. These results illustrate the potential of IDA as a quantitative tool for the assessment of the quiet-standing postural control system. 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