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Biomedical Engineering, IEEE Transactions on

Issue 9 • Date Sept. 2007

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Displaying Results 1 - 25 of 27
  • Table of contents

    Publication Year: 2007 , Page(s): C1 - C4
    Save to Project icon | Request Permissions | PDF file iconPDF (114 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Biomedical Engineering publication information

    Publication Year: 2007 , Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (39 KB)  
    Freely Available from IEEE
  • Mixed-Band Wavelet-Chaos-Neural Network Methodology for Epilepsy and Epileptic Seizure Detection

    Publication Year: 2007 , Page(s): 1545 - 1551
    Cited by:  Papers (70)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (651 KB) |  | HTML iconHTML  

    A novel wavelet-chaos-neural network methodology is presented for classification of electroencephalograms (EEGs) into healthy, ictal, and interictal EEGs. Wavelet analysis is used to decompose the EEG into delta, theta, alpha, beta, and gamma sub-bands. Three parameters are employed for EEG representation: standard deviation (quantifying the signal variance), correlation dimension, and largest Lyapunov exponent (quantifying the non-linear chaotic dynamics of the signal). The classification accuracies of the following techniques are compared: 1) unsupervised-means clustering; 2) linear and quadratic discriminant analysis; 3) radial basis function neural network; 4) Levenberg-Marquardt backpropagation neural network (LMBPNN). To reduce the computing time and output analysis, the research was performed in two phases: band-specific analysis and mixed-band analysis. In phase two, over 500 different combinations of mixed-band feature spaces consisting of promising parameters from phase one of the research were investigated. It is concluded that all three key components of the wavelet-chaos-neural network methodology are important for improving the EEG classification accuracy. Judicious combinations of parameters and classifiers are needed to accurately discriminate between the three types of EEGs. It was discovered that a particular mixed-band feature space consisting of nine parameters and LMBPNN result in the highest classification accuracy, a high value of 96.7%. View full abstract»

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  • Pulse Morphology Visualization and Analysis With Applications in Cardiovascular Pressure Signals

    Publication Year: 2007 , Page(s): 1552 - 1559
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1178 KB) |  | HTML iconHTML  

    We present a new analysis and visualization method for studying the functional relationship between the pulse morphology of pressure signals and time or signal metrics such as heart rate, pulse pressure, and means of pressure signals, such as arterial blood pressure and central venous pressure. The pulse morphology is known to contain potentially useful clinical information, but it is difficult to study in the time domain without the aid of a tool such as the method we present here. The primary components of the method are established signal processing techniques, nonparametric regression, and an automatic beat detection algorithm. Some of the insights that can be gained from this are demonstrated through the analysis of intracranial pressure signals acquired from patients with traumatic brain injuries. The analysis indicates the point of transition from low-pressure morphology consisting of three distinct peaks to a high-pressure morphology consisting of a single peak. In addition, we demonstrate how the analysis can reveal distinctions in the relationship between morphology and several signal metrics for different patients. View full abstract»

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  • Automatic Identification and Removal of Scalp Reference Signal for Intracranial EEGs Based on Independent Component Analysis

    Publication Year: 2007 , Page(s): 1560 - 1572
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2462 KB) |  | HTML iconHTML  

    The pursuit of an inactive recording reference is one of the oldest technical problems in electroencephalography (EEG). Since commonly used cephalic references contaminate EEG and can lead to misinterpretation, extraction of the reference contribution is of fundamental interest. Here, we apply independent component analysis (ICA) to intracranial recordings and propose two methods to automatically identify and remove the reference based on the assumption that the scalp reference is independent from the local and distributed intracranial sources. This assumption, supported by our results, is generally valid because the reference scalp electrode is relatively electrically isolated from the intracranial electrodes by the skull's high resistivity. We point out that the linear model is underdetermined when the reference is considered as a source, and discuss one special underdetermined case for which a unique class of outputs can be separated. For this case most ICA algorithms can be applied, and we argue that intracranial or scalp EEGs follow this special case. We apply the two proposed methods to intracranial EEGs from three patients undergoing evaluation for epilepsy surgery, and compare the results to bipolar and average reference recordings. The proposed methods should have wide application in quantitative EEG studies. View full abstract»

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  • Evaluation of Respiratory Muscles Activity by Means of Cross Mutual Information Function at Different Levels of Ventilatory Effort

    Publication Year: 2007 , Page(s): 1573 - 1582
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2035 KB) |  | HTML iconHTML  

    Analysis of respiratory muscles activity is an effective technique for the study of pulmonary diseases such as obstructive sleep apnea syndrome (OSAS). Respiratory diseases, especially those associated with changes in the mechanical properties of the respiratory apparatus, are often associated with disruptions of the normally highly coordinated contractions of respiratory muscles. Due to the complexity of the respiratory control, the assessment of OSAS related dysfunctions by linear methods are not sufficient. Therefore, the objective of this study was the detection of diagnostically relevant nonlinear complex respiratory mechanisms. Two aims of this work were: 1) to assess coordination of respiratory muscles contractions through evaluation of interactions between respiratory signals and myographic signals through nonlinear analysis by means of cross mutual information function (CMIF); 2) to differentiate between functioning of respiratory muscles in patients with OSAS and in normal subjects. Electromyographic (EMG) and mechanomyographic (MMG) signals were recorded from three respiratory muscles: genioglossus, sternomastoid and diaphragm. Inspiratory pressure and flow were also acquired. All signals were measured in eight patients with OSAS and eight healthy subjects during an increased respiratory effort while awake. Several variables were defined and calculated from CMIF in order to describe correlation between signals. The results indicate different nonlinear couplings of respiratory muscles in both populations. This effect is progressively more evident at higher levels of respiratory effort. View full abstract»

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  • Estimation of Muscle Fiber Conduction Velocity With a Spectral Multidip Approach

    Publication Year: 2007 , Page(s): 1583 - 1589
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (375 KB) |  | HTML iconHTML  

    We propose a novel method for estimation of muscle fiber conduction velocity from surface electromyographic (EMG) signals. The method is based on the regression analysis between spatial and temporal frequencies of multiple dips introduced in the EMG power spectrum through the application of a set of spatial filters. This approach leads to a closed analytical expression of conduction velocity as a function of the auto- and cross-spectra of monopolar signals detected along the direction of muscle fibers. The performance of the algorithm was compared with respect to that of the classic single dip approach on simulated and experimental EMG signals. The standard deviation of conduction velocity estimates from simulated single motor unit action potentials was reduced from 1.51 m/s [10 dB signal-to-noise ratio (SNR)] and 1.06 m/s (20 dB SNR) with the single dip approach to 0.51 m/s (10 dB) and 0.23 m/s (20 dB) with the proposed method using 65 dips. When 200 active motor units were simulated in an interference EMG signal, standard deviation of conduction velocity decreased from 0.95 m/s (10 dB SNR) and 0.60 m/s (20 dB SNR) with a single dip to 0.21 m/s (10 dB) and 0.11 m/s (20 dB) with 65 dips. In experimental signals detected from the abductor pollicis brevis muscle, standard deviation of estimation decreased from (mean plusmn SD over 5 subjects) 1.25 plusmn 0.62 m/s with one dip to 0.10 plusmn 0.03 m/s with 100 dips. The proposed method does not imply limitation in resolution of the estimated conduction velocity and does not require any iterative procedure for the estimate since it is based on a closed analytical formulation. View full abstract»

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  • A New Heart Rate Variability Analysis Method by Means of Quantifying the Variation of Nonlinear Dynamic Patterns

    Publication Year: 2007 , Page(s): 1590 - 1597
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (766 KB) |  | HTML iconHTML  

    A new heart rate variability (HRV) analysis method, quantifying the variation of nonlinear dynamic pattern (VNDP) in heart rate series, is proposed and validated against the age stratified Fantasia database. The method is based on three processes: 1) a recurrence quantification analysis (RQA) to quantify the dynamic patterns, 2) the use of mutual information (MI) and the entropy (EN) to characterize the VNDP, and 3) linear discriminant analysis to exploit the associations within MI and EN measures. Practically, the VNDP method overcomes the nonstationarity problem and exploits the nonstationary properties in HRV analyses. Physiologically, the VNDP reflects the properties of the fundamental short-term HRV dynamic system and the external associations of the system within the autonomous nervous system (ANS). The characteristic probability density peaks portrayed by VNDP plots indicate the quantum-like heart dynamics, which may provide valuable insights into the control of the ANS. The discrimination results of the reduced pattern dynamic range due to aging, from a new perspective, display the reduction in HRV. The significantly improved discriminatory power, compared to conventional RQA analyses, shows that the VNDP analysis can practically quantify the nonstationary nonlinear dynamics for ANS assessments. View full abstract»

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  • Design of a Wire-Mesh Collimator for Gamma Cameras

    Publication Year: 2007 , Page(s): 1598 - 1612
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2435 KB) |  | HTML iconHTML  

    This paper presents a model of a wire-mesh collimator for a gamma camera that produces images of comparable quality as those produced with the conventional multihole collimator, but has about half the weight of the multihole collimator. The gamma camera and the collimator are simulated using the MCNPX code. Two final configurations of the wire-mesh collimator are proposed, and their performance is compared with other wire-mesh collimators and with the multihole collimator, using a point source, a planar square source, and two point sources, all in water. In all cases, photons with energy 140 keV are simulated. In addition, we use the simulation of a realistic phantom of a hot tumor in a warm background to assess the performance of our collimator in conjunction with an extended source. View full abstract»

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  • Theoretical Limits of Localizing 3-D Landmarks and Features

    Publication Year: 2007 , Page(s): 1613 - 1620
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (564 KB) |  | HTML iconHTML  

    In this paper, we analyze the accuracy of estimating the location of 3D landmarks and characteristic image structures. Based on nonlinear estimation theory, we study the minimal stochastic errors of the position estimate caused by noisy data. Given analytic models of the image intensities, we derive closed-form expressions of the Cramer-Rao bound for different 3D structures such as 3D edges, 3D ridges, 3D lines, 3D boxes, and 3D blobs. It turns out that the precision of localization depends on the noise level, the size of the region-of-interest, the image contrast, the width of the intensity transitions, as well as on other parameters describing the considered image structure. The derived lower bounds can serve as benchmarks and the performance of existing algorithms can be compared with them. To give an impression of the achievable accuracy, numeric examples are presented. Moreover, by experimental investigations, we demonstrate that the derived lower bounds can be achieved by fitting parametric intensity models directly to the image data. View full abstract»

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  • fMRI Data Analysis With Nonstationary Noise Models: A Bayesian Approach

    Publication Year: 2007 , Page(s): 1621 - 1630
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (628 KB) |  | HTML iconHTML  

    The assumption of noise stationarity in the functional magnetic resonance imaging (fMRI) data analysis may lead to the loss of crucial dynamic features of the data and thus result in inaccurate activation detection. In this paper, a Bayesian approach is proposed to analyze the fMRI data with two nonstationary noise models (the time-varying variance noise model and the fractional noise model). The covariance matrices of the time-varying variance noise and the fractional noise after wavelet transform are diagonal matrices. This property is investigated under the Bayesian framework. The Bayesian estimator not only gives an accurate estimate of the weights in general linear model, but also provides posterior probability of activation in a voxel and, hence, avoids the limitations (i.e., using only hypothesis testing) in the classical methods. The performance of the proposed Bayesian methods (under the assumption of different noise models) are compared with the ordinary least squares (OLS) and the weighted least squares (WLS) methods. Results from the simulation studies validate the superiority of the proposed approach to the OLS and WLS methods considering the complex noise structures in the fMRI data. View full abstract»

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  • The Removal of Wall Components in Doppler Ultrasound Signals by Using the Empirical Mode Decomposition Algorithm

    Publication Year: 2007 , Page(s): 1631 - 1642
    Cited by:  Papers (29)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1824 KB) |  | HTML iconHTML  

    Doppler ultrasound systems, used for the noninvasive detection of the vascular diseases, normally employ a high-pass filter (HPF) to remove the large, low-frequency components from the vessel wall from the blood flow signal. Unfortunately, the filter also removes the low-frequency Doppler signals arising from slow-moving blood. In this paper, we propose to use a novel technique, called the empirical mode decomposition (EMD), to remove the wall components from the mixed signals. The EMD is firstly to decompose a signal into a finite and usually small number of individual components named intrinsic mode functions (IMFs). Then a strategy based on the ratios between two adjacent values of the wall-to-blood signal ratio (WBSR) has been developed to automatically identify and remove the relevant IMFs that contribute to the wall components. This method is applied to process the simulated and clinical Doppler ultrasound signals. Compared with the results based on the traditional high-pass filter, the new approach obtains improved performance for wall components removal from the mixed signals effectively and objectively, and provides us with more accurate low blood flow. View full abstract»

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  • Comparison of Applied and Induced Current Electrical Impedance Tomography

    Publication Year: 2007 , Page(s): 1643 - 1649
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (676 KB) |  | HTML iconHTML  

    Several papers on induced current electrical impedance tomography (IC-EIT) have dwelt on potential advantages of this technique over conventional EIT which uses applied current (AC-EIT). Experimental evidence that IC-EIT could surpass AC-EIT in similar imaging conditions is lacking. In this paper, we describe a system that can switch rapidly between both AC-EIT and IC-EIT. The system makes it possible to image objects in a saline-Ailed tank, providing data acquired in identical test conditions for comparing the performance of the two modes. The system uses eight circular coils and 16 electrodes to acquire 120 linearly independent measurements in IC-EIT and 104 in AC-EIT. Difference images were reconstructed from data acquired with both modes using the maximum a posteriori method. Spatial resolution was lower in IC-EIT images than in AC-EIT, especially in the radial direction. IC-EIT also exhibits a bias toward the center for positioning a conductivity perturbation. These results were obtained for a typical coil configuration widely used in the literature and may not be representative of alternate coil configurations. The system described in this paper provides stable experimental conditions for comparing the performance of the two EIT imaging modes and would be a valuable tool for validating new coil configurations. View full abstract»

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  • Real-Time Monitoring of Cardiac Regional Function Using FastHARP MRI and Region-of-Interest Reconstruction

    Publication Year: 2007 , Page(s): 1650 - 1656
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1365 KB) |  | HTML iconHTML  

    Cardiovascular stress test imaging assists in the diagnosis and monitoring of cardiovascular disease. The procedure can be carried out in a magnetic resonance (MR) scanner using pharmacological agents that mimic the effects of natural exercise. In order to provide real time indication of ischemia, thereby assisting in diagnosis and helping to assure patient safety, it is desirable to have real time monitoring of the myocardial regional function. This paper presents an algorithm for the real time myocardium region-of-interest reconstruction and myocardial strain computation using data acquired from a real time pulse sequence that has been previously reported. The chirp Fourier transform is used for efficient computation, enabling a real-time continuous strain map at a rate of 25 frames/s. Coupled with a real time data path from the scanner to a laptop computer, this algorithm enables real time continuous monitoring of cardiac strain and is targeted for use in the early detection and quantification of ischemia during MR stress tests. View full abstract»

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  • Prototype Fabrication and Preliminary In Vitro Testing of a Shape Memory Endovascular Thrombectomy Device

    Publication Year: 2007 , Page(s): 1657 - 1666
    Cited by:  Papers (13)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1867 KB) |  | HTML iconHTML  

    An electromechanical microactuator comprised of shape memory polymer (SMP) and shape memory nickel-titanium alloy (nitinol) was developed and used in an endovascular thrombectomy device prototype. The microactuator maintains a straight rod shape until an applied current induces electro-resistive (Joule) heating, causing the microactuator to transform into a corkscrew shape. The straight-to-corkscrew transformation geometry was chosen to permit endovascular delivery through (straight form) and retrieval of (corkscrew form) a stroke-causing thrombus (blood clot) in the brain. Thermal imaging of the microactuator during actuation in air indicated that the steady-state temperature rise caused by Joule heating varied quadratically with applied current and that actuation occurred near the glass transition temperature of the SMP (86degC). To demonstrate clinical application, the device was used to retrieve a blood clot in a water-filled silicone neurovascular model. Numerical modeling of the heat transfer to the surrounding blood and associated thermal effects on the adjacent artery potentially encountered during clinical use suggested that any thermal damage would likely be confined to localized areas where the microactuator was touching the artery wall. This shape memory mechanical thrombectomy device is a promising tool for treating ischemic stroke without the need for infusion of clot-dissolving drugs. View full abstract»

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  • A Multiobjective Design of a Patient and Anaesthetist-Friendly Neuromuscular Blockade Controller

    Publication Year: 2007 , Page(s): 1667 - 1678
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (783 KB) |  | HTML iconHTML  

    During surgeries (especially in long ones), patients are subject to a substantial amount of drug dosage necessary to achieve the required neuromuscular blockade level. This paper aims at the development of a fuzzy controller that satisfies two important goals: 1) an optimization of the amount of drug (atracurium) required to induce an adequate level of relaxation and 2) a concomitant ability to explain the undertaken control decision at the level of natural language. For instance, statements of the form ldquoSince the difference between the target and the current blockade level is near zero, a small quantity of drug infusion is currently being applied,rdquo where ldquonear zerordquo and ldquosmallrdquo are linguistic terms that are represented as fuzzy sets. In this sense, we can regard this controller as a construct that is human friendly and highly interpretable (transparent). To address the two objectives outlined above, we consider the use of a multiobjective evolutionary optimization. How the quality of the control action and the controller interpretability are formalized and captured in this optimization framework is presented. The effectiveness of the approach is demonstrated through a comprehensive suite of experiments involving 100 simulated patients (used for training) and 500 patients (forming the test set), validating the approach for application in the operating theater. View full abstract»

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  • Testing the Immunity of Active Implantable Medical Devices to CW Magnetic Fields up to 1 MHz by an Immersion Method

    Publication Year: 2007 , Page(s): 1679 - 1686
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (792 KB) |  | HTML iconHTML  

    This paper presents a magnetic-field system and the method developed for testing the immunity of the active implantable medical devices to continuous-wave magnetic fields in the frequency range up to 1 MHz. The system is able to produce magnetic fields of 150 A/m for frequencies up to 100 kHz and strengths decreasing as l/f between 100 kHz and 1 MHz, with uniformity of the field within plusmn2.5% in the volume for tests. To simulate human tissue, the medical device, together with its leads, is placed on a plastic grid in a saline tank that is introduced in the magnetic field of the induction coil. This paper offers an alternative for the injection voltage methods provided in the actual standards for assessing the protection of the implantable medical devices from the effects of the magnetic fields up to 1 MHz. This paper presents the equipment and signals used, the test procedure, and results from the preliminary tests performed at the Food and Drug Administration-Center for Devices and Radiological Health on implantable pacemakers and neurostimulators. The new system and test method are useful for the EMC research on the implantable medical devices. View full abstract»

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  • Design of patient-specific gait modifications for knee osteoarthritis rehabilitation

    Publication Year: 2007 , Page(s): 1687 - 1695
    Cited by:  Papers (47)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1192 KB)  

    Gait modification is a nonsurgical approach for reducing the external knee adduction torque in patients with knee osteoarthritis (OA). The magnitude of the first adduction torque peak in particular is strongly associated with knee OA progression. While toeing out has been shown to reduce the second peak, no clinically realistic gait modifications have been identified that effectively reduce both peaks simultaneously. This study predicts novel patient-specific gait modifications that achieve this goal without changing the foot path. The modified gait motion was designed for a single patient with knee OA using dynamic optimization of a patient-specific, full-body gait model. The cost function minimized the knee adduction torque subject to constraints limiting how much the new gait motion could deviate from the patient's normal gait motion. The optimizations predicted a ldquomedial-thrustrdquo gait pattern that reduced the first adduction torque peak between 32% and 54% and the second peak between 34% and 56%. The new motion involved three synergistic kinematic changes: slightly decreased pelvis obliquity, slightly increased leg flexion, and slightly increased pelvis axial rotation. After gait retraining, the patient achieved adduction torque reductions of 39% to 50% in the first peak and 37% to 55% in the second one. These reductions are comparable to those reported after high tibial osteotomy surgery. The associated kinematic changes were consistent with the predictions except for pelvis obliquity, which showed little change. This study demonstrates that it is feasible to design novel patient-specific gait modifications with potential clinical benefit using dynamic optimization of patient-specific, full-body gait models. Further investigation is needed to assess the extent to which similar gait modifications may be effective for other patients with knee OA. View full abstract»

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  • Robotic Platform for Human Gait Analysis

    Publication Year: 2007 , Page(s): 1696 - 1702
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (681 KB) |  | HTML iconHTML  

    A hydraulically actuated platform with 4-degrees of freedom (4-DOF) was designed to be able to apply velocity- or acceleration-controlled floor surface perturbations to freely walking human subjects. The apparatus was required to provide velocity-controlled translational perturbations over the floor surface, rotational perturbations about the ankle joint, and acceleration-controlled vertical translational perturbations. The apparatus was physically constructed, and tested by both measurements of dynamics and repeatability. Crossover of movement from one DOF to another was shown to be less than 1 mm or 0.5deg for all desired perturbations. Repeated perturbations were nearly identical with a standard deviation of less than 0.2 mm over translational axes. The application of the platform to human gait research was demonstrated with a protocol of midstance phase perturbations (n = 8). For this, the platform controller was programmed to randomly select one out of three conditions: 1) no movement (control); 2) upward perturbation of 0.8 g, 50 mm, 300 ms after heel contact; 3) downward perturbation of 0.8 g, 50 mm, 300 ms after heel contact. In total, 90 trials (3 conditions times 30 repetitions) were recorded for each subject. By singling out the SOL EMG and normalizing and averaging over the subject population, it was shown that the upward and downward perturbations elicited at least two distinctive stereotypical reflex responses in the ankle extensors, opposite in sign. All subjects reported comfort with the apparatus and nobody fell. View full abstract»

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  • Fluoroscopic Bone Fragment Tracking for Surgical Navigation in Femur Fracture Reduction by Incorporating Optical Tracking of Hip Joint Rotation Center

    Publication Year: 2007 , Page(s): 1703 - 1706
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (797 KB) |  | HTML iconHTML  

    A new method for fluoroscopic tracking of a proximal bone fragment in femoral fracture reduction is presented. The proposed method combines 2-D and 3-D image registration from single-view fluoroscopy with tracking of the head center position of the proximal femoral fragment to improve the accuracy of fluoroscopic registration without the need for repeated manual adjustment of the C-arm as required in stereo-view registrations. Kinematic knowledge of the hip joint, which has a positional correspondence with the femoral head center and the pelvis acetabular center, allows the position of the femoral fragment to be determined from pelvis tracking. The stability of the proposed method with respect to fluoroscopic image noise and the desired continuity of the fracture reduction operation is demonstrated, and the accuracy of tracking is shown to be superior to that achievable by single-view image registration, particularly in depth translation. View full abstract»

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  • Redefining Performance Evaluation Tools for Real-Time QRS Complex Classification Systems

    Publication Year: 2007 , Page(s): 1706 - 1710
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (301 KB) |  | HTML iconHTML  

    In a heartbeat classification procedure, the detection of QRS complex waveforms is necessary. In many studies, this heartbeat extraction function is not considered: the inputs of the classifier are assumed to be correctly identified. This communication aims to redefine classical performance evaluation tools in entire QRS complex classification systems and to evaluate the effects induced by QRS detection errors on the performance of heartbeat classification processing (normal versus abnormal). Performance statistics are given and discussed considering the MIT/BIH database records that are replayed on a real-time classification system composed of the classical detector proposed by Hamilton and Tompkins, followed by a neural-network classifier. This study shows that a classification accuracy of 96.72% falls to 94.90% when a drop of 1.78% error rate is introduced in the detector quality. This corresponds to an increase of about 50% bad classifications. View full abstract»

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  • Phase Resetting in One-Dimensional Model of the Sinoatrial Node

    Publication Year: 2007 , Page(s): 1710 - 1714
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (233 KB) |  | HTML iconHTML  

    In this paper, we use a one-dimensional model of the rabbit sinoatrial node (SAN), and we investigate the response of the model to hyperpolarizing and depolarizing stimulus. Depending on the stimulus timing, either a delay or an advance in the occurrence of next action potential is produced. This resetting behavior of the model is quantified in terms of phase transition curves (PTCs) for short electrical current pulses of varying amplitude which span the whole period. The main focus of this paper is to compare the dynamic properties of the spatially extended system and the single cell model. The detailed analysis of the results provides new insights in the understanding of the transition from the theoretical single cell models to the spatially extended systems. View full abstract»

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  • A Hybrid Classifier Fusion Approach for Motor Unit Potential Classification During EMG Signal Decomposition

    Publication Year: 2007 , Page(s): 1715 - 1721
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (308 KB) |  | HTML iconHTML  

    In this paper, we propose a hybrid classifier fusion scheme for motor unit potential classification during electromyographic (EMG) signal decomposition. The scheme uses an aggregator module consisting of two stages of classifier fusion: the first at the abstract level using class labels and the second at the measurement level using confidence values. Performance of the developed system was evaluated using one set of real signals and two sets of simulated signals and was compared with the performance of the constituent base classifiers and the performance of a one-stage classifier fusion approach. Across the EMG signal data sets used and relative to the performance of base classifiers, the hybrid approach had better average classification performance overall. For the set of simulated signals of varying intensity, the hybrid classifier fusion system had on average an improved correct classification rate (CCr) (6.1%) and reduced error rate (Er) (0.4%). For the set of simulated signals of varying amounts of shape and/or firing pattern variability, the hybrid classifier fusion system had on average an improved CCr (6.2%) and reduced Er (0.9%). For real signals, the hybrid classifier fusion system had on average an improved CCr (7.5%) and reduced Er (1.7%). View full abstract»

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  • A Shape Memory Polymer Dialysis Needle Adapter for the Reduction of Hemodynamic Stress Within Arteriovenous Grafts

    Publication Year: 2007 , Page(s): 1722 - 1724
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1894 KB) |  | HTML iconHTML  

    A deployable, shape memory polymer adapter is investigated for reducing the hemodynamic stress caused by dialysis needle flow impingement within an arteriovenous graft. Computational fluid dynamics simulations of dialysis sessions with and without the adapter demonstrate that the adapter provides a significant decrease in the wall shear stress. Preliminary in vitro flow visualization measurements are made within a graft model following delivery and actuation of a prototype shape memory polymer adapter. Both the simulations and the qualitative flow visualization measurements demonstrate that the adapter reduces the severity of the dialysis needle flow impingement on the vascular access graft. View full abstract»

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  • Origin of the Radio Frequency Pulse Artifact in Simultaneous EEG-fMRI Recording: Rectification at the Carbon-Metal Interface

    Publication Year: 2007 , Page(s): 1725 - 1727
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (104 KB) |  | HTML iconHTML  

    Simultaneous electroencephalograph-functional magnetic resonance imaging (EEG-fMRI ) recording has become an important tool for investigating spatiotemporal properties of brain events, such as epilepsy, evoked brain responses, and changes in brain rhythms. Reduction of noise in EEG signals during fMRI recording is crucial for acquiring high-quality EEG-fMRI data. The main source of the noise includes the gradient artifact, the radio frequency (RF) pulse artifact, and the cardiac pulse artifact. Since the RF pulse artifact is relatively small in amplitude, little attention has been paid to this artifact, and its origin is not well understood. However, the amplitude of the RF pulse artifact fluctuates randomly even if a very high EEG sampling rate is used, making it more salient than the gradient artifact after postprocessing for noise removal. In this paper, we investigate the cause of the RF pulse artifact in EEG systems that use carbon wires. View full abstract»

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IEEE Transactions on Biomedical Engineering contains basic and applied papers dealing with biomedical engineering. Papers range from engineering development in methods and techniques with biomedical applications to experimental and clinical investigations with engineering contributions.

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Bin He
Department of Biomedical Engineering