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Biomedical Engineering, IEEE Transactions on

Issue 1 • Date Jan. 2008

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Displaying Results 1 - 25 of 54
  • Table of contents

    Publication Year: 2008 , Page(s): C1 - 2
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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
  • Computationally Efficient Strategy for Modeling the Effect of Ion Current Modifiers

    Publication Year: 2008 , Page(s): 3 - 13
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (681 KB) |  | HTML iconHTML  

    Electrophysiological studies often seek to relate changes in ion current properties caused by a chemical modifier to changes in cellular properties. Therefore, quantifying concentration-dependent effects of modifiers on ion currents is a topic of importance. In this paper, we sought a mathematical method for using ion current data to predict the effect of several theoretical ion current modifiers on cellular and tissue properties that is computationally efficient without compromising predictive power. We focused on the current as an example case due to its link to long QT syndrome and arrhythmias, but these methods should be generally applicable to other electrophysiological studies. We compared predictions using a Markov model with mass action binding of the modifiers to specific conformational states of the channel to predictions generated by two simplified models. We investigated scaling conductance, and found that although this method produced predictions that agreed qualitatively with the more complicated model, it did not generate quantitatively consistent predictions for all modifiers tested. Our simulations showed that a more computationally efficient Hodgkin-Huxley model that incorporates the effect of modifiers through functional changes in the current produced quantitatively consistent predictions of concentration-dependent changes in cell and tissue properties for all modifiers tested. View full abstract»

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  • Polygonal Modeling of Contours of Breast Tumors With the Preservation of Spicules

    Publication Year: 2008 , Page(s): 14 - 20
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (490 KB) |  | HTML iconHTML  

    Malignant breast tumors typically appear in mammograms with rough, spiculated, or microlobulated contours, whereas most benign masses have smooth, round, oval, or macrolobulated contours. Several studies have shown that shape factors that incorporate differences as above can provide high accuracies in distinguishing between malignant tumors and benign masses based upon their contours only. However, global measures of roughness, such as compactness, are less effective than specially designed features based upon spicularity and concavity. We propose a method to derive polygonal models of contours that preserve spicules and details of diagnostic importance. We show that an index of spiculation derived from the turning functions of the polygonal models obtained by the proposed method yields better classification accuracy than a similar measure derived using a previously published method. The methods were tested with a set of 111 contours of 65 benign masses and 46 malignant tumors. A high classification accuracy of 0.94 in terms of the area under the receiver operating characteristics curve was obtained. View full abstract»

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  • A Discrete-Time Control Algorithm Applied to Closed-Loop Pacing of HL-1 Cardiomyocytes

    Publication Year: 2008 , Page(s): 21 - 30
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1285 KB) |  | HTML iconHTML  

    Electrical stimulation represents a useful tool for electrophysiologic investigation of electrically excitable cells such as cardiomyocytes. The stimulation threshold and electrophysiologic response to precisely timed pulses yields valuable information regarding physiologic processes. However, determining these parameters accurately, while simultaneously resolving time-dependent or transient effects has been difficult or impossible with previous methods. This paper presents a discrete-time algorithmic controller used for closed-loop electrical stimulation of HL-1 clonal cardiomyocytes cultured on, and stimulated using, a planar microelectrode array. We introduce the temporal error-controlled algorithm (TECA), that is well-suited to control using capture fraction, a low data rate, highly quantized feedback parameter describing stimulation efficacy. HL-1 cardiomyocytes were electrically stimulated and resulting parameters were used to develop a representative model of partial capture, enabling extensive analysis of the algorithm. The performance of this approach is compared via computer simulation to a previously introduced conditional convergence algorithm to quantify its performance and relative advantages. Operation of the TECA is demonstrated by tracking the real-time biological response of stimulation threshold to a rapid increase in extracellular potassium concentration in four independent cell cultures. This work enables the use of stimulation threshold as a real-time, continuously monitored parameter with considerable utility in cardiac pharmacology, electrophysiology, and cell-based biosensing. View full abstract»

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  • Application of Stochastic Finite Element Methods to Study the Sensitivity of ECG Forward Modeling to Organ Conductivity

    Publication Year: 2008 , Page(s): 31 - 40
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (898 KB) |  | HTML iconHTML  

    Because numerical simulation parameters may significantly influence the accuracy of the results, evaluating the sensitivity of simulation results to variations in parameters is essential. Although the field of sensitivity analysis is well developed, systematic application of such methods to complex biological models is limited due to the associated high computational costs and the substantial technical challenges for implementation. In the specific case of the forward problem in electrocardiography, the lack of robust, feasible, and comprehensive sensitivity analysis has left many aspects of the problem unresolved and subject to empirical and intuitive evaluation rather than sound, quantitative investigation. In this study, we have developed a systematic, stochastic approach to the analysis of sensitivity of the forward problem of electrocardiography to the parameter of inhomogeneous tissue conductivity. We apply this approach to a two-dimensional, inhomogeneous, geometric model of a slice through the human thorax. We assigned probability density functions for various organ conductivities and applied stochastic finite elements based on the generalized polynomial chaos-stochastic Galerkin (gPC-SG) method to obtain the standard deviation of the resulting stochastic torso potentials. This method utilizes a spectral representation of the stochastic process to obtain numerically accurate stochastic solutions in a fraction of the time required when employing classic Monte Carlo methods. We have shown that a systematic study of sensitivity is not only easily feasible with the gPC-SG approach but can also provide valuable insight into characteristics of the specific simulation. View full abstract»

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  • Nonparametric Identification of Population Models: An MCMC Approach

    Publication Year: 2008 , Page(s): 41 - 50
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (970 KB) |  | HTML iconHTML  

    The paper deals with the nonparametric identification of population models, that is models that explain jointly the behavior of different subjects drawn from a population, e.g., responses of different patients to a drug. The average response of the population and the individual responses are modeled as continuous-time Gaussian processes with unknown hyperparameters. Within a Bayesian paradigm, the posterior expectation and variance of both the average and individual curves are computed by means of a Markov Chain Monte Carlo scheme. The model and the estimation procedure are tested on both simulated and experimental pharmacokinetic data. View full abstract»

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  • Reducing the Effect of Respiration in Baroreflex Sensitivity Estimation With Adaptive Filtering

    Publication Year: 2008 , Page(s): 51 - 59
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (542 KB) |  | HTML iconHTML  

    Cardiac baroreflex is described by baroreflex sensitivity (BRS) from blood pressure and heart rate interval (RRi) fluctuations. However, respiration affects both blood pressure and RRi via mechanisms that are not necessarily of baroreflex origin. To separate the effects of baroreflex and respiration, metronome-guided breathing in a high frequency band (HF, 0.25-0.4 Hz) and a low frequency spectral band (LF, 0.04-0.15 Hz) have therefore been commonly used for BRS estimation. The controlled breathing may, however, change the natural functioning of the autonomic system and interfere BRS estimates. To enable usage of spontaneous breathing, we propose an adaptive LMS-based filter for removing the respiration effect from the BRS estimates. ECG, continuous blood pressure and respiration were measured during 5 min spontaneous and 5 min controlled breathing at 0.25 Hz in healthy males (n =24, 33plusmn7 years). BRS was calculated with spectral methods from the LF band with and without filtering. In those subjects whose spontaneous breathing rate was <0.15 Hz, the BRS(LF) values were overestimated, whereas the adaptive filtering reduced the bias significantly. As a conclusion, the adaptive filter reduces the distorting effect of respiration on BRS values, which enables more accurate estimation of BRS and the usage of spontaneous breathing as a measurement protocol. View full abstract»

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  • Automatic Identification of Return of Spontaneous Circulation During Cardiopulmonary Resuscitation

    Publication Year: 2008 , Page(s): 60 - 68
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (652 KB) |  | HTML iconHTML  

    The main problem during pulse check in out-of-hospital cardiac arrest is the discrimination between normal pulse-generating rhythm (PR) and pulseless electrical activity (PEA). It has been suggested that circulatory information can be acquired by measuring the thoracic impedance via the defibrillator pads. To investigate this, we performed an experimental study where we retrospectively analyzed 127 PEA segments and 91 PR segments out of 219 and 113 segments. A PEA versus PR classification framework was developed, that uses short segments (< 10 s) of ECG and impedance measurements to discriminate between the two rhythms. Using realistic data analyzed over a duration of 3 s, our system correctly identifies 90.0% of the segments with rhythm being pulseless electrical activity, and 91.5% of the normal pulse rhythm segments. Automatic identification of pulse could avoid unnecessary pulse checks and thereby reduce no-flow time and potentially increase the chance of survival. View full abstract»

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  • The Effect of Connectivity on EEG Rhythms, Power Spectral Density and Coherence Among Coupled Neural Populations: Analysis With a Neural Mass Model

    Publication Year: 2008 , Page(s): 69 - 77
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (633 KB) |  | HTML iconHTML  

    In the present work, a neural mass model consisting of four interconnected neural groups (pyramidal neurons, excitatory interneurons, inhibitory interneurons with slow synaptic kinetics, and inhibitory interneurons with fast synaptic kinetics) is used to investigate the mechanisms which cause the appearance of multiple rhythms in EEG spectra, and to assess how these rhythms can be affected by connectivity among different populations. In particular, we analyze a circuit, composed of three interconnected populations, each with a different synaptic kinetics (hence, with a different intrinsic rhythm). Results demonstrate that a single population can exhibit many different simultaneous rhythms, provided that some of these come from external sources (for instance, from remote regions). Analysis of coherence, and of the position of peaks in power spectral density, reveals important information on the possible connections among populations, especially useful to follow temporal changes in connectivity. Subsequently, the model is validated by comparing the power spectral density simulated in one population with that computed in the controlateral cingulated cortex (a region involved in motion preparation) during a right foot movement task in four normal subjects. The model is able to simulate real spectra quite well with only moderate parameter changes within the subject. In perspective, the results may be of value for a deeper comprehension of mechanism causing EEGs rhythms, for the study of brain connectivity and for the test of neurophysiological hypotheses. View full abstract»

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  • Optimized Wavelets for Blind Separation of Nonstationary Surface Myoelectric Signals

    Publication Year: 2008 , Page(s): 78 - 86
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (803 KB) |  | HTML iconHTML  

    Surface electromyography (EMG) signals detected over the skin surface may be mixtures of signals generated by many active muscles due to poor spatial selectivity of the recording. In this paper, we propose a new method for blind source separation (BSS) of nonstationary signals modeled as linear instantaneous mixtures. The method is based on whitening of the observations and rotation of the whitened observations. The rotation is performed by joint diagonalization of a set of spatial wavelet distributions (SWDs). The SWDs depend on the selection of the mother wavelet which can be defined by unconstrained parameters via the lattice parameterization within the multiresolution analysis framework. As the sources are classically supposed to be mutually uncorrelated, the design parameters of the mother wavelet can be blindly optimized by minimizing the average (over time lags) cross correlation between the estimated sources. The method was tested on simulated and experimental surface EMG signals and results were compared with those obtained with spatial time-frequency distributions and with second-order statistics (only spectral information). On a set of simulated signals, for 10-dB signal-to-noise ratio (SNR), the cross-correlation coefficient between original and estimated sources was 0.92plusmn0.07 with wavelet optimization, 0.74plusmn0.09 with the wavelet leading to the poorest performance, 0.85plusmn0.07 with Wigner-Ville distribution, 0.86plusmn0.07 with Choi-Williams distribution, and 0.73plusmn0.05 with second-order statistics. In experimental conditions, when the flexor carpi radialis and pronator teres were concomitantly active for 50% of the time, crosstalk was 55.2plusmn10.0% before BSS and was reduced to 15.2plusmn6.3% with wavelet optimization, 30.1plusmn15.0% with the worst wavelet, 28.3plusmn12.3% with Wigner-Ville distribution, 26.2plusmn12.0% with Choi-Williams distribution, and 35.1plusmn15.5% with second-order statistics. In conclusion, the proposed appr- - oach resulted in better performance than previous methods for the separation of nonstationary myoelectric signals. View full abstract»

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  • Midsagittal Jaw Movement Analysis for the Scoring of Sleep Apneas and Hypopneas

    Publication Year: 2008 , Page(s): 87 - 95
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (682 KB) |  | HTML iconHTML  

    Given the importance of the detection and classification of sleep apneas and hypopneas (SAHs) in the diagnosis and the characterization of the SAH syndrome, there is a need for a reliable noninvasive technique measuring respiratory effort. This paper proposes a new method for the scoring of SAHs based on the recording of the midsagittal jaw motion (MJM, mouth opening) and on a dedicated automatic analysis of this signal. Continuous wavelet transform is used to quantize respiratory effort from the jaw motion, to detect salient mandibular movements related to SAHs and to delineate events which are likely to contain the respiratory events. The classification of the delimited events is performed using multilayer perceptrons which were trained and tested on sleep data from 34 recordings. Compared with SAHs scored manually by an expert, the sensitivity and specificity of the detection were 86.1% and 87.4%, respectively. Moreover, the overall classification agreement in the recognition of obstructive, central, and mixed respiratory events between the manual and automatic scorings was 73.1%. The MJM signal is hence a reliable marker of respiratory effort and allows an accurate detection and classification of SAHs. View full abstract»

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  • Critical Analysis of the Impact of Glottal Features in the Classification of Clinical Depression in Speech

    Publication Year: 2008 , Page(s): 96 - 107
    Cited by:  Papers (29)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (892 KB) |  | HTML iconHTML  

    The motivation for this work is in an attempt to rectify the current lack of objective tools for clinical analysis of emotional disorders. This study involves the examination of a large breadth of objectively measurable features for use in discriminating depressed speech. Analysis is based on features related to prosodics, the vocal tract, and parameters extracted directly from the glottal waveform. Discrimination of the depressed speech was based on a feature selection strategy utilizing the following combinations of feature domains: prosodic measures alone, prosodic and vocal tract measures, prosodic and glottal measures, and all three domains. The combination of glottal and prosodic features produced better discrimination overall than the combination of prosodic and vocal tract features. Analysis of discriminating feature sets used in the study reflect a clear indication that glottal descriptors are vital components of vocal affect analysis. View full abstract»

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  • Sleep Versus Wake Classification From Heart Rate Variability Using Computational Intelligence: Consideration of Rejection in Classification Models

    Publication Year: 2008 , Page(s): 108 - 118
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (834 KB) |  | HTML iconHTML  

    Reliability of classification performance is important for many biomedical applications. A classification model which considers reliability in the development of the model such that unreliable segments are rejected would be useful, particularly, in large biomedical data sets. This approach is demonstrated in the development of a technique to reliably determine sleep and wake using only the electrocardiogram (ECG) of infants. Typically, sleep state scoring is a time consuming task in which sleep states are manually derived from many physiological signals. The method was tested with simultaneous 8-h ECG and polysomnogram (PSG) determined sleep scores from 190 infants enrolled in the collaborative home infant monitoring evaluation (CHIME) study. Learning vector quantization (LVQ) neural network, multilayer perceptron (MLP) neural network, and support vector machines (SVMs) are tested as the classifiers. After systematic rejection of difficult to classify segments, the models can achieve 85%-87% correct classification while rejecting only 30% of the data. This corresponds to a Kappa statistic of 0.65-0.68. With rejection, accuracy improves by about 8% over a model without rejection. Additionally, the impact of the PSG scored indeterminate state epochs is analyzed. The advantages of a reliable sleep/wake classifier based only on ECG include high accuracy, simplicity of use, and low intrusiveness. Reliability of the classification can be built directly in the model, such that unreliable segments are rejected. View full abstract»

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  • Statistical Modeling of Cardiovascular Signals and Parameter Estimation Based on the Extended Kalman Filter

    Publication Year: 2008 , Page(s): 119 - 129
    Cited by:  Papers (24)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1140 KB) |  | HTML iconHTML  

    Cardiovascular signals such as arterial blood pressure (ABP), pulse oximetry (POX), and intracranial pressure (ICP) contain useful information such as heart rate, respiratory rate, and pulse pressure variation (PPV). We present a novel state-space model of cardiovascular signals and describe how it can be used with the extended Kalman filter (EKF) to simultaneously estimate and track many cardiovascular parameters of interest using a unified statistical approach. We analyze data from four databases containing cardiovascular signals and present representative examples intended to illustrate the versatility, accuracy, and robustness of the algorithm. Our results demonstrate the ability of the algorithm to estimate and track several clinically relevant features of cardiovascular signals. We illustrate how the algorithm can be used to elegantly solve several actively researched and clinically significant problems including heart and respiratory rate estimation, artifact removal, pulse morphology characterization, and PPV estimation. View full abstract»

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  • Removal of CPR Artifacts From the Ventricular Fibrillation ECG by Adaptive Regression on Lagged Reference Signals

    Publication Year: 2008 , Page(s): 130 - 137
    Cited by:  Papers (9)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1341 KB) |  | HTML iconHTML  

    Removing cardiopulmonary resuscitation (CPR)-related artifacts from human ventricular fibrillation (VF) electrocardiogram (ECG) signals provides the possibility to continuously detect rhythm changes and estimate the probability of defibrillation success. This could reduce ldquohands-offrdquo analysis times which diminish the cardiac perfusion and deteriorate the chance for successful defibrillations. Our approach consists in estimating the CPR part of a corrupted signal by adaptive regression on lagged copies of a reference signal which correlate with the CPR artifact signal. The algorithm is based on a state-space model and the corresponding Kalman recursions. It allows for stochastically changing regression coefficients. The residuals of the Kalman estimation can be identified with the CPR-filtered ECG signal. In comparison with ordinary least-squares regression, the proposed algorithm shows, for low signal-to-noise ratio (SNR) corrupted signals, better SNR improvements and yields better estimates of the mean frequency and mean amplitude of the true VF ECG signal. The preliminary results from a small pool of human VF and animal asystole CPR data are slightly better than the results of comparable previous studies which, however, not only used different algorithms but also different data pools. The algorithm carries the possibility of further optimization. View full abstract»

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  • Cell Culture Imaging Using Microimpedance Tomography

    Publication Year: 2008 , Page(s): 138 - 146
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1269 KB) |  | HTML iconHTML  

    We present a novel, inexpensive, and fast microimpedance tomography system for two-dimensional imaging of cell and tissue cultures. The system is based on four-electrode measurements using 16 planar microelectrodes (5 mum x 4 mm) integrated into a culture chamber. An Agilent 4294A impedance analyzer combined with a front-end amplifier is used for the impedance measurements. Two-dimensional images are obtained using a reconstruction algorithm. This system is capable of accurately resolving the shape and position of a human hair, yielding vertical cross sections of the object. Human epithelial stem cells (YF 29) are also grown directly on the device surface. Tissue growth can be followed over several days. A rapid resistivity decrease caused by permeabilized cell membranes is also monitored, suggesting that this technique can be used in electroporation studies. View full abstract»

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  • Atlas-Based Indexing of Brain Sections via 2-D to 3-D Image Registration

    Publication Year: 2008 , Page(s): 147 - 156
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1297 KB) |  | HTML iconHTML  

    A 2-D to 3-D nonlinear intensity-based registration method is proposed in which the alignment of histological brain sections with a volumetric brain atlas is performed. First, sparsely cut brain sections were linearly matched with an oblique slice automatically extracted from the atlas. Second, a planar-to-curved surface alignment was employed in order to match each section with its corresponding image overlaid on a curved-surface within the atlas. For the latter, a PDE-based registration technique was developed that is driven by a local normalized-mutual-information similarity measure. We demonstrate the method and evaluate its performance with simulated and real data experiments. An atlas-guided segmentation of mouse brains' hippocampal complex, retrieved from the Mouse Brain Library (MBL) database, is demonstrated with the proposed algorithm. View full abstract»

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  • Independent Histogram Pursuit for Segmentation of Skin Lesions

    Publication Year: 2008 , Page(s): 157 - 161
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (191 KB) |  | HTML iconHTML  

    In this paper, an unsupervised algorithm, called the Independent Histogram Pursuit (IHP), for segmenting dermatological lesions is proposed. The algorithm estimates a set of linear combinations of image bands that enhance different structures embedded in the image. In particular, the first estimated combination enhances the contrast of the lesion to facilitate its segmentation. Given an N-band image, this first combination corresponds to a line in N dimensions, such that the separation between the two main modes of the histogram obtained by projecting the pixels onto this line, is maximized. The remaining combinations are estimated in a similar way under the constraint of being orthogonal to those already computed. The performance of the algorithm is tested on five different dermatological datasets. The results obtained on these datasets indicate the robustness of the algorithm and its suitability to deal with different types of dermatological lesions. The boundary detection precision using k-means segmentation was close to 97%. The proposed algorithm can be easily combined with the majority of classification algorithms. View full abstract»

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  • Liver Microcirculation Analysis by Red Blood Cell Motion Modeling in Intravital Microscopy Images

    Publication Year: 2008 , Page(s): 162 - 170
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1284 KB) |  | HTML iconHTML  

    Intravital microscopy has been used to visualize the microcirculation by imaging fluorescent labeled red blood cells (RBCs). Traditionally, microcirculation has been modeled by computing the mean velocity of a few, randomly selected, manually tracked RBCs. However, this protocol is tedious, time consuming, and subjective with technician related bias. We present a new method for analyzing the microcirculation by modeling the RBC motion through automatic tracking. The tracking of RBCs is challenging as in each image, as many as 200 cells move through a complex network of vessels at a wide range of speeds while deforming in shape. To reliably detect RBCs traveling at a wide range of speeds, a window of temporal template matching is applied. Then, cells appearing in successive frames are corresponded based on the motion behavior constraints in terms of the direction, magnitude, and path. The performance evaluation against a ground truth indicates the detection accuracy up to 84% TP at 6% FP and a correspondence accuracy of 89%. We include an in-depth discussion on comparison of the microcirculation based on motion modeling from the proposed automated method against a mean velocity from manual analysis protocol in terms of precision, objectivity, and sensitivity. View full abstract»

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  • Arterial Vulnerable Plaque Characterization Using Ultrasound-Induced Thermal Strain Imaging (TSI)

    Publication Year: 2008 , Page(s): 171 - 180
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1133 KB) |  | HTML iconHTML  

    Thermal strain imaging (TSI) is demonstrated in two model systems mimicking two potential clinical applications. First, a custom ultrasound (US) microscope produced high-resolution TSI images of an excised porcine coronary artery. Samples were placed in a temperature-controlled water chamber and scanned transversely and longitudinally. Phase-sensitive, correlation-based speckle tracking was applied to map the spatial distribution of temporal strain across the sample. TSI differentiated fatty tissue from water-based arterial wall and muscle with high contrast and a spatial resolution of 60 mum for a 50-MHz transducer. Both transverse and longitudinal TSI images compared well with B-scans of arterial wall structures, including intima, media, adventitia, and overlying fatty tissue. A second model system was used to test the hypothesis that US can produce the heating pattern required for TSI of internal structures. A 2-D phased array with independent drive electronics was combined with a conventional US scanner (iU22, Philips, Bothell, WA) for these studies. This 513-element array, originally designed for the US therapy, acted as the US heat source. To quantify the temporal strain induced by this system, TSI was performed on a homogeneous rubber phantom. TSI temperature estimates were within 3% error for a 3.2degC temperature rise produced within 2 s using a specially designed beamformer and pulse sequencer. The system was then used to produce TSI scanning of an excised kidney containing an intact piece of fat below the collecting system. These images were validated using an magnetic resonance imaging (MRI) pulse sequence designed for lipid quantification. TSI scans matched well MRI scans and histology both anatomically and quantitatively. Finally, to test the potential of US-induced TSI for a significant clinical problem, images were obtained on an excised canine aorta with fatty tissue inside the lumen. Both longitudinal and transversal TSI agreed well with anatomy. T- - hese in vitro results demonstrate the potential of high-resolution US-induced TSI with a small temperature change (<1degC) for plaque characterization. View full abstract»

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  • Percutaneous Biphasic Electrical Stimulation for Treatment of Obstructive Sleep Apnea Syndrome

    Publication Year: 2008 , Page(s): 181 - 187
    Cited by:  Papers (1)  |  Patents (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (335 KB) |  | HTML iconHTML  

    In this paper, we study the effect of stimulation of the genioglossus with percutaneous biphasic electrical pulses on patients with the obstructive sleep apnea syndrome (OSAS). The experiment was conducted in 22 patients clinically diagnosed with OSAS. The patients were monitored with polysomnography (PSG) in the trial. When the sleep apnea was detected, the genioglossus was stimulated with percutaneous biphasic electrical pulses that were automatically regulated by a microcontroller to achieve the optimal effect. The percutaneous biphasic electrical stimulation caused contraction of the genioglossus, forward movement of the tongue, and relieving of the glossopharyngeal airway obstruction. The SaO, apnea time, hypoxemia time, and change of respiratory disturbance index (RDI) were compared in patients with treatment and without treatment. With percutaneous biphasic electrical stimulation of the genioglossus, the OSAS patients showed apnea time decreased , RDI decreased , and SaO increased . No tissue injury or major discomfort was noticed during the trial. The stimulation of genioglossus with percutaneous biphasic electrical current pulse is an effective method for treating OSAS. View full abstract»

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  • Nonwoven Fabric Active Electrodes for Biopotential Measurement During Normal Daily Activity

    Publication Year: 2008 , Page(s): 188 - 195
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1177 KB) |  | HTML iconHTML  

    Body movement is responsible for most of the interference during physiological data acquisition during normal daily activities. In this paper, we introduce nonwoven fabric active electrodes that provide the comfort required for clothing while robustly recording physiological data in the presence of body movement. The nonwoven fabric active electrodes were designed and fabricated using both hand- and screen-printing thick-film techniques. Nonstretchable nonwoven (Evolon 100) was chosen as the flexible fabric substrate and a silver filled polymer ink (Creative Materials CMI 112-15) was used to form a transducer layer and conductive lines on the nonwoven fabrics. These nonwoven fabric active electrodes can be easily integrated into clothing for wearable health monitoring applications. Test results indicate that nonwoven textile-based sensors show considerable promise for physiological data acquisition in wearable healthcare monitoring applications. View full abstract»

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  • Breathing Detection: Towards a Miniaturized, Wearable, Battery-Operated Monitoring System

    Publication Year: 2008 , Page(s): 196 - 204
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1103 KB) |  | HTML iconHTML  

    This paper analyzes the main challenges associated with noninvasive, continuous, wearable, and long-term breathing monitoring. The characteristics of an acoustic breathing signal from a miniature sensor are studied in the presence of sources of noise and interference artifacts that affect the signal. Based on these results, an algorithm has been devised to detect breathing. It is possible to implement the algorithm on a single integrated circuit, making it suitable for a miniature sensor device. The algorithm is tested in the presence of noise sources on five subjects and shows an average success rate of 91.3% (combined true positives and true negatives). View full abstract»

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  • Analysis of Current Density and Specific Absorption Rate in Biological Tissue Surrounding Transcutaneous Transformer for an Artificial Heart

    Publication Year: 2008 , Page(s): 205 - 213
    Cited by:  Papers (11)
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    This paper reports on the current density and specific absorption rate (SAR) analysis of biological tissue surrounding an air-core transcutaneous transformer for an artificial heart. The electromagnetic field in the biological tissue is analyzed by the transmission line modeling method, and the current density and SAR as a function of frequency, output voltage, output power, and coil dimension are calculated. The biological tissue of the model has three layers including the skin, fat, and muscle. The results of simulation analysis show SARs to be very small at any given transmission conditions, about 2-14 mW/kg, compared to the basic restrictions of the International Commission on nonionizing radiation protection (ICNIRP; 2 W/kg), while the current density divided by the ICNIRP's basic restrictions gets smaller as the frequency rises and the output voltage falls. It is possible to transfer energy below the ICNIRP's basic restrictions when the frequency is over 250 kHz and the output voltage is under 24 V. Also, the parts of the biological tissue that maximized the current density differ by frequencies; in the low frequency is muscle and in the high frequency is skin. The boundary is in the vicinity of the frequency 600-1000 kHz. 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