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Biomedical Engineering, IEEE Transactions on

Issue 6 • Date June 2014

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Displaying Results 1 - 25 of 43
  • [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): 1605 - 1606
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  • Ventricular Fibrillation and Tachycardia Classification Using a Machine Learning Approach

    Page(s): 1607 - 1613
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (655 KB) |  | HTML iconHTML  

    Correct detection and classification of ventricular fibrillation (VF) and rapid ventricular tachycardia (VT) is of pivotal importance for an automatic external defibrillator and patient monitoring. In this paper, a VF/VT classification algorithm using a machine learning method, a support vector machine, is proposed. A total of 14 metrics were extracted from a specific window length of the electrocardiogram (ECG). A genetic algorithm was then used to select the optimal variable combinations. Three annotated public domain ECG databases (the American Heart Association Database, the Creighton University Ventricular Tachyarrhythmia Database, and the MIT-BIH Malignant Ventricular Arrhythmia Database) were used as training, test, and validation datasets. Different window sizes, varying from 1 to 10 s were tested. An accuracy (Ac) of 98.1%, sensitivity (Se) of 98.4%, and specificity (Sp) of 98.0% were obtained on the in-sample training data with 5 s-window size and two selected metrics. On the out-of-sample validation data, an Ac of 96.3% ± 3.4%, Se of 96.2% ± 2.7%, and Sp of 96.2% ± 4.6% were obtained by fivefold cross validation. The results surpass those of current reported methods. View full abstract»

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  • Designing MR Shim Arrays With Irregular Coil Geometry: Theoretical Considerations

    Page(s): 1614 - 1620
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3961 KB) |  | HTML iconHTML  

    In magnetic resonance imaging and spectroscopy, a highly uniform magnetic field is desired for minimizing image distortions and line broadening, respectively. Typically, shim coils are employed to provide correcting fields for inhomogeneities brought about by magnetic interactions with the sample under study. Flexible field modeling is possible using an array of regularly shaped conducting loops that are independently electrically driven. In this paper, a design method is presented for generating coil winding patterns for shim arrays with irregular geometry elements. These designs are compared theoretically to the use of circular loop arrays and are shown to provide considerable improvements in field accuracy and efficiency for generating low-order correcting fields. View full abstract»

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  • Fast X-Ray Luminescence Computed Tomography Imaging

    Page(s): 1621 - 1627
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (480 KB) |  | HTML iconHTML  

    X-ray luminescence computed tomography (XLCT) opens new possibilities to perform molecular imaging with X-ray. However, challenges remain in dynamic XLCT imaging, where short scan time, good spatial resolution, and whole-body field of view should be considered simultaneously. In this paper, by the use of a single-view XLCT reconstruction method based on a compressive sensing (CS) technique, incorporating a cone beam XLCT imaging system, we implement fast 3-D XLCT imaging. To evaluate the performance of the method, two types of phantom experiments were performed based on a cone beam XLCT imaging system. In Case 1, one tube filled with the X-ray-excitable nanophosphor (Gd2O3:Eu3+) was immerged in different positions in the phantom to evaluate the effect of the source position on single-view XLCT reconstruction accuracy. In Case 2, two tubes filled with Gd2O3:Eu3+ were immerged in different heights in the phantom to evaluate the whole-body imaging performance of single-view XLCT reconstruction. The experimental results indicated that the tubes used in previous phantom experiments can be resolved from single-view XCLT reconstruction images. The location error is less than 1.2 mm. In addition, since only one view data are needed to implement 3-D XLCT imaging, the acquisition time can be greatly reduced (~1 frame/s) compared with previous XLCT systems. Hence, the technique is suited for imaging the fast distribution of the X-ray-excitable nanophosphors within a biological object. View full abstract»

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  • Investigating the Role of Vibrotactile Noise in Early Response to Perturbation

    Page(s): 1628 - 1633
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (499 KB) |  | HTML iconHTML  

    Timely reaction to perturbation is important in activities of daily living. Modulation of reaction time to and early recovery from perturbation via vibrotactile noise was investigated. It was hypothesized that subthreshold vibrotactile noise applied to the upper extremity can accelerate a person's reaction to and recovery from handle perturbation. This intervention was developed based on previous studies in which the earliest cue available for people to detect handle perturbation was somatosensation detecting changes in pressure on the hand whose sensitivity can improve with subthreshold vibrotactile noise. To induce a handle perturbation, a sudden upward load was applied to the handle that subjects were lightly grasping. Eighteen healthy subjects were instructed to stop the handle from moving up when they detected the perturbation. The muscle reaction time and handle stabilization time with and without vibrotactile noise were determined. The results showed that the muscle reaction time and handle stabilization time significantly decreased by 3 ms (p = 0.018) and 6 ms (p = 0.023), respectively, when vibrotactile noise was applied to the upper extremity, regardless of where the noise was applied among four different locations within the upper extremity ( p > 0.05). In conclusion, the application of subthreshold vibrotactile noise enhanced persons' muscle reaction time to handle perturbation and led to early recovery from the perturbation. Use of the vibrotactile noise may increase a person's ability to rapidly respond to perturbation of a grasped object in potentially dangerous situations such as holding onto ladder rungs from elevation or manipulating knives. View full abstract»

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  • Automated Removal of EKG Artifact From EEG Data Using Independent Component Analysis and Continuous Wavelet Transformation

    Page(s): 1634 - 1641
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (613 KB) |  | HTML iconHTML  

    The electrical potential produced by the cardiac activity sometimes contaminates electroencephalogram (EEG) recordings, resulting in spiky activities that are referred to as electrocardiographic (EKG) artifact. For a variety of reasons it is often desirable to automatically detect and remove these artifacts. Especially, for accurate source localization of epileptic spikes in an EEG recording from a patient with epilepsy, it is of great importance to remove any concurrent artifact. Due to similarities in morphology between the EKG artifacts and epileptic spikes, any automated artifact removal algorithm must have an extremely low false-positive rate in addition to a high detection rate. In this paper, an automated algorithm for removal of EKG artifact is proposed that satisfies such criteria. The proposed method, which uses combines independent component analysis and continuous wavelet transformation, uses both temporal and spatial characteristics of EKG related potentials to identify and remove the artifacts. The method outperforms algorithms that use general statistical features such as entropy and kurtosis for artifact rejection. View full abstract»

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  • Comparison of a Single Optimized Coil and a Helmholtz Pair for Magnetic Nanoparticle Hyperthermia

    Page(s): 1642 - 1650
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    Magnetic nanoparticles in a tumor can induce therapeutic heating when energized by an alternating magnetic field from a current-carrying coil outside the body. We analyzed a single-turn, air-core coil carrying a filamentary current to quantify the power absorbed by: a) magnetic nanoparticles at depth in tissue and b) superficial tissue in response to induced eddy currents; we defined this quotient as power ratio (PR). Given some limit on the eddy current heating tolerated by an alert patient, maximizing the PR maximizes the power absorbed in the tumor; all else being equal, this increases the thermal dose delivered to the tumor. The mean eddy current heating rate tolerated in four clinical studies we reviewed equaled 12.5 kW/m 3. We differentiated our analytical expression for PR with respect to the radius of the coil to find the value of radius that maximizes PR. Under reasonable simplifying assumptions, the optimal value of coil radius equaled 1.187 times the depth of the nanoparticle target below the body surface. We also derived the PR of two coils surrounding the body configured as a Helmholtz pair. We computed PR for combinations of nanoparticle depths below the surface and axial locations with respect to the coils. At depths less than 4.6 cm, the optimized single coil had a higher PR than that of the Helmholtz pair and furthermore produced less total ohmic heating within the coil. These results were independent of driving frequency, nanoparticle concentration, tissue electrical conductivity, and magnetic nanoparticle heating rate, provided the latter is assumed to be proportional to the product of frequency and the square of the local magnetic field. This paper supports the clinical application of current-carrying coils to deliver efficacious hyperthermia therapy to tumors injected with magnetic nanoparticles. View full abstract»

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  • Behavioral Characteristics of Manual Palpation to Localize Hard Nodules in Soft Tissues

    Page(s): 1651 - 1659
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (646 KB) |  | HTML iconHTML  

    Improving the effectiveness of artificial tactile sensors for soft-tissue examination and tumor localization is a pressing need in robot-assisted minimally invasive surgery. Despite the availability of tactile probes, guidelines for optimal palpation behavior that best exploit soft-tissue properties are not available as yet. Simulations on soft-tissue palpation show that particular stress-velocity patterns during tissue probing lead to constructive dynamic interactions between the probe and the tissue, enhancing the detection and localization of hard nodules. To the best of our knowledge, this is the first attempt to methodically evaluate the hypothesis that specific human palpation behaviors (defined by the fingers' velocity, trajectory, and exerted force) directly influence the diagnosis of soft-tissue organs. Here, we use simulation studies involving human participants to establish open hypotheses on the interaction and influence of relevant behavioral palpation variables, such as finger trajectory, its velocity, and force exerted by fingers on the accuracy of detecting embedded nodules. We validate this hypothesis through finite element analysis and the investigation of palpation strategies used by humans during straight unidirectional examination to detect hard nodules inside silicone phantoms and ex-vivo porcine organs. Thus, we conclude that the palpation strategy plays an important role during soft-tissue examination. Our findings allow us, for the first time, to derive palpation behavior guidelines suitable for the design of controllers of palpation robots. View full abstract»

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  • Noninvasive Imaging of the High Frequency Brain Activity in Focal Epilepsy Patients

    Page(s): 1660 - 1667
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (562 KB) |  | HTML iconHTML  

    High-frequency (HF) activity represents a potential biomarker of the epileptogenic zone in epilepsy patients, the removal of which is considered to be crucial for seizure-free surgical outcome. We proposed a high frequency source imaging (HFSI) approach to noninvasively image the brain sources of the scalp-recorded HF EEG activity. Both computer simulation and clinical patient data analysis were performed to investigate the feasibility of using the HFSI approach to image the sources of HF activity from noninvasive scalp EEG recordings. The HF activity was identified from high-density scalp recordings after high-pass filtering the EEG data and the EEG segments with HF activity were concatenated together to form repetitive HF activity. Independent component analysis was utilized to extract the components corresponding to the HF activity. Noninvasive EEG source imaging using realistic geometric boundary element head modeling was then applied to image the sources of the pathological HF brain activity. Five medically intractable focal epilepsy patients were studied and the estimated sources were found to be concordant with the surgical resection or intracranial recordings of the patients. The present study demonstrates, for the first time, that source imaging from the scalp HF activity could help to localize the seizure onset zone and provide a novel noninvasive way of studying the epileptic brain in humans. This study also indicates the potential application of studying HF activity in the presurgical planning of medically intractable epilepsy patients. View full abstract»

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  • Learning to Detect Vocal Hyperfunction From Ambulatory Neck-Surface Acceleration Features: Initial Results for Vocal Fold Nodules

    Page(s): 1668 - 1675
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1326 KB) |  | HTML iconHTML  

    Voice disorders are medical conditions that often result from vocal abuse/misuse which is referred to generically as vocal hyperfunction. Standard voice assessment approaches cannot accurately determine the actual nature, prevalence, and pathological impact of hyperfunctional vocal behaviors because such behaviors can vary greatly across the course of an individual's typical day and may not be clearly demonstrated during a brief clinical encounter. Thus, it would be clinically valuable to develop noninvasive ambulatory measures that can reliably differentiate vocal hyperfunction from normal patterns of vocal behavior. As an initial step toward this goal we used an accelerometer taped to the neck surface to provide a continuous, noninvasive acceleration signal designed to capture some aspects of vocal behavior related to vocal cord nodules, a common manifestation of vocal hyperfunction. We gathered data from 12 female adult patients diagnosed with vocal fold nodules and 12 control speakers matched for age and occupation. We derived features from weeklong neck-surface acceleration recordings by using distributions of sound pressure level and fundamental frequency over 5-min windows of the acceleration signal and normalized these features so that intersubject comparisons were meaningful. We then used supervised machine learning to show that the two groups exhibit distinct vocal behaviors that can be detected using the acceleration signal. We were able to correctly classify 22 of the 24 subjects, suggesting that in the future measures of the acceleration signal could be used to detect patients with the types of aberrant vocal behaviors that are associated with hyperfunctional voice disorders. View full abstract»

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  • Continuous Wave Simulations on the Propagation of Electromagnetic Fields Through the Human Head

    Page(s): 1676 - 1683
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1306 KB) |  | HTML iconHTML  

    Characterizing the human head as a propagation medium is vital for the design of both on-body and implanted antennas and radio-frequency sensors. The following problem has been addressed: find the best radio-frequency path through the brain for a given receiver position - on the top of the sinus cavity. Two parameters, transmitter position and radiating frequency, should be optimized simultaneously such that 1) the propagation path through the brain is the longest; and 2) the received power is maximized. To solve this problem, we have performed a systematic and comprehensive study of the electromagnetic fields excited in the head by small on-body magnetic dipoles (small coil antennas). An anatomically accurate high-fidelity head mesh has been generated from the Visible Human Project data. The base radiator was constructed of two orthogonal magnetic dipoles in quadrature, which enables us to create a directive beam into the head. We have found at least one optimum solution. This solution implies that a distinct RF channel may be established in the brain at a certain frequency and transmitter location. View full abstract»

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  • Combining Conformal Deformation and Cook–Torrance Shading for 3-D Reconstruction in Laparoscopy

    Page(s): 1684 - 1692
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (834 KB) |  | HTML iconHTML  

    We propose a new monocular 3-D reconstruction method adapted for reconstructing organs in the abdominal cavity. It combines both motion and shading cues. The former uses a conformal deformation prior and the latter the Cook-Torrance reflectance model. Our method runs in two phases: first, a 3-D geometric and photometric template of the organ at rest is reconstructed in vivo. The geometric shape is reconstructed using rigid shape-from-motion while the surgeon is exploring-but not deforming-structures in the abdominal cavity. This geometric template is then used to retrieve the photometric properties. A nonparametric model of the light's direction of the laparoscope and the Cook-Torrance reflectance model of the organ's tissue are estimated. Second, the surgeon manipulates and deforms the environment. Here, the 3-D template is conformally deformed to globally match a set of few correspondences between the 2-D image data provided by the monocular laparoscope and the 3-D template. Then, the coarse 3-D shape is refined using shading cues to obtain a final 3-D deformed shape. This second phase only relies on a single image. Therefore, it copes with both sequential processing and self-recovery from tracking failure. The proposed approach has been validated using 1) ex vivo and in vivo data with ground-truth, and 2) in vivo laparoscopic videos of a patient's uterus. Our experimental results illustrate the ability of our method to reconstruct natural 3-D deformations typical in real surgical procedures. View full abstract»

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  • A Nonlinear Generalization of Spectral Granger Causality

    Page(s): 1693 - 1701
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (564 KB) |  | HTML iconHTML  

    Spectral measures of linear Granger causality have been widely applied to study the causal connectivity between time series data in neuroscience, biology, and economics. Traditional Granger causality measures are based on linear autoregressive with exogenous (ARX) inputs models of time series data, which cannot truly reveal nonlinear effects in the data especially in the frequency domain. In this study, it is shown that the classical Geweke's spectral causality measure can be explicitly linked with the output spectra of corresponding restricted and unrestricted time-domain models. The latter representation is then generalized to nonlinear bivariate signals and for the first time nonlinear causality analysis in the frequency domain. This is achieved by using the nonlinear ARX (NARX) modeling of signals, and decomposition of the recently defined output frequency response function which is related to the NARX model. View full abstract»

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  • Microwave Ablation at 10.0 GHz Achieves Comparable Ablation Zones to 1.9 GHz in Ex Vivo Bovine Liver

    Page(s): 1702 - 1710
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    We demonstrate the feasibility of using high-frequency microwaves for tissue ablation by comparing the performance of a 10 GHz microwave ablation system with that of a 1.9 GHz system. Two sets of floating sleeve dipole antennas operating at these frequencies were designed and fabricated for use in ex vivo experiments with bovine livers. Combined electromagnetic and transient thermal simulations were conducted to analyze the performance of these antennas. Subsequently, a total of 16 ablation experiments (eight at 1.9 GHz and eight at 10.0 GHz) were conducted at a power level of 42 W for either 5 or 10 min. In all cases, the 1.9 and 10 GHz experiments resulted in comparable ablation zone dimensions. Temperature monitoring probes revealed faster heating rates in the immediate vicinity of the 10.0 GHz antenna compared to the 1.9 GHz antenna, along with a slightly delayed onset of heating farther from the 10 GHz antenna, suggesting that heat conduction plays a greater role at higher microwave frequencies in achieving a comparably sized ablation zone. The results obtained from these experiments agree very well with the combined electromagnetic/thermal simulation results. These simulations and experiments show that using lower frequency microwaves does not offer any significant advantages, in terms of the achievable ablation zones, over using higher frequency microwaves. Indeed, it is demonstrated that high-frequency microwave antennas may be used to create reasonably large ablation zones. Higher frequencies offer the advantage of smaller antenna size, which is expected to lead to less invasive interstitial devices and may possibly lead to the development of more compact multielement arrays with heating properties not available from single-element antennas. View full abstract»

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  • Hypnogram and Sleep Parameter Computation From Activity and Cardiovascular Data

    Page(s): 1711 - 1719
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (435 KB) |  | HTML iconHTML  

    The automatic computation of the hypnogram and sleep Parameters, from the data acquired with portable sensors, is a challenging problem with important clinical applications. In this paper, the hypnogram, the sleep efficiency (SE), rapid eye movement (REM), and nonREM (NREM) sleep percentages are automatically estimated from physiological (ECG and respiration) and behavioral (Actigraphy) nocturnal data. Two methods are described; the first deals with the problem of the hypnogram estimation and the second is specifically designed to compute the sleep parameters, outperforming the traditional estimation approach based on the hypnogram. Using an extended set of features the first method achieves an accuracy of 72.8%, 77.4%, and 80.3% in the detection of wakefulness, REM, and NREM states, respectively, and the second an estimation error of 4.3%, 9.8%, and 5.4% for the SE, REM, and NREM percentages, respectively. View full abstract»

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  • Feasibility of Real-Time Workflow Segmentation for Tracked Needle Interventions

    Page(s): 1720 - 1728
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (776 KB) |  | HTML iconHTML  

    Computer-assisted training systems promote both training efficacy and patient health. An important component for providing automatic feedback in computer-assisted training systems is workflow segmentation: the determination of what task in the workflow is being performed. Our objective was to develop a workflow segmentation algorithm for needle interventions using needle tracking data. Needle tracking data were collected from ultrasound-guided epidural injections and lumbar punctures, performed by medical personnel. The workflow segmentation algorithm was tested in a simulated real-time scenario: the algorithm was only allowed access to data recorded at, or prior to, the time being segmented. Segmentation output was compared to the ground-truth segmentations produced by independent blinded observers. Overall, the algorithm was 93% accurate. It automatically segmented the ultrasound-guided epidural procedures with 81% accuracy and the lumbar punctures with 82% accuracy. Given that the manual segmentation consistency was only 84%, the algorithm's accuracy was 93%. Using Cohen's d statistic, a medium effect size (0.5) was calculated. Because the algorithm segments needle-based procedures with such high accuracy, expert observers can be augmented by this algorithm without a large decrease in ability to follow trainees in a workflow. The proposed algorithm is feasible for use in a computer-assisted needle placement training system. View full abstract»

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  • A Nonlinear Mapping Approach to Stain Normalization in Digital Histopathology Images Using Image-Specific Color Deconvolution

    Page(s): 1729 - 1738
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (890 KB) |  | HTML iconHTML  

    Histopathology diagnosis is based on visual examination of the morphology of histological sections under a microscope. With the increasing popularity of digital slide scanners, decision support systems based on the analysis of digital pathology images are in high demand. However, computerized decision support systems are fraught with problems that stem from color variations in tissue appearance due to variation in tissue preparation, variation in stain reactivity from different manufacturers/batches, user or protocol variation, and the use of scanners from different manufacturers. In this paper, we present a novel approach to stain normalization in histopathology images. The method is based on nonlinear mapping of a source image to a target image using a representation derived from color deconvolution. Color deconvolution is a method to obtain stain concentration values when the stain matrix, describing how the color is affected by the stain concentration, is given. Rather than relying on standard stain matrices, which may be inappropriate for a given image, we propose the use of a color-based classifier that incorporates a novel stain color descriptor to calculate image-specific stain matrix. In order to demonstrate the efficacy of the proposed stain matrix estimation and stain normalization methods, they are applied to the problem of tumor segmentation in breast histopathology images. The experimental results suggest that the paradigm of color normalization, as a preprocessing step, can significantly help histological image analysis algorithms to demonstrate stable performance which is insensitive to imaging conditions in general and scanner variations in particular. View full abstract»

    Open Access
  • A Reconstruction Algorithm of Magnetoacoustic Tomography With Magnetic Induction for an Acoustically Inhomogeneous Tissue

    Page(s): 1739 - 1746
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1021 KB) |  | HTML iconHTML  

    Magnetoacoustic tomography with magnetic induction (MAT-MI) is a noninvasive electrical conductivity imaging approach that measures ultrasound wave induced by magnetic stimulation, for reconstructing the distribution of electrical impedance in a biological tissue. Existing reconstruction algorithms for MAT-MI are based on the assumption that the acoustic properties in the tissue are homogeneous. However, the tissue in most parts of human body has heterogeneous acoustic properties, which leads to potential distortion and blurring of small buried objects in the impedance images. In this study, we proposed a new algorithm for MAT-MI to image the impedance distribution in tissues with inhomogeneous acoustic speed distributions. With a computer head model constructed from MR images of a human subject, a series of numerical simulation experiments were conducted. The present results indicate that the inhomogeneous acoustic properties of tissues in terms of speed variation can be incorporated in MAT-MI imaging. View full abstract»

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  • Differentiating Between Psychogenic Nonepileptic Seizures and Epilepsy Based on Common Spatial Pattern of Weighted EEG Resting Networks

    Page(s): 1747 - 1755
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (617 KB) |  | HTML iconHTML  

    Discriminating psychogenic nonepileptic seizures (PNES) from epilepsy is challenging, and a reliable and automatic classification remains elusive. In this study, we develop an approach for discriminating between PNES and epilepsy using the common spatial pattern extracted from the brain network topology (SPN). The study reveals that 92% accuracy, 100% sensitivity, and 80% specificity were reached for the classification between PNES and focal epilepsy. The newly developed SPN of resting EEG may be a promising tool to mine implicit information that can be used to differentiate PNES from epilepsy. View full abstract»

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  • Abnormal Dynamics of EEG Oscillations in Schizophrenia Patients on Multiple Time Scales

    Page(s): 1756 - 1764
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (949 KB) |  | HTML iconHTML  

    Neuronal oscillations reflect the activity of neuronal ensembles engaged in integrative cognition, and may serve as a functional measure for the cognitive impairment in schizophrenia. This study aims to reveal the abnormal amplitude dynamics of electroencephalogram (EEG) oscillations in schizophrenia patients on multiple time scales. EEGs were recorded from schizophrenia patients ( n = 19) and healthy controls ( n = 16) while they were at resting state with eyes closed, at resting state with eyes open, and at watching video. Detrended fluctuation analysis and measures of life-time and waiting-time were used to characterize the abnormal dynamics of EEG oscillations on both long (1-20 s) and short (≤1 s) time scales. Abnormal dynamics of EEG oscillations in alpha and beta bands were observed. In particular, compared with healthy controls, schizophrenia patients have smaller DFA exponent (implying weaker long-range temporal correlation) in the left fronto-temporal area and smaller DFA exponent, smaller life-time (indicating shorter oscillation burst), and smaller waiting-time in the occipital area in beta band at resting state with eyes open. In addition, schizophrenia patients have larger DFA exponent, larger life-time, and larger waiting-time at some clustered channels in the temporo-parietal area in alpha band at watching video. The present results provide new insights for cognitive deficits and the underlying neuronal dysfunction in schizophrenia. View full abstract»

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  • Miniature Electrical Stimulator for Hemorrhage Control

    Page(s): 1765 - 1771
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (744 KB) |  | HTML iconHTML  

    Noncompressible hemorrhage is currently the most common cause of preventable death in battlefield and in civilian trauma injuries. Tourniquets, specialized wound dressings, and hemorrhage-inhibiting biomaterials are not sufficiently effective in arrest of noncompressible hemorrhage and often cause collateral tissue damage. An effective, easy-to-use, portable device is needed to reduce blood loss in trauma patients immediately following injury and to maintain hemorrhage control up to several hours-until the injured is evacuated to a medical facility. We developed a miniature electrical stimulator to induce vascular constriction and, thereby, reduce hemorrhage. Vasoconstriction of the rat femoral arteries and veins was studied with pulse durations in the range of 1 μs to 10 ms and repetition rate of 10 Hz. Pulse amplitude of 20 V, duration of 1 ms, and repetition rate of 10 Hz were found sufficient to induce rapid constriction down to 31 ± 2% of the initial diameter, which could be maintained throughout a two-hour treatment. Within one minute following treatment termination the artery dilated back to 88 ± 3% of the initial diameter, providing rapid restoration of blood perfusion. Histology indicated no damage to the vessel wall and endothelium seven days after stimulation. The same treatment reduced the blood loss following complete femoral artery resection by 68 ± 11%, compared to untreated vessels. Very low power consumption during stimulation (<;10 mW per 1.6 mm electrode) allows miniaturization of the stimulator for portable battery-powered operation in the field to control the blood loss following vascular trauma. View full abstract»

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  • Automatic Ingestion Monitor: A Novel Wearable Device for Monitoring of Ingestive Behavior

    Page(s): 1772 - 1779
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1030 KB) |  | HTML iconHTML  

    Objective monitoring of food intake and ingestive behavior in a free-living environment remains an open problem that has significant implications in study and treatment of obesity and eating disorders. In this paper, a novel wearable sensor system (automatic ingestion monitor, AIM) is presented for objective monitoring of ingestive behavior in free living. The proposed device integrates three sensor modalities that wirelessly interface to a smartphone: a jaw motion sensor, a hand gesture sensor, and an accelerometer. A novel sensor fusion and pattern recognition method was developed for subject-independent food intake recognition. The device and the methodology were validated with data collected from 12 subjects wearing AIM during the course of 24 h in which both the daily activities and the food intake of the subjects were not restricted in any way. Results showed that the system was able to detect food intake with an average accuracy of 89.8%, which suggests that AIM can potentially be used as an instrument to monitor ingestive behavior in free-living individuals. View full abstract»

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  • Feature Selection and Activity Recognition System Using a Single Triaxial Accelerometer

    Page(s): 1780 - 1786
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (342 KB) |  | HTML iconHTML  

    Activity recognition is required in various applications such as medical monitoring and rehabilitation. Previously developed activity recognition systems utilizing triaxial accelerometers have provided mixed results, with subject-to-subject variability. This paper presents an accurate activity recognition system utilizing a body worn wireless accelerometer, to be used in the real-life application of patient monitoring. The algorithm utilizes data from a single, waist-mounted triaxial accelerometer to classify gait events into six daily living activities and transitional events. The accelerometer can be worn at any location around the circumference of the waist, thereby reducing user training. Feature selection is performed using Relief-F and sequential forward floating search (SFFS) from a range of previously published features, as well as new features introduced in this paper. Relevant and robust features that are insensitive to the positioning of accelerometer around the waist are selected. SFFS selected almost half the number of features in comparison to Relief-F and provided higher accuracy than Relief-F. Activity classification is performed using Naïve Bayes and k-nearest neighbor (k-NN) and the results are compared. Activity recognition results on seven subjects with leave-one-person-out error estimates show an overall accuracy of about 98% for both the classifiers. Accuracy for each of the individual activity is also more than 95%. 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.

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Meet Our Editors

Editor-in-Chief
Bin He
Department of Biomedical Engineering