9,820 results match your criteria IEEE transactions on bio-medical engineering[Journal]


Optimizing robust PID control of propofol anesthesia for children; design and clinical evaluation.

IEEE Trans Biomed Eng 2019 Feb 8. Epub 2019 Feb 8.

Objective: The goal of this study was to optimize robust PID control for propofol anesthesia in children aged 5-10 years to improve performance, particularly to decrease the time of induction of anesthesia while maintaining robustness.

Methods: We analyzed results of a previous study conducted by our group to identify opportunities for system improvement. Allometric scaling was introduced to reduce the interpatient variability and a new robust PID controller was designed using an optimization based method. Read More

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http://dx.doi.org/10.1109/TBME.2019.2898194DOI Listing
February 2019

Contact Forces Required to Record Monophasic Action Potentials: a Complement to Catheter Contact Force Measurement.

IEEE Trans Biomed Eng 2019 Feb 14. Epub 2019 Feb 14.

Objective: The ability to monitor catheter contact force (CF) plays a major role in assessing radiofrequency ablation, impacting lesion size and arrhythmia recurrence, and dictating ablation duration and/or overall patient safety. Our study sought to determine the relative CFs required to elicit reproducible monophasic action potential (MAP) recordings.

Methods: The study utilized 4 swine in which: 1) median sternotomies were performed and MAPs were collected from 7 ventricular locations on the epicardial surface of each heart, and 2) a subset of endocardial signals was recorded from a reanimated heart. Read More

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http://dx.doi.org/10.1109/TBME.2019.2899554DOI Listing
February 2019

Surface Electromyography-based Gesture Recognition by Multi-view Deep Learning.

IEEE Trans Biomed Eng 2019 Feb 13. Epub 2019 Feb 13.

Gesture recognition using sparse multichannel Surface Electromyography (sEMG) is a challenging problem, and the solutions are far from optimal from the point of view of Muscle-Computer Interface (MCI). In this work, we address this problem from the context of multi-view deep learning. A novel multi-view Convolutional Neural Network (CNN) framework is proposed by combining classical sEMG feature sets with a CNN-based deep learning model. Read More

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http://dx.doi.org/10.1109/TBME.2019.2899222DOI Listing
February 2019
2.347 Impact Factor

High-Quality Immunohistochemical Stains through Computational Assay Parameter Optimization.

IEEE Trans Biomed Eng 2019 Feb 13. Epub 2019 Feb 13.

Accurate profiling of tumors using immunohistochemistry (IHC) is essential in cancer diagnosis. The inferences drawn from IHC-stained images depend to a great extent on the quality of immunostaining, which is in turn affected strongly by assay parameters. To optimize assay parameters, the available tissue sample is often limited. Read More

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http://dx.doi.org/10.1109/TBME.2019.2899156DOI Listing
February 2019

Evaluation of Submillimeter Diffusion Imaging of the Macaque Brain Using Readout-Segmented EPI at 7T.

IEEE Trans Biomed Eng 2019 Feb 13. Epub 2019 Feb 13.

Objective: The purpose of the present study was to achieve submillimeter-level diffusion tensor imaging (DTI) of the macaque brain by using diffusion weighted (DW) readout-segmented echo planar imaging (rsEPI) with an optimized protocol at 7T MRI.

Methods: Three anesthetized macaques were included in this study. Under different scan settings, we compared signal-to-noise ratio (SNR) and geometric distortion of DW images, implemented an optimized protocol for submillimeter-level DTI acquisition, and evaluated its performance. Read More

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http://dx.doi.org/10.1109/TBME.2019.2899132DOI Listing
February 2019

Numerical Study of Enhancement of Positive Dielectrophoresis Particle Trapping in Electrode-multilayered Microfluidic Device.

IEEE Trans Biomed Eng 2019 Feb 12. Epub 2019 Feb 12.

Enhancement of positive dielectrophoresis (pDEP) particle trapping by a co-occurring fluid flow under an AC electric field in an electrode-multilayered microfluidic device is investigated by three-dimensional particle-fluid flow simulations. The particle motion near one cross-section of the microfluidic device is simulated under a zero flow condition by the Eulerian- Lagrangian method incorporating the AC electrothermal effect, thermal buoyancy and dielectrophoresis. The mean trapping rate under the steady state R is evaluated from the simulated number of trapped particles Nrap for 54 cases with four parameters: electrode excitation pattern, medium conductivity σ, applied voltage ϕ and the real part of the Clausius-Mossotti factor Re[Kω)]. Read More

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http://dx.doi.org/10.1109/TBME.2019.2898876DOI Listing
February 2019

M/EEG-based Bio-markers to predict the Mild Cognitive Impairment and Alzheimer's disease: A Review from the Machine Learning Perspective.

IEEE Trans Biomed Eng 2019 Feb 12. Epub 2019 Feb 12.

This work reviews the state-of-the-art neuromarkers development for the prognosis of Alzheimer's diseases (AD) and mild cognitive impairment (MCI). The first part of this study is devoted to reviewing the recently-emerged machine learning (ML) algorithms based on electroencephalography (EEG) and magnetoencephalography (MEG) modalities. In particular, the methods are categorized by different types of neuromarkers. Read More

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http://dx.doi.org/10.1109/TBME.2019.2898871DOI Listing
February 2019

Cardiovascular function and ballistocardiogram: a relationship interpreted via mathematical modeling.

IEEE Trans Biomed Eng 2019 Feb 6. Epub 2019 Feb 6.

Objective: to develop quantitative methods for the clinical interpretation of the ballistocardiogram (BCG).

Methods: a closed-loop mathematical model of the cardiovascular system is proposed to theoretically simulate the mechanisms generating the BCG signal, which is then compared with the signal acquired via accelerometry on a suspended bed.

Results: simulated arterial pressure waveforms and ventricular functions are in good qualitative and quantitative agreement with those reported in the clinical literature. Read More

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http://dx.doi.org/10.1109/TBME.2019.2897952DOI Listing
February 2019

Electrode-Electrolyte Interface Modeling and Impedance Characterizing of Tripolar Concentric Ring Electrode.

IEEE Trans Biomed Eng 2019 Feb 6. Epub 2019 Feb 6.

Electrodes are used to convert ionic currents to electrical currents in biological systems. Modeling the electrode electrolyte interface and characterizing the impedance of the interface could help to optimize the performance of the electrode interface to achieve higher signal to noise ratios. Previous work has yielded accurate models for single-element biomedical electrodes. Read More

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http://dx.doi.org/10.1109/TBME.2019.2897935DOI Listing
February 2019

Incorporating Long-Acting Insulin Glargine into the UVA/ Padova Type 1 Diabetes Simulator for In Silico Testing of MDI Therapies.

IEEE Trans Biomed Eng 2019 Feb 6. Epub 2019 Feb 6.

Objective: Glargine 100U/mL (Gla-100) and 300U/mL (Gla-300) are long-acting insulin analogs providing basal insulin supply in multiple daily injection (MDI) therapy of type 1 diabetes (T1D). Both insulins require extensive testing to arrive at the optimal dosing regimen, e.g. Read More

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http://dx.doi.org/10.1109/TBME.2019.2897851DOI Listing
February 2019
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Learning cancer-related drug efficacy exploiting consensus in coordinated motility within cell clusters.

IEEE Trans Biomed Eng 2019 Feb 6. Epub 2019 Feb 6.

Objective: The ability of cells to collectively move is essential in various biological contexts including cancer metastasis. In this work, we propose an automatic video analysis tool to correlate cell movement inhibition with replication block induced by dose-dependent chemotherapy administration. The novel approach combines individual and collective cell kinematic analysis performed over time-lapse microscopy video frames. Read More

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http://dx.doi.org/10.1109/TBME.2019.2897825DOI Listing
February 2019

EEG based emotion recognition by combining functional connectivity network and local activations.

IEEE Trans Biomed Eng 2019 Feb 5. Epub 2019 Feb 5.

Objective: Spectral power analysis plays a predominant role in electroencephalogram (EEG) based emotional recognition. It can reflect activity differences among multiple brain regions. In addition to activation difference, different emotions also involve different large-scale network during related information processing. Read More

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http://dx.doi.org/10.1109/TBME.2019.2897651DOI Listing
February 2019
1 Read

A novel gastric pacing device to modulate slow waves and assessment by high-resolution mapping.

IEEE Trans Biomed Eng 2019 Feb 5. Epub 2019 Feb 5.

Objective: The use of electroceuticals in the gastrointestinal field continues to advance, however, the efficacy and effectiveness of clinical gastric stimulation and pacing remains limited. In the stomach, rhythmic bioelectrical events known as slow waves coordinates the muscular contractions that aid digestion. A range of slow wave abnormalities have been shown to be associated with functional motility disorders, such as gastroparesis, chronic unexplained nausea and vomiting, and functional dyspepsia. Read More

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http://dx.doi.org/10.1109/TBME.2019.2896624DOI Listing
February 2019

Severe Dengue Prognosis Using Human Genome Data and Machine Learning.

IEEE Trans Biomed Eng 2019 Feb 4. Epub 2019 Feb 4.

Dengue has become one of the most important worldwide arthropod-borne diseases. Dengue phenotypes are based on laboratorial and clinical exams, which are known to be inaccurate.

Objective: We present a machine learning approach for the prediction of dengue fever severity based solely on human genome data. Read More

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http://dx.doi.org/10.1109/TBME.2019.2897285DOI Listing
February 2019
1 Read

Optimum wavelengths in the near infrared for imaging photoplethysmography.

IEEE Trans Biomed Eng 2019 Feb 4. Epub 2019 Feb 4.

Objective: The purpose of this contribution is to determine the ideal near infrared wavelength bands for monochromatic and dual-band remote heartbeat detection using imaging photoplethysmography of the forehead.

Methods: Experimental data of 38 healthy volunteers has been recorded and analyzed. For the data acquisition a fast hyperspectral imager has been used. Read More

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http://dx.doi.org/10.1109/TBME.2019.2897284DOI Listing
February 2019

A coaxial RF applicator for ultra high field human MRI.

IEEE Trans Biomed Eng 2019 Feb 1. Epub 2019 Feb 1.

Objective: To describe a novel radio-frequency (RF) concept for ultra-high field (UHF) human magnetic resonance imaging (MRI) based on a coaxial cavity.

Methods: A two-channel slotted coaxial cavity RF applicator was designed for human head MRI at 9.4T. Read More

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https://ieeexplore.ieee.org/document/8632760/
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http://dx.doi.org/10.1109/TBME.2019.2897029DOI Listing
February 2019
2 Reads

Vessel Wall Segmentation Using Convolutional Neural Networks.

IEEE Trans Biomed Eng 2019 Feb 1. Epub 2019 Feb 1.

Objective: To develop an automated vessel wall segmentation method using convolutional neural networks (CNN) to facilitate the quantification on magnetic resonance (MR) vessel wall images of patients with intracranial atherosclerotic disease (ICAD).

Methods: Vessel wall images of 56 subjects were acquired with our recently developed whole-brain 3D MR vessel wall imaging (VWI) technique. An intracranial vessel analysis (IVA) framework was presented to extract, straighten, and resample the interested vessel segment into 2D slices. Read More

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http://dx.doi.org/10.1109/TBME.2019.2896972DOI Listing
February 2019
2.347 Impact Factor

Multiscale Functional Clustering Reveals Frequency Dependent Brain Organization in Type II Focal Cortical Dysplasia with Sleep Hypermotor Epilepsy.

IEEE Trans Biomed Eng 2019 Feb 1. Epub 2019 Feb 1.

Objective: A multiscale functional clustering approach is proposed to investigate the organization of the epileptic networks (EN) during different sleep stages and in relation with the occurrence of seizures.

Method: Stereo-electroencephalographic signals from seven pharmaco-resistant epileptic patients (FCD type II) were analyzed. The discrete wavelet transform provided a multiscale framework on which a data-driven functional clustering procedure was applied, based on multivariate measures of integration and mutual information. Read More

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http://dx.doi.org/10.1109/TBME.2019.2896893DOI Listing
February 2019
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Estimating the Memory Order of Electrocorticography Recordings.

IEEE Trans Biomed Eng 2019 Jan 30. Epub 2019 Jan 30.

Objective: This paper presents a data-driven method for estimating the memory order of a recorded Electrocorticography (ECoG) sequence.

Methods: The proposed inference method is based on the relationship between the loss in predicting the next sample in a time-series, and the dependence of this sample on the previous samples. Specifically, the memory order is estimated to be the number of past samples that minimizes the least squares error (LSE) in predicting the next sample. Read More

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http://dx.doi.org/10.1109/TBME.2019.2896076DOI Listing
January 2019

Leveraging device-arterial coupling to determine cardiac and vascular state.

IEEE Trans Biomed Eng 2019 Jan 28. Epub 2019 Jan 28.

Objective: Limitations in available diagnostic metrics restrict the efficacy of managing therapies for cardiogenic shock. In current clinical practice, cardiovascular state is inferred through measurement of pulmonary capillary wedge pressure and reliance on linear approximations between pressure and flow to estimate peripheral vascular resistance. Mechanical circulatory support devices residing within the left ventricle and aorta provide an opportunity for both determining cardiac and vascular state and offering therapeutic benefit. Read More

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http://dx.doi.org/10.1109/TBME.2019.2895752DOI Listing
January 2019
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Multi-mode Particle Filtering Methods for Heart Rate Estimation from Wearable Photoplethysmography.

IEEE Trans Biomed Eng 2019 Jan 28. Epub 2019 Jan 28.

Objective: Obtaining accurate estimates of instantaneous heart rates (HRs) using reflectance-type photoplethysmography (PPG) sensors is challenging because the dominant frequency observed in the PPG signal can be corrupted by motion artifacts (MAs), especially during exercise. To address this problem, we propose multi-mode particle filtering (MPF) methods.

Methods: We propose four MPF methods based on different approaches to particle weighting and HR determination. Read More

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http://dx.doi.org/10.1109/TBME.2019.2895685DOI Listing
January 2019

A Scale Mixture-based Stochastic Model of Surface EMG Signals with Variable Variances.

IEEE Trans Biomed Eng 2019 Jan 28. Epub 2019 Jan 28.

Objective: Surface electromyogram (EMG) signals have typically been assumed to follow a Gaussian distribution. However, the presence of non-Gaussian signals associated with muscle activity has been reported in recent studies, and there is no general model of the distribution of EMG signals that can explain both non-Gaussian and Gaussian distributions within a unified scheme.

Methods: In this paper, we describe the formulation of a non-Gaussian EMG model based on a scale mixture distribution. Read More

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http://dx.doi.org/10.1109/TBME.2019.2895683DOI Listing
January 2019
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Deep Neural Generative Model of Functional MRI Images for Psychiatric Disorder Diagnosis.

IEEE Trans Biomed Eng 2019 Jan 28. Epub 2019 Jan 28.

Accurate diagnosis of psychiatric disorders plays a critical role in improving the quality of life for patients and potentially supports the development of new treatments. Many studies have been conducted on machine learning techniques that seek brain imaging data for specific biomarkers of disorders. These studies have encountered the following dilemma: An end-to-end classification overfits to a small number of high-dimensional samples but unsupervised feature-extraction has the risk of extracting a signal of no interest. Read More

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http://dx.doi.org/10.1109/TBME.2019.2895663DOI Listing
January 2019
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Evoked Haptic Sensation in the Hand with Concurrent Non-Invasive Nerve Simulation.

IEEE Trans Biomed Eng 2019 Jan 28. Epub 2019 Jan 28.

Objective: Haptic perception is critical for prosthetic users to control their prosthetic hand intuitively. In this study, we seek to evaluate the haptic perception evoked from concurrent stimulation trains through multiple channels using transcutaneous nerve stimulation.

Methods: A 2x8 electrode grid was used to deliver current to the median and ulnar nerves in the upper arm. Read More

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https://ieeexplore.ieee.org/document/8627974/
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http://dx.doi.org/10.1109/TBME.2019.2895575DOI Listing
January 2019
3 Reads

Wrap-Around Wearable Coils for Seamless Monitoring of Joint Flexion.

IEEE Trans Biomed Eng 2019 Jan 25. Epub 2019 Jan 25.

Objective: We introduce and validate a new class of wearable coils that seamlessly monitor joint flexion in the individual's natural environment while overcoming shortcomings in the state-of-the-art.

Methods: Our approach relies on Faraday's Law of Induction and employs wrap-around transmit and receive coils that get angularly misaligned as the joint flexes.

Results: Simulation and in vitro measurement results for both copper and e-thread coils are in excellent agreement. Read More

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http://dx.doi.org/10.1109/TBME.2019.2895293DOI Listing
January 2019

Bayesian inference-based estimation of normal aortic, aneurysmal and atherosclerotic tissue mechanical properties: from material testing, modelling and histology.

IEEE Trans Biomed Eng 2019 Jan 25. Epub 2019 Jan 25.

Objective: Mechanical properties of healthy, aneurysmal and atherosclerotic arterial tissues are essential for assessing the risk of lesion development and rupture. Strain energy density function (SEDF) has been widely used to describe these properties, where material constants of the SEDF are traditionally determined using the ordinary least square (OLS) method. However, the material constants derived using OLS are usually dependent on initial guesses. Read More

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http://dx.doi.org/10.1109/TBME.2018.2886681DOI Listing
January 2019
1 Read

A framework for measuring the time-varying shape and full-field deformation of residual limbs using 3D digital image correlation.

IEEE Trans Biomed Eng 2019 Jan 24. Epub 2019 Jan 24.

Effective prosthetic socket design following lower-limb amputation depends upon the accurate characterization of the shape of the residual limb as well as its volume and shape fluctuations.

Objective: This study proposes a novel framework for the measurement and analysis of residual limb shape and deformation, using a high-resolution and low-cost system.

Methods: A multi-camera system was designed to capture sets of simultaneous images of the entire residuum surface. Read More

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http://dx.doi.org/10.1109/TBME.2019.2895283DOI Listing
January 2019
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Gradient Field Deviation (GFD) Correction using a Hybrid-norm Approach with Wavelet Sub-band Dependent Regularisation: Implementation for Radial MRI at 9.4 T.

IEEE Trans Biomed Eng 2019 Jan 24. Epub 2019 Jan 24.

In magnetic resonance imaging (MRI), system imperfections and eddy currents can cause gradient field deviation (GFD), leading to various image distortions such as increased noise, ghosting artefacts and geometric deformation. These distortions can degrade the clinical value of MR images. Generally, non-Cartesian image sequences, such as radial sampling, produce larger gradient deviations than Cartesian sampling, as a result of stronger eddy current-induced gradient delays and phase errors. Read More

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http://dx.doi.org/10.1109/TBME.2019.2895091DOI Listing
January 2019

Bayesian Inference Identifies Combination Therapeutic Targets in Breast Cancer.

IEEE Trans Biomed Eng 2019 Jan 23. Epub 2019 Jan 23.

Objective: Breast Cancer is the second leading cause of cancer death among US women, hence identifying potential drug targets is an ever increasing need. In this paper, we integrate existing biological information with graphical models to deduce the significant nodes in the Breast Cancer signaling pathway.

Methods: We make use of biological information from the literature to develop a Bayesian network. Read More

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https://ieeexplore.ieee.org/document/8624316/
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http://dx.doi.org/10.1109/TBME.2019.2894980DOI Listing
January 2019
5 Reads

Electroporation induced stress response and its effect on gene electrotransfer efficacy: in vivo imaging and numerical modelling.

IEEE Trans Biomed Eng 2019 Jan 23. Epub 2019 Jan 23.

Objective: Skin is an attractive target tissue for gene transfer due to its size, accessibility and its immune competence. One of the promising delivery methods is gene delivery by means of electroporation (EP), i.e. Read More

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http://dx.doi.org/10.1109/TBME.2019.2894659DOI Listing
January 2019

A New RF Heating Strategy for Thermal Treatment of Atherosclerosis.

IEEE Trans Biomed Eng 2019 Jan 21. Epub 2019 Jan 21.

Objectives: Restenosis remains a challenge for treatment of atherosclerosis due to damage of the endothelial layer and induced proliferation of the smooth muscle cell.

Methods: A new RF heating strategy was proposed to selectively ablate the atherosclerosis plaque, and to thermally inhibit the proliferation of smooth muscle cells, while keeping the endothelial cells intact. To achieve the goal, an internal cooling agent and distributed electrodes have been integrated in the new designed balloon cathode to focus the shape conformal energy onto the plaque shape. Read More

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https://ieeexplore.ieee.org/document/8620531/
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http://dx.doi.org/10.1109/TBME.2019.2894503DOI Listing
January 2019
3 Reads

Axonal Anatomy Optimizes Spatial Encoding in the Rat Entorhinal-Dentate System: A Computational Study.

IEEE Trans Biomed Eng 2019 Jan 21. Epub 2019 Jan 21.

Objective: The network architecture connecting neural regions is defined by the organization and anatomical properties of the projecting axons, but its contributions to neural encoding and system function are difficult to study experimentally.

Methods: Using a large-scale, spiking neuronal network model of rat dentate gyrus, the role of the anatomy of the entorhinal-dentate axonal projection was evaluated in the context of spatial encoding by incorporating grid cell activity to provide physiological, spatially-correlated input. The dorso-ventral extent of the entorhinal axon terminal field was varied to generate different feedforward architectures, and the resulting spatial representations and spatial information scores of the network were evaluated. Read More

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http://dx.doi.org/10.1109/TBME.2019.2894410DOI Listing
January 2019
2 Reads

Auto-regressive Discrete Acquisition Points Transformation for Diffusion Weighted MRI Data.

IEEE Trans Biomed Eng 2019 Jan 24. Epub 2019 Jan 24.

ObjectivObjective: A new method for fitting Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) data composed of an unknown number of multi-exponential components is presented and evaluated.

Methods: The Auto-regressive Discrete Acquisition Points Transformation (ADAPT) method is an adaption of the auto-regressive moving average system, which allows for the modelling of multi-exponential data and enables the estimation of the number of exponential components without prior assumptions. ADAPT was evaluated on simulated DW-MRI data. Read More

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http://dx.doi.org/10.1109/TBME.2019.2893523DOI Listing
January 2019

Toward Unobtrusive In-home Gait Analysis Based on Radar Micro-Doppler Signatures.

IEEE Trans Biomed Eng 2019 Jan 16. Epub 2019 Jan 16.

Objective: In this paper, we demonstrate the applicability of radar for gait classification with application to home security, medical diagnosis, rehabilitation and assisted living. Aiming at identifying changes in gait patterns based on radar micro-Doppler signatures, this work is concerned with solving the intra motion category classification problem of gait recognition.

Methods: New gait classification approaches utilizing physical features, subspace features and sum-of-harmonics modeling are presented and their performances are evaluated using experimental K-band radar data of four test subjects. Read More

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http://dx.doi.org/10.1109/TBME.2019.2893528DOI Listing
January 2019

Noninvasive imaging of epicardial and endocardial potentials with low rank and sparsity constraints.

IEEE Trans Biomed Eng 2019 Jan 21. Epub 2019 Jan 21.

In this study, we explore the use of low rank and sparse constraints for the noninvasive estimation of epicardial and endocardial extracellular potentials from body-surface electrocardiographic data to locate the focus of premature ventricular contractions (PVCs). The proposed strategy formulates the dynamic spatiotemporal distribution of cardiac potentials by means of low rank and sparse decomposition, where the low rank term represents the smooth background and the anomalous potentials are extracted in the sparse matrix. Compared to the most previous potential-based approaches, the proposed low rank and sparse constraints are batch spatiotemporal constraints that capture the underlying relationship of dynamic potentials. Read More

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https://ieeexplore.ieee.org/document/8620345/
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http://dx.doi.org/10.1109/TBME.2019.2894286DOI Listing
January 2019
10 Reads

Liver Extraction Using Residual Convolution Neural Networks from Low-Dose CT Images.

IEEE Trans Biomed Eng 2019 Jan 21. Epub 2019 Jan 21.

An efficient and precise liver extraction from computed tomography (CT) images is a crucial step for computeraided hepatic diseases diagnosis and treatment. Considering the possible risk to patient's health due to X-ray radiation of repetitive CT examine, low-dose CT (LDCT) is an effective solution for medical imaging. However, inhomogeneous appearances and indistinct boundaries due to additional noise and streaks artifacts in LDCT images often make it a challenging task. Read More

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https://ieeexplore.ieee.org/document/8620270/
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http://dx.doi.org/10.1109/TBME.2019.2894123DOI Listing
January 2019
6 Reads

Maximum entropy based non-negative optoacoustic tomographic image reconstruction.

IEEE Trans Biomed Eng 2019 Jan 14. Epub 2019 Jan 14.

Objective: Optoacoustic (photoacoustic) tomography is aimed at reconstructing maps of the initial pressure rise induced by the absorption of light pulses in tissue. In practice, due to inaccurate assumptions in the forward model, noise and other experimental factors, the images are often afflicted by artifacts, occasionally manifested as negative values. The aim of the work is to develop an inversion method which reduces the occurrence of negative values and improves the quantitative performance of optoacoustic imaging. Read More

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http://dx.doi.org/10.1109/TBME.2019.2892842DOI Listing
January 2019

Lower limb pulse rise time as a marker of peripheral arterial disease.

IEEE Trans Biomed Eng 2019 Jan 11. Epub 2019 Jan 11.

Objective: The aim of the study was to show if pulse rise times (PRTs) extracted from photoplethysmographic (PPG) pulse waves (PWs) have an association with peripheral arterial disease (PAD) or its endovascular treatment, percutanoeus transluminal angioplasty (PTA) of the superficial femoral artery.

Methods: Lower and upper limb PPG PWs were recorded and analyzed from 24 patients who suffered from PAD. The measurements were conducted before and after the treatment, and one month later by using transmission-mode PPG-probes placed in the index finger and second toe. Read More

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https://ieeexplore.ieee.org/document/8610175/
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http://dx.doi.org/10.1109/TBME.2019.2892407DOI Listing
January 2019
2 Reads

A Practical Approach to Electrode-Skin Impedance Unbalance Measurement.

IEEE Trans Biomed Eng 2019 Jan 14. Epub 2019 Jan 14.

Unbalance between electrode-skin impedances is a major problem in biopotential recordings, leading to increased power-line interference. This paper proposes a simple, direct method to measure that unbalance at power-line frequency (50-60Hz), thus allowing the determination of actual recording conditions for biopotential amplifiers. the method is useful in research, amplifier testing, electrode design and teaching purposes. Read More

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http://dx.doi.org/10.1109/TBME.2006.873699DOI Listing
January 2019
1 Read

Neural Spike Train Synchronisation Indices: Definitions, Interpretations and Applications.

IEEE Trans Biomed Eng 2019 Jan 14. Epub 2019 Jan 14.

A comparison of previously defined spike train syncrhonization indices is undertaken within a stochastic point process framework. The second order cumulant density (covariance density) is shown to be common to all the indices. Simulation studies were used to investigate the sampling variability of a single index based on the second order cumulant. Read More

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http://dx.doi.org/10.1109/TBME.2006.871886DOI Listing
January 2019

Sparse Deconvolution of Electrodermal Activity via Continuous-Time System Identification.

IEEE Trans Biomed Eng 2019 Jan 10. Epub 2019 Jan 10.

Objective: Electrodermal activity (EDA) indicates different eccrine sweat gland activity caused by the stimulation of the autonomic nervous system. Recovering the number, timings, and amplitudes of underlying neural stimuli and physiological system parameters from EDA is a challenging problem. One of the challenges with the existing methods is the non-convexity of the optimization formulations for estimating the parameters given the stimuli. Read More

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http://dx.doi.org/10.1109/TBME.2019.2892352DOI Listing
January 2019

Combining metrics from clinical simulators and sensorimotor tasks can reveal the training background of surgeons.

IEEE Trans Biomed Eng 2019 Jan 10. Epub 2019 Jan 10.

Background: Skill assessment in surgery traditionally has relied on expert observation and qualitative scoring. Our novel study design demonstrates how analysis of performance in sensorimotor tasks and bench-top surgical simulators can provide inferences about the technical proficiency as well as the training history of surgeons.

Methods: Our unique study design examined metrics for basic sensorimotor tasks in a virtual reality interface as well as motion metrics in clinical scenario simulations. Read More

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http://dx.doi.org/10.1109/TBME.2019.2892342DOI Listing
January 2019
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3D Microwave Tomography Using the Soft Prior Regularization Technique: Evaluation in Anatomically-Realistic MRI-Derived Numerical Breast Phantoms.

IEEE Trans Biomed Eng 2019 Jan 10. Epub 2019 Jan 10.

Objective: Fusion of magnetic resonance imaging (MRI) breast images with microwave tomography is accomplished through a soft prior technique, which incorporates spatial information (from MRI), i.e. accurate boundary location of different regions of interest, into the regularization process of the microwave image reconstruction algorithm. Read More

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http://dx.doi.org/10.1109/TBME.2019.2892303DOI Listing
January 2019

Evolving Gaussian Process Autoregression based Learning of Human Motion Intent Using Improved Energy Kernel Method of EMG.

IEEE Trans Biomed Eng 2019 Jan 10. Epub 2019 Jan 10.

Continuous human motion intent learning may be modeled using a Gaussian process (GP) autoregression based evolving system to cope with the unspecified and time-varying motion patterns. Electromyography (EMG) signals are the primary input. GP is used as a mathematical foundation to model human kinematics by adopting the nonlinear autoregressive with exogenous inputs (NARX) framework, and an evolving system is applied to learn the irregular and unspecified dynamic features. Read More

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http://dx.doi.org/10.1109/TBME.2019.2892084DOI Listing
January 2019
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Dominant-Current Deep Learning Scheme for Electrical Impedance Tomography.

IEEE Trans Biomed Eng 2019 Jan 9. Epub 2019 Jan 9.

Deep learning has recently been applied to electrical impedance tomography (EIT) imaging. Nevertheless, there are still many challenges that this approach has to face, e.g. Read More

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https://ieeexplore.ieee.org/document/8606211/
Publisher Site
http://dx.doi.org/10.1109/TBME.2019.2891676DOI Listing
January 2019
4 Reads

Long-term developmental process of the human cortex revealed in vitro by axon-targeted recording using a microtunnel-augmented microelectrode array.

IEEE Trans Biomed Eng 2019 Jan 7. Epub 2019 Jan 7.

Objective: We aimed to develop a method for evaluating developmental changes in the synchronized activity of human induced pluripotent stem cell (hiPSC)-derived neurons without extrinsic signals from feeder astrocytes.

Methods: Microelectrode arrays (MEAs) and microtunnels were fabricated with photolithography and soft lithography. Human iPSCs were induced to differentiate into cortical neurons, and seeded to conventional and microtunnel MEAs. Read More

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http://dx.doi.org/10.1109/TBME.2019.2891310DOI Listing
January 2019

Robotic Transrectal Ultrasound-Guided Prostate Biopsy.

IEEE Trans Biomed Eng 2019 Jan 7. Epub 2019 Jan 7.

We present a robot-assisted approach for transrectal ultrasound (TRUS) guided prostate biopsy. The robot is a hands-free probe manipulator that moves the probe with the same 4 degrees-of-freedom (DoF) that are used manually. Software was developed for 3D imaging, biopsy planning, robot control, and navigation. Read More

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Source
https://ieeexplore.ieee.org/document/8604089/
Publisher Site
http://dx.doi.org/10.1109/TBME.2019.2891240DOI Listing
January 2019
3 Reads

Visualizing Interactions of Circulating Tumor Cell and Dendritic Cell in the Blood Circulation Using In Vivo Imaging Flow Cytometry.

IEEE Trans Biomed Eng 2019 Jan 7. Epub 2019 Jan 7.

Objective: Visualizing cell interactions in blood circulation is of great importance in studies of anticancer immunotherapy or drugs. However, the lack of a suitable imaging system hampers progress in this field.

Methods: In this work, we built a dual-channel in vivo imaging flow cytometer to visualize the interactions of circulating tumor cells (CTCs) and dendritic cells (DCs) simultaneously in the bloodstream. Read More

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http://dx.doi.org/10.1109/TBME.2019.2891068DOI Listing
January 2019

A Novel Controllable Cell Array Printing Technique on Microfluidic Chips.

IEEE Trans Biomed Eng 2019 Jan 4. Epub 2019 Jan 4.

Goal: The construction of single-cell array is known as the challenging technology to manipulate cell position and number and accomplish cell analysis in biomedical engineering.

Methods: We put forward a novel controllable cell printing technique for rapid, precise, convenient, high cell viability, multicellular, and high-throughput printing. We also proposed a novel microfluidic device to verify the effectiveness of the printing and study the migration ability and anti-cancer drug responses of cancer cell as important applications. Read More

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http://dx.doi.org/10.1109/TBME.2019.2891016DOI Listing
January 2019
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Impedance-based Gaussian Processes for Modeling Human Motor Behavior in Physical and Non-physical Interaction.

IEEE Trans Biomed Eng 2019 Jan 1. Epub 2019 Jan 1.

Objective: Modeling of human motor intention plays an essential role in predictively controlling a robotic system in human-robot interaction tasks. In most machine learning techniques, human motor behavior is modeled as a generic stochastic process. However, the integration of a priori knowledge about underlying system structures can provide insights on otherwise unobservable intrinsic states that yield superior prediction performance and increased generalization capabilities. Read More

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http://dx.doi.org/10.1109/TBME.2018.2890710DOI Listing
January 2019