Precise detection of early breast tumor using a novel EEMD-based feature extraction approach by UWB microwave
In this study, 11,232 sets of backscatter signals from simulation results of four different categories ’ breast models are utilized. And feature dataset is constructed by 24 specific features from each signal’s four valid components. The results demonstrate that the proposed method can extract representative features and detect the early breast cancer effectively with the accuracy of 84.8%.Graphical abstract (Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - February 24, 2021 Category: Biomedical Engineering Source Type: research

The effect of asymmetrical gait induced by unilateral knee brace on the knee flexor and extensor muscles
This study proposes the use of dynamic musculoskeletal modelling simulation to investigate the effect of induced mechanical perturbation on the kneeand to examine the muscle behaviour without invasive technique. Thirty-eight healthy pa rticipants were recruited. Asymmetrical gait was simulated using knee brace. Knee joint angle, joint moment and knee flexor and extensor muscle forces were computed using OpenSim. Differences inmuscle force between normal and abnormal conditions were investigated using ANOVA and Tukey-Kramer multip le comparison test.The results revealed that braced knee experie...
Source: Medical and Biological Engineering and Computing - February 24, 2021 Category: Biomedical Engineering Source Type: research

A three-compartment non-linear model of myocardial cell conduction block during photosensitization
This study constructed a new non-linear model of myocardial electrical conduction block during photosensitization reaction to identify the vulnerable cell population and generate an index for recurrent risk following catheter ablation for tachyarrhythmia. A three-compartment model of conductive, vulnerable, and blocked cells was proposed. To determine the non-linearity of the rate parameter for the change from vulnerable cells to conductive cells, we compared a previously reported non-linear model and our newly proposed model with non-linear rate parameters in the modeling of myocardial cell electrical conduction block dur...
Source: Medical and Biological Engineering and Computing - February 19, 2021 Category: Biomedical Engineering Source Type: research

Studies of the criteria for determining optimal location of medial patellofemoral ligament attachment sites
This study reaffirms that MPFL reconstruction is subject specific. The isometric criterion may be more reliable than the desired pattern criterion for determining optimal attachment sites.Graphical Abstract. Highlight of the paper. The location of the patella site significantly affects the location of the optimal femoral site. The isometric criterion option 1, with length at 0 ° regarded as MPFL's natural length, may be more reliable than other criteria or options for the planning of MPFL surgery because the optimal sites that it finds are closest to known anatomical sites.ᅟ (Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - February 17, 2021 Category: Biomedical Engineering Source Type: research

Classification of Homo sapiens gene behavior using linear discriminant analysis fused with minimum entropy mapping
AbstractClassification of Homo sapiens gene behavior employing computational biology is a recent research trend. But monitoring gene activity profile and genetic behavior from the alphabetic DNA sequence using a non-invasive method is a tremendous challenge in functional genomics. The present paper addresses such issue and attempts to differentiate Homo sapiens genes using linear discriminant analysis (LDA) method. Annotated protein coding sequences of Homo sapiens genes, collected from NCBI, are taken as test samples. Minimum entropy-based mapping (MEM) technique assists to extract highest information from the numerical D...
Source: Medical and Biological Engineering and Computing - February 17, 2021 Category: Biomedical Engineering Source Type: research

Applicability of a single camera-based catheter navigation system using teeth arch as an anatomical landmark for superselective intraarterial infusion in advanced oral cancer treatment
In this study, we propose the new application of this tracking system and a novel method of catheteri zation for superselective intraarterial infusion chemoradiotherapy for oral cancer.Graphical abstractIn retrograde superselective intraarterial catheterization, a catheter is inserted into a tumor-feeding artery originating from the external carotid artery (ECA) (the lingual artery [LA], facial artery [FA], or maxillary artery [MA]). Because the maxillary dentition is located near the external carotid artery, we focused on real-time markerless registration using maxillary dentition fixed to the skull. (Source: Medical and ...
Source: Medical and Biological Engineering and Computing - February 16, 2021 Category: Biomedical Engineering Source Type: research

EEG-based hybrid QWERTY mental speller with high information transfer rate
ConclusionQWERTY speller outperformed the stereotypical P300 speller as well as QWERTY SSVEP speller.Graphical abstract (Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - February 16, 2021 Category: Biomedical Engineering Source Type: research

Classification of orthostatic intolerance through data analytics
This study uses machine learning to categorize patients with orthostatic intolerance. We use random forest classification trees to identify a small number of markers in blood pressure, and heart rate time-series data measured during head-up tilt to (a) distinguish patients with a single pathology and (b) examine data from patients with a mixed pathophysiology. Next, we use Kmeans to cluster the markers representing the time-series data. We apply the proposed method analyzing clinical data from 186 subjects identified as control or suffering from one of four conditions: postural orthostatic tachycardia (POTS), cardioinhibit...
Source: Medical and Biological Engineering and Computing - February 13, 2021 Category: Biomedical Engineering Source Type: research

Joint low-rank prior and difference of Gaussian filter for magnetic resonance image denoising
AbstractThe low-rank matrix approximation (LRMA) is an efficient image denoising method to reduce additive Gaussian noise. However, the existing low-rank matrix approximation does not perform well in terms of Rician noise removal for magnetic resonance imaging (MRI). To this end, we propose a novel MR image denoising approach based on the extended difference of Gaussian (DoG) filter and nonlocal low-rank regularization. In the proposed method, a novel nonlocal self-similarity evaluation with the tight frame is exploited to improve the patch matching. To remove the Rician noise and preserve the edge details, the extended Do...
Source: Medical and Biological Engineering and Computing - February 13, 2021 Category: Biomedical Engineering Source Type: research

Frequency-specific network effective connectivity: ERP analysis of recognition memory process by directed connectivity estimators
AbstractHuman memory retrieval is one of the brain ’s most important, and least understood cognitive mechanisms. Traditionally, research on this aspect of memory has focused on the contributions of particular brain regions to recognition responses, but the interaction between regions may be of even greater importance to a full understanding. In th is study, we examined patterns of network connectivity during retrieval in a recognition memory task. We estimated connectivity between brain regions from electroencephalographic signals recorded from twenty healthy subjects. A multivariate autoregressive model (MVAR) was u...
Source: Medical and Biological Engineering and Computing - February 9, 2021 Category: Biomedical Engineering Source Type: research

A cascaded FC-DenseNet and level set method (FCDL) for fully automatic segmentation of the right ventricle in cardiac MRI
AbstractAccurate segmentation of the right ventricle (RV) from cardiac magnetic resonance imaging (MRI) images is an essential step in estimating clinical indices such as stroke volume and ejection fraction. Recently, image segmentation methods based on fully convolutional neural networks (FCN) have drawn much attention and shown promising results. In this paper, a new fully automatic RV segmentation method combining the FC-DenseNet and the level set method (FCDL) is proposed. The FC-DenseNet is efficiently trained end-to-end, using RV images and ground truth masks to make a per-pixel semantic inference. As a result, proba...
Source: Medical and Biological Engineering and Computing - February 9, 2021 Category: Biomedical Engineering Source Type: research

An efficient medical image encryption using hybrid DNA computing and chaos in transform domain
AbstractIn this growing era, a massive amount of digital electronic health records (EHRs) are transferred through the open network. EHRs are at risk of a myriad of security threats, to overcome such threats, encryption is a reliable technique to secure data. This paper addresses an encryption algorithm based on integer wavelet transform (IWT) blended with deoxyribo nucleic acid (DNA) and chaos to secure the digital medical images. The proposed work comprises of two phases, i.e. a two-stage shuffling phase and diffusion phase. The first stage of shuffling starts with initial block confusion followed by row and column shuffl...
Source: Medical and Biological Engineering and Computing - February 9, 2021 Category: Biomedical Engineering Source Type: research

Altered mechanical properties of actin fibers due to breast cancer invasion: parameter identification based on micropipette aspiration and multiscale tensegrity modeling
This study highlights the function of cytoskeletal fibers in cancer progression, which could be of interest in designing therapeutic strategies to target cancer progress.Graphical abstractFirstly, the viscoelastic behavior of non-invasive and invasive cells is examined with micropipette aspiration tests. A tensegrity model of cells is developed to mimic the viscoelastic behavior of cells, and tensegrity element stiffness is evaluated in an optimization procedure based on micropipette aspiration tests. Finally, by using immunofluorescent staining and confocal imaging, mechanical properties of actin filaments and microtubule...
Source: Medical and Biological Engineering and Computing - February 8, 2021 Category: Biomedical Engineering Source Type: research

A comparison of machine learning classifiers for smartphone-based gait analysis
AbstractThis paper proposes a reliable monitoring scheme that can assist medical specialists in watching over the patient ’s condition. Although several technologies are traditionally used to acquire motion data of patients, the high costs as well as the large spaces they require make them difficult to be applied in a home context for rehabilitation. A reliable patient monitoring technique, which can automatically re cord and classify patient movements, is mandatory for a telemedicine protocol. In this paper, a comparison of several state-of-the-art machine learning classifiers is proposed, where stride data are coll...
Source: Medical and Biological Engineering and Computing - February 6, 2021 Category: Biomedical Engineering Source Type: research

Wilson disease tissue classification and characterization using seven artificial intelligence models embedded with 3D optimization paradigm on a weak training brain magnetic resonance imaging datasets: a supercomputer application
AbstractWilson ’s disease (WD) is caused by copper accumulation in the brain and liver, and if not treated early, can lead to severe disability and death. WD has shown white matter hyperintensity (WMH) in the brain magnetic resonance scans (MRI) scans, but the diagnosis is challenging due to (i) subtle intensity changes and (ii) weak training MRI when using artificial intelligence (AI). Design and validate seven types of high-performing AI-based computer-aided design (CADx) systems consisting of 3D optimized classification, and characterization of WD against controls. We propose a “conventional deep conv olutio...
Source: Medical and Biological Engineering and Computing - February 5, 2021 Category: Biomedical Engineering Source Type: research

Length of hospital stay prediction with an integrated approach of statistical-based fuzzy cognitive maps and artificial neural networks
In this study, an integrated approach of the statistical-based fuzzy cognitive maps (SBFCM) and artificial neural networks (ANN) is proposed for predicting length of hospital stay of patients with COPD, who admitted to the hospital with an acute exacerbation. The SBFCM method is developed to determine the input variables of the ANN model. The SBFCM conducts statistical analysis to prepare preliminary information for the experts and then collects expert opinions accordingly, to define a conceptual map of the system. The integration of SBFCM and ANN methods provides both statistical data and expert opinion in the prediction ...
Source: Medical and Biological Engineering and Computing - February 5, 2021 Category: Biomedical Engineering Source Type: research

Optimizing ANFIS using simulated annealing algorithm for classification of microarray gene expression cancer data
AbstractIn the medical field, successful classification of microarray gene expression data is of major importance for cancer diagnosis. However, due to the profusion of genes number, the performance of classifying DNA microarray gene expression data using statistical algorithms is often limited. Recently, there has been an important increase in the studies on the utilization of artificial intelligence methods, for the purpose of classifying large-scale data. In this context, a hybrid approach based on the adaptive neuro-fuzzy inference system (ANFIS), the fuzzy c-means clustering (FCM), and the simulated annealing (SA) alg...
Source: Medical and Biological Engineering and Computing - February 5, 2021 Category: Biomedical Engineering Source Type: research

Item response theory as a feature selection and interpretation tool in the context of machine learning
AbstractOptimizing the number and utility of features to use in a classification analysis has been the subject of many research studies. Most current models use end-classifications as part of the feature reduction process, leading to circularity in the methodology. The approach demonstrated in the present research uses item response theory (IRT) to select features independent of the end-classification results without the biased accuracies that this circularity engenders. Dichotomous and polytomous IRT models were used to analyze 30 histological breast cancer features from 569 patients using the Wisconsin Diagnostic Breast ...
Source: Medical and Biological Engineering and Computing - February 3, 2021 Category: Biomedical Engineering Source Type: research

A coarse-to-fine registration method for three-dimensional MR images
AbstractThree-dimensional (3D) multimodal magnetic resonance (MR) image registration aims to align similar things in different MR images spatially. Such a technology is useful in auxiliary disease diagnosis and surgical treatment. However, inconsistent intensity correspondence and large initial displacement contribute to the difficulty in registering multimodal MR volumes. A coarse-to-fine method is proposed in this study for pairwise 3D MR image rigid registration. Firstly, the proposed method extracts image feature points to form unregistered point sets and performs coarse registration based on point set registration to ...
Source: Medical and Biological Engineering and Computing - January 29, 2021 Category: Biomedical Engineering Source Type: research

ManoMap: an automated system for characterization of colonic propagating contractions recorded by high-resolution manometry
ConclusionsAn automated framework was developed to filter, detect, quantify, and visualize propagating contractions in cHRM recordings in an efficient manner that is reliable and consistent. (Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - January 26, 2021 Category: Biomedical Engineering Source Type: research

Automatic selection and feature extraction of motor-evoked potentials by transcranial magnetic stimulation in stroke patients
AbstractTranscranial magnetic stimulation (TMS) allows the assessment of stroke patients ’ cortical excitability and corticospinal tract integrity, which provide information regarding motor function recovery. However, the extraction of features from motor-evoked potentials (MEP) elicited by TMS, such as amplitude and latency, is performed manually, increasing variability due to observ er-dependent subjectivity. Therefore, an automatic methodology could improve MEP analysis, especially in stroke, which increases the difficulty of manual MEP measurements due to brain lesions. A methodology based on time-frequency featu...
Source: Medical and Biological Engineering and Computing - January 26, 2021 Category: Biomedical Engineering Source Type: research

Pareto optimization for electrodes placement: compromises between electrophysiological and practical aspects
This study employed a secondary data set and simulations for the electrophysiological and practical aspects, respectively. Typically, there is no ideal solution that maximizes satisfaction degrees of multiple electrophysiological and practical aspects simultaneously; a compromise is the most appropriate approach. Instead of combining both aspects —which are independent of each other—into a single-objective optimization, we used multi-objective optimization to obtain a Pareto set, which contains predominant solutions. These solutions may facilitate the decision-makers to decide the preferred electrode locations ...
Source: Medical and Biological Engineering and Computing - January 26, 2021 Category: Biomedical Engineering Source Type: research

Multichannel search strategy for improving the detection of auditory steady-state response
AbstractAuditory steady-state response (ASSR) is useful for hearing threshold estimation. The ASSR is usually detected with objective response detectors (ORD). The performance of these detectors depends on the signal-to-noise ratio (SNR) as well as the signal length. Since it is undesirable to increase the signal length, then, this work provides a multivariate technique for improving the SNR and consequently the detection power. We propose the insertion of a short calibration step before the detection protocol, in order to perform a search among the available electroencephalogram (EEG) derivations and select the derivation...
Source: Medical and Biological Engineering and Computing - January 25, 2021 Category: Biomedical Engineering Source Type: research

Effects of body postures on the shear modulus of thoracolumbar fascia: a shear wave elastography study
This study is aimed to use shear wave elastography (SWE) to study the relationship between shear modulus and different body postures of the thoracolumbar fascia (TLF) and acquire physiologically meaningful information from the stiffness-posture graph to better quantify passive flexion responses. Seven passive postures were defined to evaluate the shear modulus of right side TLF at the third and fourth lumbar vertebra levels (L3 and L4) in twenty healthy male subjects. The TLF stiffness was significantly different among different postures (p 
Source: Medical and Biological Engineering and Computing - January 25, 2021 Category: Biomedical Engineering Source Type: research

Feasibility study to improve deep learning in OCT diagnosis of rare retinal diseases with few-shot classification
AbstractDeep learning (DL) has been successfully applied to the diagnosis of ophthalmic diseases. However, rare diseases are commonly neglected due to insufficient data. Here, we demonstrate that few-shot learning (FSL) using a generative adversarial network (GAN) can improve the applicability of DL in the optical coherence tomography (OCT) diagnosis of rare diseases. Four major classes with a large number of datasets and five rare disease classes with a few-shot dataset are included in this study. Before training the classifier, we constructed GAN models to generate pathological OCT images of each rare disease from normal...
Source: Medical and Biological Engineering and Computing - January 25, 2021 Category: Biomedical Engineering Source Type: research

Quantitative analysis of regional specific pelvic symmetry
AbstractUnderstanding bilateral pelvic symmetry can be useful for analyzing complex pelvis anatomy and simplifying difficult procedures for pelvic fractures. This paper aims to quantify the degree of regional pelvic symmetry using computer-based methods. CT scans of 30 intact pelvises were digitized into 3D models and regions were defined: the ilium, acetabulum, pubis, and ischium. The right hemipelvis was aligned with the left, and deviations between the two models were quantified using method 1 (global registration) and method 2 (local registration). Symmetry was evaluated using the root mean square (RMS) of the deviatio...
Source: Medical and Biological Engineering and Computing - January 16, 2021 Category: Biomedical Engineering Source Type: research

Comparison of two-dimensional synthesized mammograms versus original digital mammograms: a quantitative assessment
This study objectively evaluates the similarity between standard full-field digital mammograms and two-dimensional synthesized digital mammograms (2DSM) in a cohort of women undergoing mammography. Under an institutional review board –approved data collection protocol, we retrospectively analyzed 407 women with digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) examinations performed from September 1, 2014, through February 29, 2016. Both FFDM and 2DSM images were used for the analysis, and 3216 avail able craniocaudal (CC) and mediolateral oblique (MLO) view mammograms altogether were inclu...
Source: Medical and Biological Engineering and Computing - January 14, 2021 Category: Biomedical Engineering Source Type: research

An enhanced deep image model for glaucoma diagnosis using feature-based detection in retinal fundus
AbstractThis paper proposes a deep image analysis –based model for glaucoma diagnosis that uses several features to detect the formation of glaucoma in retinal fundus. These features are combined with most extracted parameters like inferior, superior, nasal, and temporal region area, and cup-to-disc ratio that overall forms a deep image analysis. This proposed model is exercised to investigate the various aspects related to the prediction of glaucoma in retinal fundus images that help the ophthalmologist in making better decisions for the human eye. The proposed model is presented with the combination of four machine...
Source: Medical and Biological Engineering and Computing - January 13, 2021 Category: Biomedical Engineering Source Type: research

The novel three-dimensional pulse images analyzed by dynamic L-cube polynomial model
AbstractA dynamic L-cube polynomial is proposed to analyze dynamic three-dimensional pulse images (d3DPIs), as an extension of the previous static L-cube polynomial. In this paper, a weighted least squares (WLS) method is proposed to fit the amplitudeC(t) of d3DPI at four physiological key points in addition to the best fit of L-cube polynomials to the measured normal and cold-pressor-test (CPT)-induced taut 3DPIs. Compared with other two fitting functions,C(t) of a dynamic L-cube polynomial can be well matched by the proposed WLS method with the least relative error at four physiological key points in one beat with statis...
Source: Medical and Biological Engineering and Computing - January 12, 2021 Category: Biomedical Engineering Source Type: research

Autonomic and enteric function profiling can predict disordered gastric emptying in diabetic gastropathy
AbstractGastric emptying tests (GET) are the gold standard for diagnosing gastroparesis, but many patients do not have delayed emptying. We aimed to examine the combination of autonomic nervous system testing (ANS) and the enteric measure (ENS) of electrogastrography (EGG) to predict disordered GET. Seventy-six patients (47 F, 29 M mean age 40 years) with diabetes mellitus underwent evaluation for end-organ failure including gastroparesis. ANS testing assessed autonomic function by finger capillary pulse to positional changes (PAR), vasoconstriction to cold (VC), and EKG R-R interval change (RRI) with deep breathing; the E...
Source: Medical and Biological Engineering and Computing - January 12, 2021 Category: Biomedical Engineering Source Type: research

Theoretical evaluation of enhanced gold nanoparticle delivery to PC3 tumors due to increased hydraulic conductivity or recovered lymphatic function after mild whole body hyperthermia
The objective of this study is to investigate the effect of hyperthermia-induced improvement of hydraulic conductivity and lymphatic function on both tumoral IFP reduction and nanoparticle delivery to PC3 tumors. We developed a theoretical model for nanoparticle transport in a tumor incorporating Starling ’s law, Darcy’s law, transient convection, and diffusion of chemical species in porous media, and nanoparticle accumulation in tumors. Results have shown that both mechanisms were effective to decrease the IFP at the tumor center from 1600 Pa in the control without heating to 800 Pa in tumors wi th whole body ...
Source: Medical and Biological Engineering and Computing - January 11, 2021 Category: Biomedical Engineering Source Type: research

Human locomotion with reinforcement learning using bioinspired reward reshaping strategies
AbstractRecent learning strategies such as reinforcement learning (RL) have favored the transition from applied artificial intelligence to general artificial intelligence. One of the current challenges of RL in healthcare relates to the development of a controller to teach a musculoskeletal model to perform dynamic movements. Several solutions have been proposed. However, there is still a lack of investigations exploring the muscle control problem from a biomechanical point of view. Moreover, no studies using biological knowledge to develop plausible motor control models for pathophysiological conditions make use of reward...
Source: Medical and Biological Engineering and Computing - January 8, 2021 Category: Biomedical Engineering Source Type: research

Classifying sitting, standing, and walking using plantar force data
AbstractProlonged static weight-bearing at work may increase the risk of developing plantar fasciitis (PF). However, to establish a causal relationship between weight-bearing and PF, a low-cost objective measure of workplace behaviors is needed. This proof-of-concept study assesses the classification accuracy and sensitivity of low-resolution plantar pressure measurements in distinguishing workplace postures. Plantar pressure was measured using an in-shoe measurement system in eight healthy participants while sitting, standing, and walking. Data was resampled to simulate on/off characteristics of 24 plantar force sensitive...
Source: Medical and Biological Engineering and Computing - January 8, 2021 Category: Biomedical Engineering Source Type: research

Biomechanical design prognosis of two extramedullary fixation devices for subtrochanteric femur fracture: a finite element study
AbstractThe design rationale of extramedullary fixation for femur fracture has remained a matter of debate in the orthopaedic community. The present work provides a comparative preclinical assessment between two standard fracture fixation techniques: dynamic hip screw (DHS) and proximal femoral locking plate (PFLP), by employing finite element (FE)-based in silico models. The study attempts to evaluate and compare the two implants on following biomechanical behaviours: (1) stress variation on the femur and implant, (2) axial displacement of the fixated femur constructs, (3) postoperative stress shielding and longer term ex...
Source: Medical and Biological Engineering and Computing - January 8, 2021 Category: Biomedical Engineering Source Type: research

Computer-aided diagnosis based on hand thermal, RGB images, and grip force using artificial intelligence as screening tool for rheumatoid arthritis in women
AbstractRheumatoid arthritis (RA) is an autoimmune disorder that typically affects people between 23 and 60  years old causing chronic synovial inflammation, symmetrical polyarthritis, destruction of large and small joints, and chronic disability. Clinical diagnosis of RA is stablished by current ACR-EULAR criteria, and it is crucial for starting conventional therapy in order to minimize damage progressi on. The 2010 ACR-EULAR criteria include the presence of swollen joints, elevated levels of rheumatoid factor or anti-citrullinated protein antibodies (ACPA), elevated acute phase reactant, and duration of symptoms. In...
Source: Medical and Biological Engineering and Computing - January 8, 2021 Category: Biomedical Engineering Source Type: research

Smoothed particle hydrodynamics simulation of biphasic soft tissue and its medical applications
AbstractModeling the coupled fluid and elastic mechanics of blood perfused soft tissues is important for medical applications. In particular, the current study aims to capture the effect of tissue swelling and the transport of blood through damaged tissue under bleeding or hemorrhaging conditions. The soft tissue is considered a dynamic poro-hyperelastic material with blood-filled voids. A biphasic formulation —effectively, a generalization of Darcy’s law—is utilized, treating the phases as occupying fractions of the same volume. A Stokes-like friction force and a pressure that penalizes deviations from v...
Source: Medical and Biological Engineering and Computing - January 8, 2021 Category: Biomedical Engineering Source Type: research

On the use of histograms of oriented gradients for tremor detection from sinusoidal and spiral handwritten drawings of people with Parkinson ’s disease
This study aims to contribute to the objective evaluation of tremor in PD by int roducing and assessing histograms of oriented gradients (HOG) to the analysis of handwriting sinusoidal and spiral patterns. These patterns were digitized and collected from handwritten drawings of people with PD (n = 20) and control healthy individuals (n = 20). The HOG descriptor was employed to represent relevant information from the data classified by three distinct machine-learning methods (random forest, k-nearest neighbor, support vector machine) and a  deep learning method (convolutional neural network) to identify tremor in parti...
Source: Medical and Biological Engineering and Computing - January 7, 2021 Category: Biomedical Engineering Source Type: research

Accelerometry as an objective measure of upper-extremity activity
AbstractMost studies evaluating the effectiveness of treatments targeting shoulder pathologies use subjective outcome measures such as self-administered questionnaires. To date, there are no validated tools that objectively measure shoulder-specific functional activity. The purpose of this study was to validate wearable accelerometers as an objective proxy for shoulder activity. Ten healthy volunteers wore accelerometers placed at both wrists, the dominant upper arm and the chest while performing standardised shoulder and non-shoulder activities. Recorded tridimensional acceleration was computed into activity counts for ep...
Source: Medical and Biological Engineering and Computing - January 7, 2021 Category: Biomedical Engineering Source Type: research

Lung cancer histology classification from CT images based on radiomics and deep learning models
In this study, we aim to investigate the potential of NSCLC histology classification into AC and SCC by applying different feature extraction and classification techniques on pre-treatment CT images. The employed image dataset (102 patients) was taken from the publicly available cancer imaging archive collection (TCIA). We investigated four different families of techniques: (a) radiomics with two classifiers (kNN and SVM), (b) four state-of-the-art convolutional neural networks (CNNs) with transfer learning and fine tuning (Alexnet, ResNet101, Inceptionv3 and InceptionResnetv2), (c) a CNN combined with a long short-term me...
Source: Medical and Biological Engineering and Computing - January 7, 2021 Category: Biomedical Engineering Source Type: research

Developing the computer-based auditory training program for adults with hearing impairment
AbstractAlthough it is known that auditory training is essential for hearing-impaired individuals, patients do not willingly participate in auditory training sessions, because individual training is a time-consuming and costly process. Computer-based auditory training programs are under development for reducing the cost and time. The aim of this study is to develop a computer-based auditory training program and to evaluate the usability of the program by applying it to adults with normal hearing indifferent age groups and professions. The developed auditory training program consists of nine modules: identification, discrim...
Source: Medical and Biological Engineering and Computing - January 5, 2021 Category: Biomedical Engineering Source Type: research

Over-fitting suppression training strategies for deep learning-based atrial fibrillation detection
In this study, we explored two potential training strategies to address the over-fitting problem in AF detection. The first one is to use the Fast Fourier transform (FFT) and Hanning-window-based filter to suppress the influence from individual difference. Another is to train the model on the wearable ECG data to improve the robustness of model. Wearable ECG data from 29 patients with arrhythmia were collected for at least 24 h. To verify the effectiveness of the training strategies, a Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN)-based model was proposed and tested. We tested the model on the independ...
Source: Medical and Biological Engineering and Computing - January 2, 2021 Category: Biomedical Engineering Source Type: research

Discriminative dictionary learning algorithm with pairwise local constraints for histopathological image classification
AbstractHistopathological image contains rich pathological information that is valued for the aided diagnosis of many diseases such as cancer. An important issue in histopathological image classification is how to learn a high-quality discriminative dictionary due to diverse tissue pattern, a variety of texture, and different morphologies structure. In this paper, we propose a discriminative dictionary learning algorithm with pairwise local constraints (PLCDDL) for histopathological image classification. Inspired by the one-to-one mapping between dictionary atom and profile, we learn a pair of discriminative graph Laplacia...
Source: Medical and Biological Engineering and Computing - January 2, 2021 Category: Biomedical Engineering Source Type: research

Modeling the mechanics of fibrous-porous scaffolds for skeletal muscle regeneration
AbstractThe scaffolds for skeletal muscle regeneration are designed to mimic the structure, stiffness, and strains applied to the muscle under physiologic conditions. The external strains are also used to stimulate myogenesis of the (stem) cells seeded on the scaffold. The time- and location-dependent mechanics inside the scaffold determine the microenvironment for the seeded cells. Here, fibrous-porous cylindrical scaffolds under the action of external cyclic strains are considered. The scaffold mechanics are described as two-phase (poroelastic) where the solid phase is associated with the fibers and the fluid phase is as...
Source: Medical and Biological Engineering and Computing - January 1, 2021 Category: Biomedical Engineering Source Type: research

Quantitative analysis of blood cells from microscopic images using convolutional neural network
AbstractBlood cell count provides relevant clinical information about different kinds of disorders. Any deviation in the number of blood cells implies the presence of infection, inflammation, edema, bleeding, and other blood-related issues. Current microscopic methods used for blood cell counting are very tedious and are highly prone to different sources of errors. Besides, these techniques do not provide full information related to blood cells like shape and size, which play important roles in the clinical investigation of serious blood-related diseases. In this paper, deep learning-based automatic classification and quan...
Source: Medical and Biological Engineering and Computing - January 1, 2021 Category: Biomedical Engineering Source Type: research

Hyper-acute EEG alterations predict functional and morphological outcomes in thrombolysis-treated ischemic stroke: a wireless EEG study
AbstractOwing to the large inter-subject variability, early post-stroke prognosis is challenging, and objective biomarkers that can provide further prognostic information are still needed. The relation between quantitative EEG parameters in pre-thrombolysis hyper-acute phase and outcomes has still to be investigated. Hence, possible correlations between early EEG biomarkers, measured on bedside wireless EEG, and short-term/long-term functional and morphological outcomes were investigated in thrombolysis-treated strokes. EEG with a wireless device was performed in 20 patients with hyper-acute (
Source: Medical and Biological Engineering and Computing - December 4, 2020 Category: Biomedical Engineering Source Type: research

Computational models for contact current dosimetry at frequencies below 1  MHz
AbstractElectric contact currents (CC) can cause muscle contractions, burns, or ventricular fibrillation which may result in life-threatening situations. In vivo studies with CC are rare due to potentially hazardous effects for participants. Cadaver studies are limited to the range of tissue ’s electrical properties and the utilized probes’ size, relative position, and sensitivity. Thus, the general safety standards for protection against CC depend on a limited scientific basis. The aim of this study was therefore to develop an extendable and adaptable validated numerical body model for computational CC dosimet...
Source: Medical and Biological Engineering and Computing - December 2, 2020 Category: Biomedical Engineering Source Type: research

Deep Convolutional Encoder-Decoder algorithm for MRI brain reconstruction
AbstractCompressed Sensing Magnetic Resonance Imaging (CS-MRI) could be considered a challenged task since it could be designed as an efficient technique for fast MRI acquisition which could be highly beneficial for several clinical routines. In fact, it could grant better scan quality by reducing motion artifacts amount as well as the contrast washout effect. It offers also the possibility to reduce the exploration cost and the patient ’s anxiety. Recently, Deep Learning Neuronal Network (DL) has been suggested in order to reconstruct MRI scans with conserving the structural details and improving parallel imaging-ba...
Source: Medical and Biological Engineering and Computing - November 24, 2020 Category: Biomedical Engineering Source Type: research

Numerical investigation of patient-specific thoracic aortic aneurysms and comparison with normal subject via computational fluid dynamics (CFD)
In this study, two scans of thoracic aortic aneurysm (TAA) subject with different AADs (42.94  mm and 48.01 mm) and a scan of a normal subject (19.81 mm) were analyzed to assess the effects of hemodynamics on the progression of TAA with the same flow rate. Real-patient aortic geometries were scanned by computed tomography angiography (CTA), and steady and pulsatile flow conditions were us ed to simulate real patient aortic geometries. Aortic arches were obtained from routine clinical scans. Computational fluid dynamics (CFD) simulations were performed with in vivo boundary conditions, and 3D Navier-Stokes eq...
Source: Medical and Biological Engineering and Computing - November 22, 2020 Category: Biomedical Engineering Source Type: research

Two-dimensional iterative projection method for subsample speckle tracking of ultrasound images
AbstractSpeckle tracking provides robust motion estimation necessary to create accurate post-processed images. These methods are known to be less accurate in the lateral dimension compared with the axial dimension due to the limitations on the lateral resolution of ultrasound scanning. This paper proposes a two-dimensional iterative projection (TDIP) algorithm using the Riesz transform to generate the analytic signals. The TDIP is an improvement to an already accurate speckle tracking algorithm called the phase coupled (PC) method. The PC method projects the intersection of gradients on the correlation map to the zero phas...
Source: Medical and Biological Engineering and Computing - November 21, 2020 Category: Biomedical Engineering Source Type: research

Self-evoluting framework of deep convolutional neural network for multilocus protein subcellular localization
AbstractIn the present paper, deep convolutional neural network (DCNN) is applied to multilocus protein subcellular localization as it is more suitable for multi-class classification. There are two main problems with this application. First, the appropriate features for correlation between multiple sites are hard to find. Second, the classifier structure is difficult to determine as it is greatly affected by the distribution of classified data. To solve these problems, a self-evoluting framework using DCNNs for multilocus protein subcellular localization is proposed. It has three characteristics that the previous algorithm...
Source: Medical and Biological Engineering and Computing - November 21, 2020 Category: Biomedical Engineering Source Type: research