Objective Edge Similarity Metric for denoising applications in MR images
Publication date: Available online 20 February 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Ashok Shanmugam, S. Rukmani DeviAbstractEdge Similarity Metrics (ESMs) are necessary to objectively quantify the inadvertent blur at the edge pixels which occurs during denoising. They are helpful for evaluating edge-preserving capability of nonlinear filters. Most of the ESMs in literature, consider similarity of either strength of the edges or their direction individually. They lag in terms of concordance with subjective edge similarity ratings. An Objective Edge Similarity Metric (OESM) which considers all thre...
Source: Biocybernetics and Biomedical Engineering - February 21, 2020 Category: Biomedical Engineering Source Type: research

A review of fabrication polymer scaffolds for biomedical applications using additive manufacturing techniques
This article focuses on the utilization of polymer materials (natural and synthetic) taking into account hydrogels in scaffolds fabrication. Assessment of polymer scaffolds mechanical properties enables personalized patient care, as well as prevents damage after implantation in human body. By controlling process parameters it is possible to obtain optimised mechanical properties of manufactured parts. (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - February 21, 2020 Category: Biomedical Engineering Source Type: research

Biodegradable bone implants in orthopedic applications: a review
Publication date: Available online 20 February 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Girish Chandra, Ajay PandeyAbstractA biologically - validated biodegradable material must comfortably stay in the physiological environment it is placed in, before finally disappearing over the intended period of time with adequate rates of degradation. The primary objective and utility of such a material is to eliminate the requirement of secondary surgery in applications involving bone implants. In recent decades, biodegradable alloys have exhibited enhanced biocompatibility, and improved mechanical and biodegra...
Source: Biocybernetics and Biomedical Engineering - February 21, 2020 Category: Biomedical Engineering Source Type: research

Sleep EEG analysis utilizing inter-channel covariance matrices
ConclusionThe performances of RG-TS and E1 features reveal that the changes in inter-dependencies of pre-frontal and occipital lobe along with the central lobe can be used to distinguish the different sleep stages. (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - February 21, 2020 Category: Biomedical Engineering Source Type: research

Modelling and control of a failing heart managed by a left ventricular assist device
Publication date: Available online 20 February 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Jeongeun Son, Dongping Du, Yuncheng DuAbstractLeft ventricular assist device (LVAD) recently has been used in advanced heart failure (HF), which supports a failing heart to meet blood circulation demand of the body. However, the pumping power of LVADs is typically set as a constant and cannot be freely adjusted to incorporate blood need from resting or mild exercise such as walking stairs. To promote the adoption of LVADs in clinical use as a long-term treatment option, a feedback controller is needed to regulate ...
Source: Biocybernetics and Biomedical Engineering - February 21, 2020 Category: Biomedical Engineering Source Type: research

Automatic Parkinson disease detection at early stages as a pre-diagnosis tool by using classifiers and a small set of vocal features
Publication date: Available online 5 February 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Gabriel Solana-Lavalle, Juan-Carlos Galán-Hernández, Roberto Rosas-RomeroAbstractRecent research on Parkinson disease (PD) detection has shown that vocal disorders are linked to symptoms in 90% of the PD patients at early stages. Thus, there is an interest in applying vocal features to the computer-assisted diagnosis and remote monitoring of patients with PD at early stages. The contribution of this research is an increase of accuracy and a reduction of the number of selected vocal features in PD dete...
Source: Biocybernetics and Biomedical Engineering - February 7, 2020 Category: Biomedical Engineering Source Type: research

Automatic sleep stage classification using time–frequency images of CWT and transfer learning using convolution neural network
Publication date: Available online 31 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Pankaj Jadhav, Gaurav Rajguru, Debabrata Datta, Siddhartha MukhopadhyayAbstractFor automatic sleep stage classification, the existing methods mostly rely on hand-crafted features selected from polysomnographic records. In this paper, the goal is to develop a deep learning-based method by using single channel electroencephalogram (EEG) that automatically exploits the time–frequency spectrum of EEG signal, removing the need for manual feature extraction. The time–frequency RGB color images for EEG signal ...
Source: Biocybernetics and Biomedical Engineering - February 1, 2020 Category: Biomedical Engineering Source Type: research

The selection of wart treatment method based on Synthetic Minority Over-sampling Technique and Axiomatic Fuzzy Set theory
Publication date: Available online 27 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Wenjuan Jia, Hao Xia, Lijuan Jia, Yingjie Deng, Xiaodong LiuAbstractWart disease is a kind of skin illness that is caused by Human Papillomavirus (HPV). Many medical studies are being carried out with the aid of machine learning and data mining techniques to find the most appropriate and effective treatment for a specific wart patient. However, the imbalanced distribution of medical data may lead to misclassification in this field. The purpose of this paper is to propose a algorithm to predict the response of the p...
Source: Biocybernetics and Biomedical Engineering - January 28, 2020 Category: Biomedical Engineering Source Type: research

A robust method for early diagnosis of autism spectrum disorder from EEG signals based on feature selection and DBSCAN method
This article aims to present a robust method for early diagnosis of ASD from EEG signal. The study population consists of 34 children with ASD between 3–12 years and 11 healthy children in the same ranges of age. The proposed approach uses linear and nonlinear features such as Power Spectrum, Wavelet Transform, Fast Fourier Transform (FFT), Fractal Dimension, Correlation Dimension, Lyapunov Exponent, Entropy, Detrended Fluctuation Analysis and Synchronization Likelihood for describing the EEG signal. In addition Density Based Clustering is utilized for artifact removal and robustness. Besides, features selection is a...
Source: Biocybernetics and Biomedical Engineering - January 28, 2020 Category: Biomedical Engineering Source Type: research

Granger causal analysis of electrohysterographic and tocographic recordings for classification of term vs. preterm births
Publication date: Available online 25 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Saqib Saleem, Ahmed Saeed, Shabnam Usman, Javed Ferzund, Jahangir Arshad, Jawad Mirza, Tareq ManzoorAbstractAccording to World Health Organization, 5—18% births around the world are premature, and this rate is on its rise. Recent trend has been to develop computational tools which could support obstetricians in their daily practice. This work is aimed at extracting novel diagnostic features for term vs. preterm births classification based on the dynamics of contraction and non-contractions (dummy) intervals. ...
Source: Biocybernetics and Biomedical Engineering - January 26, 2020 Category: Biomedical Engineering Source Type: research

Pose and Optical Flow Fusion (POFF) for accurate tremor detection and quantification
Publication date: Available online 25 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Mehmet Akif Alper, John Goudreau, Morris DanielAbstractLimb tremor measurements are one factor used to characterize and quantify the severity of neurodegenerative disorders. These tremor measurements can also provide dosage-response feedback to guide medication treatments. Here, we propose a system to automatically measure limb tremors in home or clinic settings. The key feature of proposed method is that it is contactless; not requiring a user to wear or hold a device or marker. Our sensor is a Kinect 2, which mea...
Source: Biocybernetics and Biomedical Engineering - January 26, 2020 Category: Biomedical Engineering Source Type: research

Brain tumor classification using a hybrid deep autoencoder with Bayesian fuzzy clustering-based segmentation approach
Publication date: Available online 21 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): P.M. Siva Raja, Antony Viswasa raniAbstractIn medical image processing, brain tumor detection and segmentation is a challenging and time-consuming task. Magnetic Resonance Image (MRI) scan analysis is a powerful tool in the recent technology that makes effective detection of the abnormal tissues from the brain. In the brain image, the size of a tumor can be varied for different patients along with the minute details of the tumor. It is a difficult task to diagnose and classify the tumor from numerous images for the...
Source: Biocybernetics and Biomedical Engineering - January 23, 2020 Category: Biomedical Engineering Source Type: research

Publisher note
Publication date: Available online 20 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - January 22, 2020 Category: Biomedical Engineering Source Type: research

Motion analysis of lumbar vertebrae for different rod materials and flexible rod device – An experimental and finite element study
Publication date: Available online 20 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Masud Rana, Jayanta Kumar Biswas, Sandipan Roy, Palash Biswas, Santanu Kumar Karmakar, Amit RoychowdhuryAbstractDifferent stabilization devices have been used for treating lumbar spine disorders, including fusion, dynamic stabilization devices, flexible rods etc., which possess a different level of limitations. A simple experimental procedure is developed using a prototype lumbar spine specimen (L1-S), to evaluate the biomechanical performance of the lumbar spine. The range of motions (ROM) are tested for pedicle s...
Source: Biocybernetics and Biomedical Engineering - January 22, 2020 Category: Biomedical Engineering Source Type: research

Deep-segmentation of plantar pressure images incorporating fully convolutional neural networks
Publication date: Available online 20 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Dan Wang, Zairan Li, Nilanjan Dey, Amira S. Ashour, Luminita Moraru, R. Simon Sherratt, Fuqian ShiAbstractComfort shoe-last design relies on the key points of last curvature. Traditional plantar pressure image segmentation methods are limited to their local and global minimization issues. In this work, an improved fully convolutional networks (FCN) employing SegNet (SegNet+FCN 8 s) is proposed. The algorithm design and operation are performed using the visual geometry group (VGG). The method has high efficie...
Source: Biocybernetics and Biomedical Engineering - January 22, 2020 Category: Biomedical Engineering Source Type: research

Classification of plantar foot alterations by fuzzy cognitive maps against multi-layer perceptron neural network
Publication date: Available online 16 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Julian Andres Ramirez-Bautista, Jorge Adalberto Huerta-Ruelas, László T. Kóczy, Miklós F. Hatwágner, Silvia L. Chaparro-Cárdenas, Antonio Hernández-ZavalaAbstractLoad distribution analysis on foot surface allows knowing human mechanical behavior and aids the doctor in the detection of gait disorders like, the risk of foot ulcerations, leg discrepancy, and footprint alterations. Plantar pressure data combined with techniques that use integral reasoning produce easy un...
Source: Biocybernetics and Biomedical Engineering - January 17, 2020 Category: Biomedical Engineering Source Type: research

Fundamental heart sounds analysis using improved complete ensemble EMD with adaptive noise
Publication date: Available online 16 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Miguel Altuve, Luis Suárez, Jeyson ArdilaAbstractPhonocardiogram (PCG) recordings contain valuable information about the functioning and state of the heart that is useful in the diagnosis of cardiovascular diseases. The first heart sound (S1) and the second heart sound (S2), produced by the closing of the atrioventricular valves and the closing of the semilunar valves, respectively, are the fundamental sounds of the heart. The similarity in morphology and duration of these heart sounds and their superpositio...
Source: Biocybernetics and Biomedical Engineering - January 17, 2020 Category: Biomedical Engineering Source Type: research

Coping with limitations of fetal monitoring instrumentation to improve heart rhythm variability assessment
Publication date: Available online 9 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Tomasz Kupka, Adam Matonia, Michal Jezewski, Krzysztof Horoba, Janusz Wrobel, Janusz JezewskiAbstractThe most commonly used method of fetal monitoring is based on analysis of the fetal heart activity. Computer-aided fetal monitoring enables extraction of information hidden for visual interpretation – the instantaneous fetal heart rate (FHR) variability. The most natural method of obtaining FHR signal is fetal electrocardiography (FECG), where the FHR has a natural form of unevenly spaced time series of events ...
Source: Biocybernetics and Biomedical Engineering - January 10, 2020 Category: Biomedical Engineering Source Type: research

Genetically modified C3A cells with restored urea cycle for improved bioartificial liver
Publication date: Available online 9 January 2020Source: Biocybernetics and Biomedical EngineeringAuthor(s): Krzysztof Dariusz Pluta, Anna Samluk, Agnieszka Wencel, Karolina Ewa Zakrzewska, Monika Gora, Beata Burzynska, Malgorzata Ciezkowska, Joanna Motyl, Dorota Genowefa PijanowskaAbstractThe bioartificial liver, a hybrid device aimed at improving the survival of patients with fulminant liver failure, requires a cell source to replicate human liver function. However, liver support systems that utilize porcine or human hepatoma-derived cells felt short of expectations in clinical trials. Here we present engineered C3A cell...
Source: Biocybernetics and Biomedical Engineering - January 10, 2020 Category: Biomedical Engineering Source Type: research

The repeatability of the instrumented timed Up & Go test: The performance of older adults and parkinson’s disease patients under different conditions
Publication date: Available online 28 December 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Slavka Viteckova, Radim Krupicka, Petr Dusek, Vaclav Cejka, Patrik Kutilek, Jan Novak, Zoltan Szabo, Evžen RůžičkaAbstractThe Timed Up & Go (TUG) test is a simple test for gait and balance that requires no special equipment and can be part of a routine clinical examination. Combined with the development of motion capture technologies, the possibilities of assessing individual TUG sub-components (i.e. sit-to-stand, gait, turn, turn-to-sit) are increasing. The clinical evaluation of an instrumented TUG requi...
Source: Biocybernetics and Biomedical Engineering - December 29, 2019 Category: Biomedical Engineering Source Type: research

Classification of pilots’ mental states using a multimodal deep learning network
In this study, we aimed to investigate the feasibility of a robust detection system of the pilot's mental states (i.e., distraction, workload, fatigue, and normal) based on multimodal biosignals (i.e., electroencephalogram, electrocardiogram, respiration, and electrodermal activity) and a multimodal deep learning (MDL) network. To do this, first, we constructed an experimental environment using a flight simulator in order to induce the different mental states and to collect the biosignals. Second, we designed the MDL architecture – which consists of a convolutional neural network and long short-term memory models &nd...
Source: Biocybernetics and Biomedical Engineering - December 28, 2019 Category: Biomedical Engineering Source Type: research

Evaluation of electrohysterogram measured from different gestational weeks for recognizing preterm delivery: a preliminary study using random Forest
Publication date: Available online 25 December 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Jin Peng, Dongmei Hao, Lin Yang, Mengqing Du, Xiaoxiao Song, Hongqing Jiang, Yunhan Zhang, Dingchang ZhengAbstractDeveloping a computational method for recognizing preterm delivery is important for timely diagnosis and treatment of preterm delivery. The main aim of this study was to evaluate electrohysterogram (EHG) signals recorded at different gestational weeks for recognizing the preterm delivery using random forest (RF). EHG signals from 300 pregnant women were divided into two groups depending on when the sig...
Source: Biocybernetics and Biomedical Engineering - December 25, 2019 Category: Biomedical Engineering Source Type: research

Simultaneous feature weighting and parameter determination of Neural Networks using Ant Lion Optimization for the classification of breast cancer
Publication date: Available online 25 December 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Singh Dalwinder, Singh Birmohan, Kaur ManpreetAbstractIn this paper, feature weighting is used to develop an effective computer-aided diagnosis system for breast cancer. Feature weighting is employed because it boosts the classification performance more as compared to feature subset selection. Specifically, a wrapper method utilizing the Ant Lion Optimization algorithm is presented that searches for best feature weights and parametric values of Multilayer Neural Network simultaneously. The selection of hidden neur...
Source: Biocybernetics and Biomedical Engineering - December 25, 2019 Category: Biomedical Engineering Source Type: research

Complex-valued distribution entropy and its application for seizure detection
Publication date: Available online 13 December 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Tao Zhang, Wanzhong Chen, Mingyang LiAbstractEmbedding entropies are powerful indicators in quantifying the complexity of signal, but most of them are only applicable for real-valued signal and the phase information is ignored if the analyzed signal is complex-valued. To assess the complexity of complex-valued signal, a new entropy called complex-valued distribution entropy (CVDistEn) was first proposed in this study. Two rules, namely equal width criterion and equal area criterion, were employed to demarcate the ...
Source: Biocybernetics and Biomedical Engineering - December 14, 2019 Category: Biomedical Engineering Source Type: research

Detection of eye closing/opening from EOG and its application in robotic arm control
Publication date: Available online 10 December 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Kamal Sharma, Neeraj Jain, Prabir K. PalAbstractDetection of eye closing/opening from alpha-blocking in the EEG of occipital region has been used to build human-machine interfaces. This paper presents an alternative method for detection of eye closing/opening from EOG signals in an online setting. The accuracies for correct detection of eye closing and opening operations with the proposed techniques were found to be 95.6% and 91.9% respectively for 8 healthy subjects. These techniques were then combined with the d...
Source: Biocybernetics and Biomedical Engineering - December 12, 2019 Category: Biomedical Engineering Source Type: research

Automated detection of optic disc contours in fundus images using decision tree classifier
Publication date: Available online 30 November 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Sumaiya Pathan, Preetham Kumar, Radhika Pai, Sulatha V. BhandaryAbstractAutomated segmentation of optic disc in fundus images plays a vital role in computer aided diagnosis (CAD) of eye pathologies. In this paper, a novel method is proposed which detects and excludes the blood vessel for accurate optic disc segmentation. This is achieved in two steps. First, an effective blood vessel detection and exclusion algorithm is developed using directional filter. In the second step, a decision tree classifier is used to o...
Source: Biocybernetics and Biomedical Engineering - November 30, 2019 Category: Biomedical Engineering Source Type: research

CNN-based superresolution reconstruction of 3D MR images using thick-slice scans
Publication date: Available online 29 November 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Jakub Jurek, Marek Kocinski, Andrzej Materka, Marcin Elgalal, Agata MajosAbstractDue to inherent physical and hardware limitations, 3D MR images are often acquired in the form of orthogonal thick slices, resulting in highly anisotropic voxels. This causes the partial volume effect, which introduces blurring of image details, appearance of staircase artifacts and significantly decreases the diagnostic value of images. To restore high resolution isotropic volumes, we propose to use a convolutional neural network (CN...
Source: Biocybernetics and Biomedical Engineering - November 30, 2019 Category: Biomedical Engineering Source Type: research

A Low-Cost EMG-Controlled Anthropomorphic Robotic Hand for Power and Precision Grasp
Publication date: Available online 27 November 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Leobardo E. Sánchez-Velasco, Manuel Arias-Montiel, Enrique Guzmán-Ramírez, Esther Lugo-GonzálezAbstractIn this paper the use of a commercial EMG armband for the motion control of a prototype hand prosthesis is proposed. The mechanical design is based on an open source six degree-of-freedom hand. Some modifications from the original design are proposed, mainly in the actuation and power transmission devices to reduce the prototype's costs and to provide a major mobility to the thumb to a...
Source: Biocybernetics and Biomedical Engineering - November 28, 2019 Category: Biomedical Engineering Source Type: research

Detection of lung cancer on chest CT images using minimum redundancy maximum relevance feature selection method with convolutional neural networks
In this study, the detection of lung cancers is realized using LeNet, AlexNet and VGG-16 deep learning models. The experiments were carried out on an open dataset composed of Computed Tomography (CT) images. In the experiment, convolutional neural networks (CNNs) were used for feature extraction and classification purposes. In order to increase the success rate of the classification, the image augmentation techniques, such as cutting, zooming, horizontal turning and filling, were applied to the dataset during the training of the models. Because of the outstanding success of AlexNet model, the features obtained from the las...
Source: Biocybernetics and Biomedical Engineering - November 24, 2019 Category: Biomedical Engineering Source Type: research

Fusing fine-tuned deep features for recognizing different tympanic membranes
In this study, we focus on recognizing normal, AOM, CSOM, and earwax tympanic membrane (TM) conditions using fused fine-tuned deep features provided by pre-trained deep convolutional neural networks (DCNNs). These features are applied as the input to several networks, such as an artificial neural network (ANN), k-nearest neighbor (k NN), decision tree (DT) and support vector machine (SVM). Moreover, we release a new publicly available TM data set consisting of totally 956 otoscope images. As a result, the DCNNs yielded promising results. Especially, the most efficient results were provided by VGG-16 with an accuracy of 93....
Source: Biocybernetics and Biomedical Engineering - November 24, 2019 Category: Biomedical Engineering Source Type: research

Muscle coordination analysis by time-varying muscle synergy extraction during cycling across various mechanical conditions
Publication date: Available online 23 November 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Javad Esmaeili, Ali MalekiAbstractCentral nervous system (CNS) uses the combination of a small number of motor primitives, named muscle synergies, for simplification of motor control in human movement. The aim of this study was to investigate the muscle coordination in both leg muscles during pedaling by time-varying muscle synergy extraction. Twenty healthy subjects performed three 6-min cycling tasks over a range of rotational speed (40, 50, and 60 rpm) and resistant torque (3, 5, and 7 N/M). Surface electromyog...
Source: Biocybernetics and Biomedical Engineering - November 24, 2019 Category: Biomedical Engineering Source Type: research

Stacking-based multi-objective evolutionary ensemble framework for prediction of diabetes mellitus
Publication date: Available online 23 November 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Namrata Singh, Pradeep SinghAbstractDiabetes mellitus (DM) is a combination of metabolic disorders characterized by elevated blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of associated complications like retinopathy, nephropathy and neuropathy and other vascular abnormalities. In this background, machine learning (ML) approaches can play an essential role in the early detection, diagnosis and therapeutic monitoring of the disease. Recently, several research works have been ...
Source: Biocybernetics and Biomedical Engineering - November 24, 2019 Category: Biomedical Engineering Source Type: research

Scattering transform-based features for the automatic seizure detection
Publication date: Available online 23 November 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Yun Jiang, Wanzhong Chen, Yang YouAbstractDeveloping the automatic detection system is of great clinical significance for assisting neurologists to detect epilepsy using electroencephalogram (EEG) signals. In this research, we explore the ability of a newly-developed algorithm named scattering transform in seizure detection. The preprocessed signal is initially decomposed into scattering coefficients with various orders and scales employing scattering transform. Fuzzy entropy (FuzzyEn) and Log energy entropy (LogE...
Source: Biocybernetics and Biomedical Engineering - November 24, 2019 Category: Biomedical Engineering Source Type: research

Fuzzy logic approach for infectious disease diagnosis: A methodical evaluation, literature and classification
Publication date: Available online 26 September 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Goli Arji, Hossein Ahmadi, Mehrbakhsh Nilashi, Tarik A. Rashid, Omed Hassan Ahmed, Nahla Aljojo, Azida ZainolAbstractThis paper presents a systematic review of the literature and the classification of fuzzy logic application in an infectious disease. Although the emergence of infectious diseases and their subsequent spread have a significant impact on global health and economics, a comprehensive literature evaluation of this topic has yet to be carried out. Thus, the current study encompasses the first systematic...
Source: Biocybernetics and Biomedical Engineering - September 27, 2019 Category: Biomedical Engineering Source Type: research

HWDCNN: Multi-class recognition in breast histopathology with Haar wavelet decomposed image based convolution neural network
Publication date: Available online 20 September 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Tasleem Kausar, MingJiang Wang, Muhammad Idrees, Yun LuAbstractAmong the predominant cancers, breast cancer is one of the main causes of cancer deaths impacting women worldwide. However, breast cancer classification is challenging due to numerous morphological and textural variations that appeared in intra-class images. Also, the direct processing of high resolution histological images is uneconomical in terms of GPU memory. In the present study, we have proposed a new approach for breast histopathological image ...
Source: Biocybernetics and Biomedical Engineering - September 21, 2019 Category: Biomedical Engineering Source Type: research

Improved robust weighted averaging for event-related potentials in EEG
Publication date: Available online 18 September 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Krzysztof Kotowski, Katarzyna Stapor, Jacek LeskiAbstractThe aim of this study was to improve the robust weighted averaging based on criterion function minimization and assess its effectiveness for extracting event-related brain potentials (ERP) from electroencephalographic (EEG) recordings. The areas of improvement include significantly lower averaging error (45% lower RMSE and 37% lower maximum difference than for original implementation) and increased robustness to local minima, strong outliers and corrupted e...
Source: Biocybernetics and Biomedical Engineering - September 19, 2019 Category: Biomedical Engineering Source Type: research

Development and testing of a passive ankle exoskeleton
This study proposes the development and initial testing of a passive ankle exoskeleton intended to provide a plantarflexion torque assist during the push off phase of gait. The design incorporates a Pneumatic Artificial Muscle as a non-linear elastic element to store and release energy during walking. The device also integrates a novel clutch mechanism design to engage and disengage the spring element about the ankle joint during walking such that it does not impede the ankle motion during swing phase. Mechanical testing demonstrated the prototypes ability to function adequately over the natural range of an ankle joint and...
Source: Biocybernetics and Biomedical Engineering - September 12, 2019 Category: Biomedical Engineering Source Type: research

Prediction of displacement in the equine third metacarpal bone using a neural network prediction algorithm
In this study, an artificial neural network (ANN) was used for the prediction of displacement in long bones followed by ex-vivo experiments. Three hydrated third metacarpal bones (MC3) from 3 thoroughbred horses were used in the experiments. A set of strain gauges were distributed around the midshaft of the bones. These bones were then loaded in compression in an MTS machine. The recordings of strains, load, rate of loading, and displacement were used as ANN input parameters. The ANN which was trained using 3250 experimental data points from two bones predicted the displacement of the third bone (R2 ≥ 0.98...
Source: Biocybernetics and Biomedical Engineering - September 10, 2019 Category: Biomedical Engineering Source Type: research

Investigating the effects of various suturing parameters on the leakage from the intestinal anastomosis site: Finite element analyses
Publication date: Available online 9 September 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Zahra Kanani, Gholamreza Rouhi, Sanaz Mosafer KhoorjestanAbstractIn this work, effects of various parameters, including regularity of sewing, distance of holes from the edge of the tissue (D), distance between holes (L), suturing pattern, and material and size of the suture on the leakage of human large intestine anastomosis site were investigated, using finite element method (FEM). The effects of various parameters of suturing on leakage were investigated in four different steps: (1) regularity of suturing; (2) v...
Source: Biocybernetics and Biomedical Engineering - September 10, 2019 Category: Biomedical Engineering Source Type: research

A hybrid regularized extreme learning machine for automated detection of pathological brain
Publication date: Available online 5 September 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Deepak Ranjan Nayak, Ratnakar Dash, Banshidhar Majhi, Yudong ZhangAbstractThis paper presents an automated method for detection of pathological brain using magnetic resonance (MR) images. The proposed method suggests to derive features using fast discrete curvelet transform. A combined feature reduction algorithm principal component analysis + linear discriminant analysis (PCA + LDA) is then applied to generate a low-dimensional and discriminant feature vector. Finally, the classification is ca...
Source: Biocybernetics and Biomedical Engineering - September 6, 2019 Category: Biomedical Engineering Source Type: research

Antiradical properties of chemo drug, carboplatin, in cooperation with ZnO nanoparticles under UV irradiation in putative model of cancer cells
Publication date: Available online 4 September 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Suttirak Pairoj, Pattareeya Damrongsak, Badin Damrongsak, Natini Jinawath, Rossukon Kaewkhaw, Tanaporn Leelawattananon, Chinnapat Ruttanasirawit, Kitsakorn LocharoenratAbstractThe main objective of this study was to assess the antiradical properties of zinc oxide (ZnO) nanoparticles upon exposure to ultraviolet radiation with carboplatin, an anti-proliferative drug used in the treatment of retinoblastoma. For the purpose of this study, the decomposition of 2,2(diphenyl-1-picryhydrazyl) radical (DPPH*) was used to ...
Source: Biocybernetics and Biomedical Engineering - September 5, 2019 Category: Biomedical Engineering Source Type: research

Extracting multiple commands from a single SSVEP flicker using eye-accommodation
Publication date: Available online 5 September 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Kamal Sharma, Soumitra KarAbstractThe steady-state visually evoked potential (SSVEP) based brain-computer interfaces (BCIs) generally deploy flickering stimuli with different frequencies in order to generate different commands. This paper presents a setup that can be used to generate multiple commands from a single flickering stimulus using magnitude modulation of SSVEP through eye-accommodation. In this setup, a flickering stimulus was shown on the computer screen and a passive fixation target was placed between ...
Source: Biocybernetics and Biomedical Engineering - September 5, 2019 Category: Biomedical Engineering Source Type: research

Tissue coefficient of bioimpedance spectrometry as an index to discriminate different tissues in vivo
Publication date: Available online 31 August 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Ying Li, Ren Ma, Xin Wang, Jingna Jin, He Wang, Zhipeng Liu, Tao YinAbstractBioimpedance indicating cell and tissue condition of the living things is of great importance in impedance spectrum analysis and other related researches, in which measurement of the skin impedance is a tricky problem due to the peculiarity of the stratum corneum. The aim of the study is to develop a method to elucidate the skin impedance in a large frequency range and to find out a biomarker to estimate it.In this article, we introduce a no...
Source: Biocybernetics and Biomedical Engineering - August 31, 2019 Category: Biomedical Engineering Source Type: research

Social-Group-Optimization based tumor evaluation tool for clinical brain MRI of Flair/diffusion-weighted modality
This article proposes a two-stage image assessment tool to examine brain MR images acquired using the Flair and DW modalities. The combination of the Social-Group-Optimization (SGO) and Shannon’s-Entropy (SE) supported multi-thresholding is implemented to pre-processing the input images. The image post-processing includes several procedures, such as Active Contour (AC), Watershed and region-growing segmentation, to extract the tumor section. Finally, a classifier system is implemented using ANFIS to categorize the tumor under analysis into benign and malignant. Experimental investigation was executed using benchmark ...
Source: Biocybernetics and Biomedical Engineering - August 30, 2019 Category: Biomedical Engineering Source Type: research

Inter-patient ECG classification with convolutional and recurrent neural networks
Publication date: Available online 19 August 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Li Guo, Gavin Sim, Bogdan MatuszewskiAbstractThe recent advances in ECG sensor devices provide opportunities for user self-managed auto-diagnosis and monitoring services over the internet. This imposes the requirements for generic ECG classification methods that are inter-patient and device independent. In this paper, we present our work on using the densely connected convolutional neural network (DenseNet) and gated recurrent unit network (GRU) for addressing the inter-patient ECG classification problem. A deep lea...
Source: Biocybernetics and Biomedical Engineering - August 21, 2019 Category: Biomedical Engineering Source Type: research

P300 based character recognition using sparse autoencoder with ensemble of SVMs
In this study, a brain–computer interface (BCI) system known as P300 speller is used to spell the word or character without any muscle activity. For P300 signal classification, feature extraction is an important step. In this work, deep feature learning techniques based on sparse autoencoder (SAE) and stacked sparse autoencoder (SSAE) are proposed for feature extraction. Deep feature provides the abstract information about the signal. This work proposes fusion of deep features with the temporal features, which provides abstract and temporal information about the EEG signal. These deep feature and temporal feature are...
Source: Biocybernetics and Biomedical Engineering - August 13, 2019 Category: Biomedical Engineering Source Type: research

Technology-based health promotion: Current state and perspectives in emerging gig economy
Publication date: Available online 12 August 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Jafet Morales, Devasena Inupakutika, Sahak Kaghyan, David Akopian, Zenong Yin, Deborah Parra-Medina, Martin EvansAbstractIt has been a decade since smartphone application stores started allowing developers to post their own applications. This paper presents a narrative review on the state-of-the-art and the future of the technology used by researchers in the field of health promotion, which very often uses smartphones. In this area, researchers build high cost, complex systems with the purpose of promoting health an...
Source: Biocybernetics and Biomedical Engineering - August 13, 2019 Category: Biomedical Engineering Source Type: research

Application of decision tree in determining the importance of surface electrohysterography signal characteristics for recognizing uterine contractions
In conclusion, decision tree could be used to classify the uterine activities, and the Power and SamEn of un-normalized EHG segments were the most important characteristics in uterine contraction classification. (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - August 9, 2019 Category: Biomedical Engineering Source Type: research

Machine learning-based novel approach to classify the shoulder motion of upper limb amputees
Publication date: Available online 8 August 2019Source: Biocybernetics and Biomedical EngineeringAuthor(s): Kaur AmanpreetAbstractAn upper limb amputation is a traumatic event that can seriously affect the person’s capacity to perform regular tasks and can lead individuals to lose their confidence and autonomy. Prosthetic devices can be controlled via the acquisition and processing of electromyogram signal produced at the muscles fiber from the surface of the body with an array of an electrode placed on the residual limb. This paper presents the feasibility of classifying the different shoulder movements from around ...
Source: Biocybernetics and Biomedical Engineering - August 9, 2019 Category: Biomedical Engineering Source Type: research

Social-group-optimization based tumor evaluation tool for clinical brain MRI of flair/DW modality
This article proposes a two-stage image assessment tool to examine brain MR images acquired using the Flair and DW modalities. The combination of the Social-Group-Optimization (SGO) and Shannon's-Entropy (SE) supported multi-thresholding is implemented to pre-processing the input images. The image post-processing includes several procedures, such as Active Contour (AC), Watershed and region-growing segmentation, to extract the tumor section. Finally, a classifier system is implemented using ANFIS to categorize the tumor under analysis into benign and malignant. Experimental investigation was executed using benchmark datase...
Source: Biocybernetics and Biomedical Engineering - July 27, 2019 Category: Biomedical Engineering Source Type: research