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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 requires ...
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 – to ...
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 11, 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 adapt the motion to the s...
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