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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 detection while ...
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 are extr...
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 appli...
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. To a...
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 efficiency f...
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 understanding medical tools for assisting in...
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 superposition in t...
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