Spectral F Test for detecting TMS/EEG responses
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Alexandre Cardozo de Almeida, Mariana Aguiar Massote, Roberto Macoto Ichinose, Antonio Mauricio Ferreira Leite Miranda de SáAbstractElectroencephalogram (EEG) is a well-known painless and noninvasive method, measuring the real time brain electrical activity. Transcranial Magnetic Stimulation (TMS) is another noninvasive, painless and safe method, to modulate nerve cells activity. TMS has been increasingly used as a tool in neurosciences. However, its basic mechanisms are not yet fully understood. Simultaneous TMS/EEG re...
Source: Biomedical Signal Processing and Control - February 16, 2020 Category: Biomedical Science Source Type: research

Lymph-vascular space invasion prediction in cervical cancer: Exploring radiomics and deep learning multilevel features of tumor and peritumor tissue on multiparametric MRI
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Wenqing Hua, Taohui Xiao, Xiran Jiang, Zaiyi Liu, Meiyun Wang, Hairong Zheng, Shanshan WangAbstractPreoperative determination of the presence of LVSI plays an important role in guiding surgical planning. In this paper, multiparametric magnetic resonance imaging (MRI)-based radiomics and deep feature learning strategy was applied to both tumor and peritumor tissues for preoperative prediction of LVSI in early-stage cervical cancer. 111 training cohort patients (44 LVSI-positive and 67 LVSI-negative) and 56 validation cohort pat...
Source: Biomedical Signal Processing and Control - February 14, 2020 Category: Biomedical Science Source Type: research

A review of machine learning techniques in photoplethysmography for the non-invasive cuff-less measurement of blood pressure
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): C. El-Hajj, P.A. KyriacouAbstractHypertension or high blood pressure is a leading cause of death throughout the world and a critical factor for increasing the risk of serious diseases, including cardiovascular diseases such as stroke and heart failure. Blood pressure is a primary vital sign that must be monitored regularly for the early detection, prevention and treatment of cardiovascular diseases. Traditional blood pressure measurement techniques are either invasive or cuff-based, which are impractical, intermittent, and unc...
Source: Biomedical Signal Processing and Control - February 13, 2020 Category: Biomedical Science Source Type: research

Robust brain causality network construction based on Bayesian multivariate autoregression
ConclusionsThe analyses conducted in the current work demonstrate the robustness of Bayesian-based Granger analysis to outlier conditions or physiological signals with small sample sizes. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - February 13, 2020 Category: Biomedical Science Source Type: research

A new method for muscular visual fatigue detection using electrooculogram
ConclusionWavelet packet barycenter frequency and average blink time can be used for muscular visual fatigue detection, a certain degree of muscular visual fatigue occurred after induction and the trained support vector machine can achieve a good classification detection. We conclude that wavelet packet barycenter frequency and average blink time can be used for accurate muscular visual fatigue detection.SignificanceThis study is of great significance in muscular visual fatigue prevention and treatment. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - February 13, 2020 Category: Biomedical Science Source Type: research

Automated emotion recognition based on higher order statistics and deep learning algorithm
This study is carried out with the web-available DEAP dataset that yields 82.01% average classification accuracy with 10-fold cross-validation technique corresponding to four-labeled emotions classes. The achieved results have confirmed that the proposed algorithm has the potential for accurate and rapid recognition of human emotions. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - February 13, 2020 Category: Biomedical Science Source Type: research

A high-precision arrhythmia classification method based on dual fully connected neural network
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Haoren Wang, Haotian Shi, Ke Lin, Chengjin Qin, Liqun Zhao, Yixiang Huang, Chengliang LiuAbstractAs an important arrhythmia detection method, the electrocardiogram (ECG) can directly reflect abnormalities in cardiac physiological activity. In view of the difficulty in the diagnosis of arrhythmia in different people, automatic arrhythmia detection methods have been studied in previous works. In this paper, we present a dual fully-connected neural network model for accurate classification of heartbeats. Our method is following t...
Source: Biomedical Signal Processing and Control - February 13, 2020 Category: Biomedical Science Source Type: research

Calibrationless joint compressed sensing reconstruction for rapid parallel MRI
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Bhabesh Deka, Sumit DattaAbstract3D magnetic resonance imaging (3D MRI) or multi-slice MRI involves significant data acquisition time. Traditionally, scanning rate of conventional MRI is restricted due to inherent physiological and instrumental limitations. In multi-slice parallel MRI (multi-slice pMRI) adjacent slices are highly correlated, so one can interpolate missing k-space data of any slice from its adjacent slices. Moreover, images corresponding to different coils are also highly correlated as they represent the same f...
Source: Biomedical Signal Processing and Control - February 13, 2020 Category: Biomedical Science Source Type: research

EMG-driven hand model based on the classification of individual finger movements
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Maria V. Arteaga, Jenny C. Castiblanco, Ivan F. Mondragon, Julian D. Colorado, Catalina Alvarado-RojasAbstractThe recovery of hand motion is one of the most challenging aspects in stroke rehabilitation. This paper presents an initial approach to robot-assisted hand-motion therapies. Our goal was twofold: firstly, we have applied machine learning methods to identify and characterize finger motion patterns from healthy individuals. To this purpose, Electromyographic (EMG) signals have been acquired from flexor and extensor muscl...
Source: Biomedical Signal Processing and Control - January 30, 2020 Category: Biomedical Science Source Type: research

Temporal super-resolution of 2D/3D echocardiography using cubic B-spline interpolation
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Mohammad Jalali, Hamid Behnam, Fateme Davoodi, Maryam ShojaeifardAbstractEchocardiography is an important imaging modality in daily clinical practices. Lack of image quality and limited number of frames per second are the major problems of this modality. Frame rate limitation becomes worse in 3D echocardiography, because it has to scan a volume instead of a plane and acquisition of a volume consumes more time compared to its two-dimensional counterpart. Higher frame rates can help improve medical diagnostics like tracking move...
Source: Biomedical Signal Processing and Control - January 30, 2020 Category: Biomedical Science Source Type: research

A deep stacked random vector functional link network autoencoder for diagnosis of brain abnormalities and breast cancer
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Deepak Ranjan Nayak, Ratnakar Dash, Banshidhar Majhi, Ram Bilas Pachori, Yudong ZhangAbstractAutomated diagnosis of two-class brain abnormalities through magnetic resonance imaging (MRI) has progressed significantly in past few years. In contrast, there exists a limited amount of methods proposed to date for multiclass brain abnormalities detection. Such detection has shown its importance in biomedical research and has remained a challenging task. Almost all existing methods are designed using conventional machine learning app...
Source: Biomedical Signal Processing and Control - January 29, 2020 Category: Biomedical Science Source Type: research

3D right ventricular endocardium segmentation in cardiac magnetic resonance images by using a new inter-modality statistical shape modelling method
ConclusionA novel SSM-based approach to segment the RV endocardium in CMR scans by using a model trained on 3DE-derived RV endocardial surfaces, was proposed. This inter-modality technique proved to be rapid when segmenting the RV endocardium with an accurate anatomical delineation, in particular in apical and basal regions. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - January 26, 2020 Category: Biomedical Science Source Type: research

A dual approach for positive T–S fuzzy controller design and its application to cancer treatment under immunotherapy and chemotherapy
This study proposes an effective positive control design strategy for cancer treatment by resorting to the combination of immunotherapy and chemotherapy. The treatment objective is to transfer the initial number of tumor cells and immune–competent cells from the malignant region into the region of benign growth where the immune system can inhibit tumor growth. In order to achieve this goal, a new modeling strategy is used that is based on Takagi–Sugeno. A Takagi-Sugeno fuzzy model is derived based on the Stepanova nonlinear model that enables a systematic design of the controller. Then, a positive Parallel Dist...
Source: Biomedical Signal Processing and Control - January 26, 2020 Category: Biomedical Science Source Type: research

Frame rate up-conversion in cardiac ultrasound
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Hani Nozari Mirarkolaei, Sten Roar Snare, Anne H Schistad Solberg, Erik Normann SteenAbstractThe temporal resolution of echocardiographic sequences affects the interpretation of cardiac motion as well as the viewing experience. Temporal resolution, however, is limited by the propagation velocity of sound in tissue. Altering the acquisition system can improve temporal resolution but normally reduces image quality. Alternatively, motion compensated frame interpolation enhances perceived temporal resolution without reducing spati...
Source: Biomedical Signal Processing and Control - January 26, 2020 Category: Biomedical Science Source Type: research

Optimal adaptive intuitionistic fuzzy logic control of anti-cancer drug delivery systems
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Mohamed Esmail Karar, Ahmed Hamdy El-Garawany, Mohamed El-BrawanyAbstractThis paper introduces a new closed loop fuzzy logic controller for regulating intravenous anti-cancer drug delivery, based on intuitionistic fuzzy sets and invasive weed optimization (IWO) algorithm. The developed intuitionistic fuzzy logic controller (IFLC) contributes the following advancements: First, the parameters of IFLC are adaptive and optimally tuned to achieve desired drug concentrations at the tumor site, killing almost all cancer cells at the ...
Source: Biomedical Signal Processing and Control - January 24, 2020 Category: Biomedical Science Source Type: research

Near lossless image compression using parallel fractal texture identification
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): R. Suresh Kumar, P. ManimegalaiAbstractThe most important parameters of image processing are resolution of the image and processing speed. The datasets of multimedia are compressed, which are rich in quality and quantity is challenging. This paper develops a novel approach to estimate the affine parameters of fractal texture identification, in order to minimize the complexity of computation. In this proposed NLICPFTI, a pattern dictionary is maintained to hold repeated fractal patterns. Different types of data chunks such as F...
Source: Biomedical Signal Processing and Control - January 24, 2020 Category: Biomedical Science Source Type: research

Corrigendum to “Color-based template selection for detection of gastric abnormalities in video endoscopy” [Biomed. Signal Process. Control 56 (2020) February 101668]
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): Hussam Ali, Muhammad Sharif, Mussarat Yasmin, Mubashir Husain Rehmani (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - January 23, 2020 Category: Biomedical Science Source Type: research

Automated focal EEG signal detection based on third order cumulant function
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Rahul Sharma, Pradip Sircar, Ram Bilas PachoriAbstractEpilepsy is a chronic neurological disorder which occurs due to recurrent seizures. The epilepsy surgery is the only cure of epileptic seizures as it cannot be controlled with medication. Hence, it becomes the primary task to localize the epileptogenic zone for successful epilepsy surgery. The epileptic surgical area can be recognized by the focal intracranial electroencephalogram (EEG) signals. In this paper, a nonlinear third-order cumulant has been proposed for the class...
Source: Biomedical Signal Processing and Control - January 23, 2020 Category: Biomedical Science Source Type: research

Blood pressure prediction from speech recordings
In conclusion, it can be observed that the proposed feature vector (FVx) shows a relationship between BP and the human voices, and in this direction, it can be used as an FVx in a system that will be developed in order to follow the tension of individuals. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - January 23, 2020 Category: Biomedical Science Source Type: research

Walsh code based numerical mapping method for the identification of protein coding regions in eukaryotes
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Raman Kumar M, Naveen Kumar VaegaeAbstractThe protein coding regions play a significant role for gene applications in genomic signal processing. Unlike prokaryotes, the coding regions in eukaryotes are arranged in a random manner. Owing to unequal lengths and low volume density of coding regions, the identification of coding regions makes cumbersome. In this work, a new numerical mapping method based on Walsh codes is proposed to detect the coding regions in eukaryotes. The Walsh code for each nucleotide is obtained using the ...
Source: Biomedical Signal Processing and Control - January 21, 2020 Category: Biomedical Science Source Type: research

Fractional mesh-free linear diffusion method for image enhancement and segmentation for automatic tumor classification
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Saroj Kumar Chandra, Manish Kumar BajpaiAbstractComputer aided diagnostic (CAD) models have shown outstanding performance in identifying many kind of diseases. Tumor identification is one of the most useful application of CAD model. Benign and malignant are two categories of tumor cells. Both categories share some textural features due to which tumor classification becomes complex and difficult task. In the present manuscript, a novel CAD model is being presented for classifying tumor cells automatically. The proposed model ha...
Source: Biomedical Signal Processing and Control - January 16, 2020 Category: Biomedical Science Source Type: research

Generalization of a wavelet-based algorithm to adaptively detect activation intervals in weak and noisy myoelectric signals
This study introduces an adaptive implementation of a Continuous Wavelet Transform (CWT) decomposition technique used to estimate the timing of muscular activation in weak and noisy myoelectric signals. The algorithm updates automatically the threshold based on the statistical properties of the EMG data, through an iterative estimation of the Signal-to-Noise Ratio (SNR). Moreover, it includes a stopping criterion for the number of CWT decomposition levels, and this allows a relevant decrease of the computational burden. This algorithm was applied to both synthetic and semi-synthetic signals, and compared against the origin...
Source: Biomedical Signal Processing and Control - January 12, 2020 Category: Biomedical Science Source Type: research

A novel automated system of discriminating Microaneurysms in fundus images
This article explores a novel and reliable method for automatic early detection of Microaneurysms (MA) in fundus images. Microaneurysms characterized by small red spots on the retina, the red lesions are symptoms of early stage of DR. Development of an automated screening system would assist an ophthalmologist in diagnosing DR at an early stage. Hence, in this paper, a novel feature extraction technique using a Local Neighborhood Differential Coherence Pattern (LNDCP) is proposed. In this method, texture characteristics needed for classification by Feed Forward Neural Network (FFNN) is captured efficiently. The performance...
Source: Biomedical Signal Processing and Control - January 12, 2020 Category: Biomedical Science Source Type: research

Temporal-spatial-frequency depth extraction of brain-computer interface based on mental tasks
In this study, two types of series and parallel structures are proposed by combining convolutional neural network (CNN) and long short term memory (LSTM). The frequency and spatial features of EEG are extracted by CNN, and the temporal features are extracted by LSTM. The EEG signals of mental tasks with speech imagery are extracted and classified by these architectures. In addition, the proposed methods are further validated by the 2008 BCI competition IV-2a EEG data set, and its mental task is motor imagery. The series structure with compact CNN obtains the best results for two data sets. Compared with the algorithms of o...
Source: Biomedical Signal Processing and Control - January 11, 2020 Category: Biomedical Science Source Type: research

Blind extraction of fetal and maternal components from the abdominal electrocardiogram: An ICA implementation for low-dimensional recordings
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Aída Jiménez-González, Norma Castañeda-VillaAbstractThis work studied Space-Time ICA (ST-ICA) on the separation of fetal and maternal ECGs from low-dimensional abdominal recordings. ST-ICA was implemented by combining the Method of Delays with FastICA and an automatic classifier and applied to the “Abdominal and Direct Fetal Electrocardiogram Database” in Physionet. Next, 24 indexes qualified the FECGs retrieved by using 4, 3, 2 channels and combinations of them (e.g., channels 1–3...
Source: Biomedical Signal Processing and Control - January 11, 2020 Category: Biomedical Science Source Type: research

Evolving control of human-exoskeleton system using Gaussian process with local model
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Jiantao Yang, Cheng PengAbstractSignificant application breakthrough has not been achieved in human-exoskeleton systems due to the lack of transparent human-exoskeleton interaction. An evolving learning control strategy based on Gaussian process with local model (GPLM) is proposed to realize transparent control of a human-exoskeleton system. As a data driven technique, Gaussian process (GP) serves as a mathematical foundation to learn the dynamics of human lower limbs. Local model is incorporated into the GP framework to impro...
Source: Biomedical Signal Processing and Control - January 11, 2020 Category: Biomedical Science Source Type: research

Study on the usage feasibility of continuous-wave radar for emotion recognition
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Carolina Gouveia, Ana Tomé, Filipa Barros, Sandra C. Soares, José Vieira, Pedro PinhoAbstractNon-contact vital signs monitoring has a wide range of applications, such as in safe drive and in health care. In mental health care, the use of non-invasive signs holds a great potential, as it would likely enhance the patient's adherence to the use of objective measures to assess their emotional experiences, hence allowing for more individualized and efficient diagnoses and treatment. In order to evaluate the possibilit...
Source: Biomedical Signal Processing and Control - January 11, 2020 Category: Biomedical Science Source Type: research

EEG-based emotion recognition using simple recurrent units network and ensemble learning
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Chen Wei, Lan-lan Chen, Zhen-zhen Song, Xiao-guang Lou, Dong-dong LiAbstractThe purpose of this research is to develop an EEG-based emotion recognition system for identification of three emotions: positive, neutral and negative. Up to now, various modeling approaches for automatic emotion recognition have been reported. However, the time dependency property during emotion process has not been fully considered. In order to grasp the temporal information of EEG, we adopt deep Simple Recurrent Units (SRU) network which is not onl...
Source: Biomedical Signal Processing and Control - January 9, 2020 Category: Biomedical Science Source Type: research

Validation of freely-available pitch detection algorithms across various noise levels in assessing speech captured by smartphone in Parkinson’s disease
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Vojtech Illner, Pavel Sovka, Jan RuszAbstractMeasuring the fundamental frequency of the vocal folds F0 is recognized as an important parameter in the assessment of speech impairments in Parkinson`s disease (PD). Although a number of F0 trackers currently exist, their performance in smartphone-based evaluation and robustness against background noise have never been tested. Monologues from 30 newly-diagnosed, untreated PD patients and 30 matched healthy control participants were collected. Additive non-stationary urban and house...
Source: Biomedical Signal Processing and Control - January 9, 2020 Category: Biomedical Science Source Type: research

Epileptic seizure detection in EEG signals using normalized IMFs in CEEMDAN domain and quadratic discriminant classifier
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Md. Faizul Bari, Shaikh Anowarul FattahAbstractEpilepsy is the fourth most common neurological disorder that manifests itself through unprovoked seizures, detection of which is the very first step of proper diagnosis and treatment of this severe disease. In this paper, an automated seizure detection method has been proposed based on the statistical and spectral features of max normalized intrinsic mode functions or IMFs that were extracted using complete ensemble empirical mode decomposition with adaptive noise method. First, ...
Source: Biomedical Signal Processing and Control - January 9, 2020 Category: Biomedical Science Source Type: research

Accuracy improvement of quantification information using super-resolution with convolutional neural network for microscopy images
ConclusionsWe confirmed that the proposed method is more effective than the conventional method. It is expected that this approach will be helpful in evaluating the drug responses of patients by improving the accuracy of image-based cell phenotypic profiling. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - January 9, 2020 Category: Biomedical Science Source Type: research

Evaluation of convolutional neural networks using a large multi-subject P300 dataset
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Lukáš VařekaAbstractDeep neural networks (DNN) have been studied in various machine learning areas. For example, event-related potential (ERP) signal classification is a highly complex task potentially suitable for DNN as signal-to-noise ratio is low, and underlying spatial and temporal patterns display a large intra- and intersubject variability. Convolutional neural networks (CNN) have been compared with baseline traditional models, i.e. linear discriminant analysis (LDA) and support vector machines (SVM) for ...
Source: Biomedical Signal Processing and Control - January 9, 2020 Category: Biomedical Science Source Type: research

Breast tumors recognition based on edge feature extraction using support vector machine
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Yangyang Liu, Li Ren, Xuehong Cao, Ying TongAbstractNowadays, it is important for the detection of ultrasound images of breast tumors. In this paper, a new ultrasonic image feature extraction algorithm combining edge-based features and morphologic feature information is proposed, which has good effect on benign and malignant identification of breast tumors. This paper mainly studies three features (Sum of maximum curvature, Sum of maximum curvature and peak, Sum of maximum curvature and standard deviation) according to the sha...
Source: Biomedical Signal Processing and Control - January 9, 2020 Category: Biomedical Science Source Type: research

A physiological control system for ECG-synchronized pulsatile pediatric ventricular assist devices
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): Thiago D. Cordeiro, Daniel L. Sousa, Idágene A. Cestari, Antonio M.N. LimaAbstractVentricular assist devices (VADs) are mechanical pumps used to provide support to the circulatory system of patients with ventricular dysfunction that are waiting for heart transplantation. The majority of pulsatile VADs are used in the fill-to-empty mode or the asynchronous mode at a fixed rate. However, when this support lasts for weeks or months, physiological control systems can improve the treatment by changing VAD operation in respon...
Source: Biomedical Signal Processing and Control - January 8, 2020 Category: Biomedical Science Source Type: research

Adaptation of Common Spatial Patterns based on mental fatigue for motor-imagery BCI
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Upasana Talukdar, Shyamanta M. Hazarika, John Q. GanAbstractCommon Spatial Pattern (CSP) is the most popular method in motor imagery (MI) based Brain–Computer Interfaces (BCI) for extracting features from electroencephalogram (EEG) signals. Due to the non-stationary nature of EEG signals, the CSP computed on the training data may not be optimal for the evaluation data. One of the major causes of such non-stationarity is the change in user's cognitive state due to fatigue, frustration, low arousal level, etc. This paper p...
Source: Biomedical Signal Processing and Control - January 8, 2020 Category: Biomedical Science Source Type: research

Improved image processing techniques for optic disc segmentation in retinal fundus images
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): R. Geetha Ramani, J. Jeslin ShanthamalarAbstractGlaucoma is one of the leading causes of blindness in the world and is projected to affect over 79.6 million people globally. Recently, automated computer aided systems are used in disease detection and proven to be highly useful in assisting experts in the early diagnosis. Hence, automated optic disc segmentation through the intelligent system is very much helpful for the early detection of Glaucoma. This paper presents an improved image processing algorithm for retinal fundus i...
Source: Biomedical Signal Processing and Control - January 8, 2020 Category: Biomedical Science Source Type: research

A Kalman filtering based adaptive threshold algorithm for QRS complex detection
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Zhong Zhang, Qi Yu, Qihui Zhang, Ning Ning, Jing LiAbstractThis work presents an adaptive threshold algorithm in electrocardiogram signal feature extraction by introducing Kalman filtering theory. Low computational cost, low storage requirement and fast response feature are achieved by applying two sets of adaptive threshold systems in different conditions. Also, double-threshold peak detection design dramatically decreases the false detection conditions resulting from noise. As a proof of concept, the proposed algorithm is ve...
Source: Biomedical Signal Processing and Control - January 8, 2020 Category: Biomedical Science Source Type: research

Robust LPV control design for blood glucose regulation considering daily life factors
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): Alireza Mirzaee, Maryam Dehghani, Mohsen MohammadiAbstractIn blood glucose control, the daily life factors such as food intake, exercise, stress, fatigue and circadian rhythm that alter the level of blood glucose should be meticulously considered, which requires the design of a robust control approach for dealing with these uncertainties. In this paper, a robust LPV-based controller is designed in order to achieve a predefined level of blood glucose considering the effects of daily life factors. To be sure that the proposed co...
Source: Biomedical Signal Processing and Control - January 1, 2020 Category: Biomedical Science Source Type: research

Classification of intracavitary electrograms in atrial fibrillation using information and complexity measures
Conclusions and significanceClassification performance obtained using information and complexity measures shown better results than previous works over this dataset, encouraging the application of these features to characterize atrial electrograms. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - December 31, 2019 Category: Biomedical Science Source Type: research

Novel algorithm for conventional myocontrol of upper limbs prosthetics
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): S.I. Benchabane, N. Saadia, A. Ramdane-CherifAbstractOne of the most common issue in surface electromyography (sEMG) based myocontrol is to set a recurrent feature which allows to ensure a reliable multi degree of freedom (MDoF) prosthetic drive, mainly due to non-stationary behavior of signal. According to studies, electrode placement and shifts, variation in muscle contraction effort and muscle fatigue are the most common disturbance sources in sEMG recording, which traduces into a cumbersome donning and doffing recalibratio...
Source: Biomedical Signal Processing and Control - December 31, 2019 Category: Biomedical Science Source Type: research

Epileptic seizure prediction by the detection of seizure waveform from the pre-ictal phase of EEG signal
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): Khakon Das, Debashis Daschakladar, Partha Pratim Roy, Atri Chatterjee, Shankar Prasad SahaAbstractEpilepsy is a significant burden on our society till now, due to appropriate healthcare treatment, cost of therapy, the spontaneous and unpredictable occurrence of seizures. There is a need for a fast and integrated neural investigation process that could help epileptologist to determine and diagnose the patients as soon as possible. Electroencephalogram (EEG) has been commonly used to diagnose patients by investigating the brain'...
Source: Biomedical Signal Processing and Control - December 27, 2019 Category: Biomedical Science Source Type: research

A new 360° rotating type stimuli for improved SSVEP based brain computer interface
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): Anupam Bisht, Shivam Srivastava, Geethanjali PurushothamanAbstractThe authors investigated for first time clockwise and counter clockwise 360° rotating stimuli at two different speeds of rotation/phase for brain computer interface (BCI). The 360° rotating stimuli of frequencies 3 Hz, 7.5 Hz and 10 Hz are considered and compared to the performance with non-rotating flickering stimuli using signal-to-noise ratio at four channels Oz, Pz, O1 and O2. In addition, the authors have also attempted to study the effect of ...
Source: Biomedical Signal Processing and Control - December 27, 2019 Category: Biomedical Science Source Type: research

Heart rate estimation from wrist-type photoplethysmography signals during physical exercise
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): K.R. Arunkumar, M. BhaskerAbstractWearable devices, such as smart watch use photoplethysmography (PPG) signals for estimating heart rate (HR). The motion artifacts (MA) contained in these PPG signals lead to an erroneous HR estimation. In this manuscript, a new de-noising algorithm has been proposed that uses the combination of cascaded recursive least square (RLS), normalized least mean square (NLMS) and least mean square (LMS) adaptive filters. The MA reduced PPG signals obtained from these cascaded adaptive filters are comb...
Source: Biomedical Signal Processing and Control - December 27, 2019 Category: Biomedical Science Source Type: research

Differentiation of early mild cognitive impairment in brainstem MR images using multifractal detrended moving average singularity spectral features
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): P. Rohini, S. Sundar, S. RamakrishnanAbstractBrainstem texture analysis can provide valuable information in the diagnosis of Early Mild Cognitive Impairment (EMCI) condition. In this work, 3D brainstem structure is segmented and analysed for texture alterations using multifractal features to differentiate EMCI from other Alzheimer’s disease stages. The images obtained from public domain database are preprocessed for spatial registration, skull stripping and contrast enhancement. White matter volume is segmented from the ...
Source: Biomedical Signal Processing and Control - December 27, 2019 Category: Biomedical Science Source Type: research

A review of feature extraction and performance evaluation in epileptic seizure detection using EEG
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): Poomipat Boonyakitanont, Apiwat Lek-uthai, Krisnachai Chomtho, Jitkomut SongsiriAbstractSince the manual detection of electrographic seizures in continuous electroencephalogram (EEG) monitoring is very time-consuming and requires a trained expert, attempts to develop automatic seizure detection are diverse and ongoing. Machine learning approaches are intensely being applied to this problem due to their ability to classify seizure conditions from a large amount of data, and provide pre-screened results for neurologists. Several...
Source: Biomedical Signal Processing and Control - December 26, 2019 Category: Biomedical Science Source Type: research

Feature selection algorithm based on PDF/PMF area difference
ConclusionBy testing and comparing the different feature selection algorithms, the proposed feature selection algorithm is shown to be accurate and effective for various tasks, including medical imaging and visualization.Graphical abstract (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - December 26, 2019 Category: Biomedical Science Source Type: research

A New Tumor-Immunotherapy Regimen based on Impulsive Control Strategy
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): Azadeh Aghaeeyan, Mohammad Javad Yazdanpanah, Jamshid HadjatiAbstractAutologous tumor infiltrating lymphocyte (TIL) therapy refers to a kind of immunotherapy in which the tumor-resident lymphocytes are harvested, cultured, and then transferred into the patient. In spite of some well-known TILs expansion recommendations, there is a lack of well-established TILs injection protocol. This paper addresses the challenge using a feedback-based control strategy. Utilizing Lyapunov technique, a novel dose calculation method is proposed...
Source: Biomedical Signal Processing and Control - December 26, 2019 Category: Biomedical Science Source Type: research

Development of a brain computer interface based on steady-state visual evoked potential with multiple intermittent photo stimulation
ConclusionsA stable and active BCI was designed with a correct detection rate within 74–76%, ITR value between 19 and 26 [bit/min] and response delay for the detection between two consecutive stimulation frequencies within 2–2.5 s. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - December 26, 2019 Category: Biomedical Science Source Type: research

Multilevel mental stress detection using ultra-short pulse rate variability series
In conclusion, we found that the proposed multilevel stress detection system in conjunction with new parameters of the Poincare plot has the potential to detect five different mental stress states using ultra-short term recordings of a low-cost PPG sensor. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - December 26, 2019 Category: Biomedical Science Source Type: research

An efficient two-pass classifier system for patient opinion mining to analyze drugs satisfaction
Publication date: March 2020Source: Biomedical Signal Processing and Control, Volume 57Author(s): P. Padmavathy, S. Pakkir MohideenAbstractOpinion mining is a well-known problem in natural language processing that increasing attention in recent years. With the rapid growth in e-commerce, reviews for popular products on the web have grown rapidly. In opinion mining, the greater part of the scientists has dealt with general domains, for example, electronic items, movies, and restaurants audit not much on health and medical domains. Therefore, in this paper, we focus on predicting the drug satisfaction level among the other p...
Source: Biomedical Signal Processing and Control - December 26, 2019 Category: Biomedical Science Source Type: research