A novel heart-mobile interface for detection and classification of heart sounds
We present a low-cost, patient-centered device for the initial screening of the heart sounds that can be potentially used by the users on themselves. They can later share these readings with their healthcare providers. We have created an innovative mobile-health service platform for analyzing and classifying heart sounds. The presented system enables remote patient-monitoring by integrating advanced wireless communications with a customized low-cost stethoscope. This system also permits remote management of a patient’s cardiac status while maximizing patient mobility. The smartphone application facilitates recording,...
Source: Biomedical Signal Processing and Control - June 22, 2018 Category: Biomedical Science Source Type: research

Effective EMG denoising using a hybrid model based on WAT and GARCH
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Ruby K. Joseph, Geevarghese Titus, Sudhakar M S EMG is the recording of electrical activity of the muscles that can be used in diagnosing muscular diseases like myopathy and neuropathy and in generating control signals for operating artificial prosthetic arms and limbs. Various forms of artifacts get introduced into the EMG during the acquisition process that limits its proper analysis and characterization. This paper proposes a novel noise suppression method for EMG signals employing orthogonal Wave Atom Transform (WAT) fo...
Source: Biomedical Signal Processing and Control - June 19, 2018 Category: Biomedical Science Source Type: research

Using a multichannel Wiener filter to remove eye-blink artifacts from EEG data
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Adam Borowicz This paper presents a novel method for removing ocular artifacts from EEG recordings. The proposed approach is based on time-domain linear filtering. Instead of directly estimating the artifact-free signal, we propose to obtain the eye-blink signal first, using a multichannel Wiener filter (MWF) and a small subset of the frontal electrodes, so that extra EOG sensors are unnecessary. Then, the estimate of the eye-blink signal is subtracted from the noisy EEG signal in accordance with principles of regression an...
Source: Biomedical Signal Processing and Control - June 19, 2018 Category: Biomedical Science Source Type: research

Compressed sensing ECG using restricted Boltzmann machines
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Luisa F. Polanía, Rafael I. Plaza Recently, it has been shown that compressed sensing (CS) has the potential to lower energy consumption in wireless electrocardiogram (ECG) systems. By reducing the number of acquired measurements, the communication burden is decreased and energy is saved. In this paper, we aim at further reducing the number of necessary measurements to achieve faithful reconstruction by exploiting the representational power of restricted Boltzmann machines (RBMs) to model the probability distribution...
Source: Biomedical Signal Processing and Control - June 19, 2018 Category: Biomedical Science Source Type: research

Intelligent human emotion recognition based on elephant herding optimization tuned support vector regression
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Aboul Ella Hassanien, Moataz Kilany, Essam H. Houssein, Hameed AlQaheri The ability to recognize emotional states of people surrounding us is an important portion of natural communication as emotions are fundamental factors in human decision handling, interaction, and cognitive procedure. The primary intention of this paper is to present an approach that uses electroencephalography (EEG) signals to recognize human emotions. This work targets emotional recognition in terms of three emotional scales; valence, arousal and domi...
Source: Biomedical Signal Processing and Control - June 19, 2018 Category: Biomedical Science Source Type: research

A deconvolution scheme for the stochastic metabolic/hemodynamic model (sMHM) based on the square root cubature Kalman filter and maximum likelihood estimation
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Mohammed Boureghda, Toufik Bouden Based on clinical data collected using different brain imaging and recording techniques, brain researchers built mathematical models of the activity in the human brain. To test these models they simulate them by performing on those models a virtual brain experiment, and compare the outputs from those with the real brain activity recordings. The models can be a basis for understanding what goes wrong in brain diseases and brain disorders and potentially help to create new drugs for these con...
Source: Biomedical Signal Processing and Control - June 16, 2018 Category: Biomedical Science Source Type: research

Automatic detection of optic disc in color fundus retinal images using circle operator
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): M. Nahid Reza In the field of computer aided eye disease diagnosis, automatic optic disk detection is required. In this paper a method is proposed to detect optic disk automatically in color retinal fundus image without using background mask and blood vessels. Based on the properties of optic disk, an idea of circle operator is presented here. This method has been applied on six public databases and the promising results are obtained. The experimental results indicate that this proposed method of automatic optic disk detect...
Source: Biomedical Signal Processing and Control - June 15, 2018 Category: Biomedical Science Source Type: research

Effect of threshold values on the combination of EMG time domain features: Surface versus intramuscular EMG
In this study, we investigate the effect of threshold selection on the classification for prosthetic use. Surface and intramuscular EMG were recorded concurrently from four forearm muscles on nine able-bodied subjects. Subjects were prompted to elicit comfortable and sustainable contractions corresponding to eight classes of motion. Four repetitions of three seconds were collected for each motion during medium level steady state contractions. The threshold for each feature was computed as a factor (R = 0:0.02:6) times the average root mean square of the baseline. For each threshold value, classification error was quant...
Source: Biomedical Signal Processing and Control - June 15, 2018 Category: Biomedical Science Source Type: research

Beating-heart robotic surgery using bilateral impedance control: Theory and experiments
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Mojtaba Sharifi, Hassan Salarieh, Saeed Behzadipour, Mahdi Tavakoli A bilateral impedance controller is presented to enable robot-assisted surgery of a beating heart. For this purpose, two desired impedance models are designed and realized for the master and slave robots interacting with the operator (surgeon) and the environment (heart tissue), respectively. The impedance models are designed such that (a) the slave robot complies with the oscillatory motion of the beating heart and (b) the surgeon perceives the non-oscilla...
Source: Biomedical Signal Processing and Control - June 15, 2018 Category: Biomedical Science Source Type: research

Novel electromyography signal envelopes based on binary segmentation
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): J.A. Guerrero, M.A. Castillo-Galván, J.E. Macías-Díaz In this work, we introduce two novel methodologies to compute the envelope of superficial electromyography signals. Our methods are based on the detection of activation and deactivation patterns using a change-point approach on the variances of the sample. More concretely, an iterative algorithms is proposed to select the change-points between two segments of the signal based on some local statistics introduced in this work. The signal is split up in...
Source: Biomedical Signal Processing and Control - June 15, 2018 Category: Biomedical Science Source Type: research

A new approach for denoising multichannel electrogastrographic signals
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): D. Komorowski, B. Mika Electrogastrography (EGG) can be considered as a non-invasive method for the measurement of gastric myoelectrical activity. The multichannel signal is non-invasively captured by disposable electrodes placed on the surface of a stomach. The recorded signal can include not only EGG components, but also the interfering signals from other organs, for instance, the disturbances connected with respiratory movements and random noise. In order to correctly calculate the parameters of the EGG examination and i...
Source: Biomedical Signal Processing and Control - June 15, 2018 Category: Biomedical Science Source Type: research

A novel statistical signal processing method to estimate effects of compounds on contractility of cardiomyocytes using impedance assays
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): L. Batista, T. Bastogne, A. Delaunois, J.-P. Valentin, F. Atienzar Label free methods such as cell impedance assays are in vitro tests increasingly used in drug development and producing large and high-content data files. Since the current commercial software is not suited for fully automated analysis, there is a need to develop validated and rapid solutions to extract relevant information for biologists. This need is particularly obvious in the case of impedance signals analysis from cardiomyocytes. The proposed solution i...
Source: Biomedical Signal Processing and Control - June 15, 2018 Category: Biomedical Science Source Type: research

Liver vessel segmentation based on centerline constraint and intensity model
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Ye-zhan Zeng, Yu-qian Zhao, Sheng-hui Liao, Miao Liao, Yan Chen, Xi-yao Liu Liver vessels provide lots of important information for liver-disease diagnosis and liver surgery. This paper presents an effective liver vessel segmentation method from abdominal computer tomography angiography (CTA) images. The proposed method applies two techniques including centerline constraint and intensity model for effective detection of liver vessels, in which the former aims at generating the position and distance restraints for the detect...
Source: Biomedical Signal Processing and Control - June 15, 2018 Category: Biomedical Science Source Type: research

Automated detection and classification of basic shapes of newborn cry melody
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Claudia Manfredi, Andrea Bandini, Donatella Melino, Renaud Viellevoye, Masendu Kalenga, Silvia Orlandi The study of newborn cry is a promising non-intrusive and cheap approach to support the early diagnosis of neurodevelopmental disorders. Specifically, cry melody, the trend of the fundamental frequency (f0) over time, could add relevant information to the acoustical analysis of infant crying. To date, the cry analysis is mainly performed by paediatricians/neurologists through a perceptual examination based on listening to ...
Source: Biomedical Signal Processing and Control - June 7, 2018 Category: Biomedical Science Source Type: research

A Novel Approach to Mortality Prediction of ICU Cardiovascular Patient Based on Fuzzy Logic Method
Conclusion As a result, the implementation of these methods leads to more favorable treatment of patients and the allocation of appropriate equipment to them. Another of these aims is to reduce costs, avoid unnecessary treatments and reduce the risk for patients. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - June 7, 2018 Category: Biomedical Science Source Type: research

Automatic detection of peripapillary atrophy in retinal fundus images using statistical features
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Anindita Septiarini, Agus Harjoko, Reza Pulungan, Retno Ekantini The presence of peripapillary atrophy (PPA) is associated with two kinds of diseases, namely glaucoma and myopia. PPA is one of the characteristics of these diseases that can be observed through retinal fundus images. We propose an automatic detection method of PPA in retinal fundus images using statistical features and Backpropagation Neural Network. In this research, those images are classified into two classes: no-PPA and PPA. The features are extracted fro...
Source: Biomedical Signal Processing and Control - June 7, 2018 Category: Biomedical Science Source Type: research

Neural modulation in action video game players during inhibitory control function: An EEG study using discrete wavelet transform
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Jupitara Hazarika, Piyush Kant, Rajdeep Dasgupta, Shahedul Haque Laskar The ability to attend relevant visual information, suppressing or inhibiting irrelevant information present in the visual field is a vital feature of human plasticity. To examine how long-term involvement in action video games modulates the neural processes of the inhibitory control mechanism is the aim of this study. The experiment involves quantitative analysis of brain signals of Action video game players (AVGPs) and non-AVGPs on an attention inhibit...
Source: Biomedical Signal Processing and Control - June 7, 2018 Category: Biomedical Science Source Type: research

Baseline wander and power line interference removal from ECG signals using eigenvalue decomposition
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Rishi Raj Sharma, Ram Bilas Pachori In this paper, a novel method is proposed for baseline wander (BW) and power line interference (PLI) removal from electrocardiogram (ECG) signals. The proposed methodology is based on the eigenvalue decomposition of the Hankel matrix. It has been observed that the end-point eigenvalues of the Hankel matrix formed using noisy ECG signals are correlated with BW and PLI components. We have proposed a methodology to remove BW and PLI noise by eliminating eigenvalues corresponding to noisy com...
Source: Biomedical Signal Processing and Control - June 7, 2018 Category: Biomedical Science Source Type: research

Changes in connectivity and local synchrony after cognitive stimulation – Intracerebral EEG study
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Petr Klimes, Pavel Jurak, Josef Halamek, Robert Roman, Jan Chladek, Milan Brazdil Electroencephalographic studies utilize event-related power decrease/increase in order to analyze changes of neuronal activity in a single EEG channel during cognitive tasks. Other analytical approaches draw on bivariate methods which evaluate connectivity between two EEG channels. Despite the fact that spatial mapping of combined results of power and connectivity analyses may be used to study the dynamics of neuronal activation patterns, they...
Source: Biomedical Signal Processing and Control - June 6, 2018 Category: Biomedical Science Source Type: research

Prediction therapy outcomes of HCV patients treated with interferon/ribavirin
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Zeinab Ebrahimi, Niloofar Gharesi, Mohammad Mehdi Arefi, Ali Akbar Safavi, Mehrdad Hosseini Zadeh Hepatitis C is a kind of an infectious disease that mainly has an impact on the liver and also disrupts its activities. As an approximation, 130∼170 millions of people around the world have been suffering from hepatitis C virus. Until now, a combination of interferon-alpha (IFN-Alpha) and ribavirin (RBV) is employed as a therapy to those who infected with hepatitis C virus (HCV). This paper presents powerful and novel metho...
Source: Biomedical Signal Processing and Control - June 6, 2018 Category: Biomedical Science Source Type: research

Automated detection of parenchymal changes of ischemic stroke in non-contrast computer tomography: A fuzzy approach
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): A. Davis, N. Gordillo, E. Montseny, F.X. Aymerich, M. López-Córdova, J. Mej’ia, L. Ortega, B. Mederos The detection of ischemic changes is a primary task in the interpretation of brain Computer Tomography (CT) of patients suffering from neurological disorders. Although CT can easily show these lesions, their interpretation may be difficult when the lesion is not easily recognizable. The gold standard for the detection of acute stroke is highly variable and depends on the experience of physicians. This re...
Source: Biomedical Signal Processing and Control - June 6, 2018 Category: Biomedical Science Source Type: research

Detection of preterm labor by partitioning and clustering the EHG signal
This study aims to predict the risk of preterm labor by analyzing electrohysterogram (EHG). To this purpose, the Term-Preterm EHG Database (TPEHG Database) with 300 EHG signals from pregnant women that are categorized into two classes of term (262) and preterm (38) has been taken into account. This research proposes an algorithm based on time-frequency analysis and thresholding methods for quantitative estimation of uterine contractions. This estimation dismantles the EHG signals into small segments where each segment refers to an event. Then, Linear Predictive Coding (LPC) is applied to extract features from these segment...
Source: Biomedical Signal Processing and Control - June 6, 2018 Category: Biomedical Science Source Type: research

Open-access software for analysis of fetal heart rate signals
In this study, open-access software (CTG-OAS) developed with MATLAB® is introduced for the analysis of FHR signals. The software contains important processes of the automated CTG analysis, from accessing the database to conducting model evaluations. In addition to traditionally used morphological, linear, nonlinear, and time–frequency features, the developed software introduces an innovative approach called image-based time–frequency features to characterize FHR signals. All functions of the software are well documented, and it is distributed freely for research purposes. In addition, an experimental study ...
Source: Biomedical Signal Processing and Control - June 6, 2018 Category: Biomedical Science Source Type: research

Scalp tapping-based protocol for adjusting the parameters of binaural hearing aids
In this study, we propose a new scalp tapping-based protocol for controlling the parameters of binaural HAs. We then demonstrate the reliability, benefits, and clinical feasibility of the protocol via subjective evaluations from 11 volunteers. In the reliability test, the implemented scalp-tapping detection algorithm showed accuracies above 95.0% in various conditions and no false adjustment of internal parameters occurred from motions or other artifacts. In the benefit test, improvements of signal-to-noise ratio (SNR) and segmental SNR were 2.42–4.04 dB and 1.22–3.95 dB on average for serial connection of ...
Source: Biomedical Signal Processing and Control - June 6, 2018 Category: Biomedical Science Source Type: research

ECG-derived respiration estimation from single-lead ECG using gaussian process and phase space reconstruction methods
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Parvaneh Janbakhshi, Mohammad B. Shamsollahi Respiratory activity influences electrocardiographic measurements (ECG) in various ways. Therefore, extraction of respiratory information from ECG, namely ECG-derived respiratory (EDR), can be used as a promising noninvasive method to monitor respiration activity. In this paper, an automatic EDR extraction system using single-lead ECG is proposed. Respiration effects on ECG are categorized into two different models: additive and multiplicative based models. After selection of a p...
Source: Biomedical Signal Processing and Control - June 6, 2018 Category: Biomedical Science Source Type: research

A new method for automatically modelling brain functional networks
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Gang Li, Bo Li, Yonghua Jiang, Weidong Jiao, Hu Lan, Chungeng Zhu Traditional methods for constructing brain functional network often need to artificially set a certain threshold, which requires professional and technical personnel to do this work. In order to overcome this deficiency, this study proposed a new method that can automatically construct brain functional network from electroencephalogram (EEG) data, based on positional relations among the vertices and network motif theories. To verify this method, resting state...
Source: Biomedical Signal Processing and Control - June 6, 2018 Category: Biomedical Science Source Type: research

Assistive technology using regurgitation fraction and fractional-order integration to assess pulmonary valve insufficiency for pre-surgery decision making and post-surgery outcome evaluation
This study proposes an assistive technology to quantify regurgitation using the regurgitation fraction (RF) and heart pump efficiency (HPE). In signal preprocessing stage, the detrending and zero-crossing processes are used to remove the unwanted flow fluctuations and identify the end-systolic and end-diastolic periods per each cardiac cycle. The fractional-order integrations are employed to calculate the stroke volume (SV) and regurgitation volume (RV). Then, the regurgitation flow can be quantified that indicates the high correlation with HPE. For a mimicking pulmonary circulation loop system, the proposed screening mode...
Source: Biomedical Signal Processing and Control - June 1, 2018 Category: Biomedical Science Source Type: research

A visual attention guided unsupervised feature learning for robust vessel delineation in retinal images
Conclusions The discriminative features learned via visual attention mechanism is superior to hand-crafted features, and it is easily adaptable to various kind of datasets where generous training images are often scarce. Hence, our approach can be easily integrated into large-scale retinal screening programs where the expensive labelled annotation is often unavailable. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - June 1, 2018 Category: Biomedical Science Source Type: research

Joint power line interference suppression and ECG signal recovery in transform domains
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Hongqing Liu, Yong Li, Yi Zhou, Xiaorong Jing, Trieu-Kien Truong This work addresses the electrocardiogram (ECG) recovery problem in the presence of power line interference (PLI) that corrupts the signal quality if it is not effectively suppressed. In this paper, the PLI is modeled as a linear superposition of sinusoidal signals, which has a sparse representation in the frequency domain. To accurately reconstruct the ECG, the time, second-order difference, and wavelet domains are exploited to sparsely represent the ECG. From ...
Source: Biomedical Signal Processing and Control - June 1, 2018 Category: Biomedical Science Source Type: research

Myocardial segmentation in cardiac magnetic resonance images using fully convolutional neural networks
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Liset Vázquez Romaguera, Francisco Perdigón Romero, Cicero Ferreira Fernandes Costa Filho, Marly Guimarães Fernandes Costa According to the World Health Organization, cardiovascular diseases are the leading cause of death worldwide. Many coronary diseases involve the left ventricle; therefore, estimation of several functional parameters from a previous segmentation of this structure can be helpful in diagnosis. Although a high number of automated methods have been proposed, left ventricle segmentation in ...
Source: Biomedical Signal Processing and Control - June 1, 2018 Category: Biomedical Science Source Type: research

Deep learning with 3D-second order difference plot on respiratory sounds
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Gokhan Altan, Yakup Kutlu, Adnan Özhan Pekmezci, Serkan Nural The second order difference plot (SODP) is a nonlinear signal analysis method that visualizes two consecutive data points for many types of biomedical signals. The proposed method is based on analysing quantization of 3D-space which is originated using three consecutive data points in signal. The obtained 3D-SODP space was segmented into 3–10 spaces using octants, spheres and cuboid polyhedrons of which centroids are at the origin. Lung sound is an ind...
Source: Biomedical Signal Processing and Control - May 30, 2018 Category: Biomedical Science Source Type: research

A dual model approach to EOG-based human activity recognition
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Yu Lu, Chao Zhang, Bang-Yan Zhou, Xiang-Ping Gao, Zhao Lv Ongoing eyeball activities can be recorded as Electrooculography (EOG) to discover the links between human activities and eye movements. In the present work, we propose a dual model to achieve human activity recognition (HAR) under a specific task background. Specifically, the “EOG Signals Recognition (ESR)” model is used to recognize basic eye movement unit signals collected under different activities; the “Activities Relationship (AR)” model...
Source: Biomedical Signal Processing and Control - May 27, 2018 Category: Biomedical Science Source Type: research

A novel algorithm for segmentation of leukocytes in peripheral blood
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Haichao Cao, Hong Liu, Enmin Song In the detection of anemia, leukemia and other blood diseases, the number and type of leukocytes are essential evaluation parameters. However, the conventional leukocyte counting method is not only quite time-consuming but also error-prone. Consequently, many automation methods are introduced for the diagnosis of medical images. It remains difficult to accurately extract related features and count the number of cells under the variable conditions such as background, staining method, stainin...
Source: Biomedical Signal Processing and Control - May 25, 2018 Category: Biomedical Science Source Type: research

Artificial pancreas clinical trials: Moving towards closed-loop control using insulin-on-board constraints
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Emilia Fushimi, Nicolás Rosales, Hernán De Battista, Fabricio Garelli Artificial pancreas (AP) systems for people with type 1 diabetes (T1DM) combine the use of a smart insulin pump with a Continuous Glucose Monitor (CGM) and a control algorithm to improve the regulation of glycaemia. Based on the extensive clinical evidence provided by the main research groups in the area, a hybrid control algorithm combining insulin meal boluses and glucose feedback action has been recently approved. However, this sort of al...
Source: Biomedical Signal Processing and Control - May 25, 2018 Category: Biomedical Science Source Type: research

Multiple-feature-branch convolutional neural network for myocardial infarction diagnosis using electrocardiogram
Publication date: August 2018 Source:Biomedical Signal Processing and Control, Volume 45 Author(s): Wenhan Liu, Qijun Huang, Sheng Chang, Hao Wang, Jin He Generally, 12-lead electrocardiogram (ECG) is widely used in MI diagnosis. It has two unique attributes namely integrity and diversity. But most of the previous studies on automated MI diagnosis algorithm didn’t utilize these two attributes simultaneously. In this paper, a novel Multiple-Feature-Branch Convolutional Neural Network (MFB-CNN) is proposed for automated MI detection and localization using ECG. Each independent feature branch of the MFB-CNN corresponds...
Source: Biomedical Signal Processing and Control - May 25, 2018 Category: Biomedical Science Source Type: research

Accurate detection of speech auditory brainstem responses using a spectral feature-based ANN method
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Anwar Fallatah, Hilmi R. Dajani The speech auditory brainstem response (sABR) is a promising tool that can be used for objectively assessing auditory function. The main problem in obtaining the sABR is the high background noise, especially noise associated with general brain activity. In practice, a very long recording is needed to detect the sABR. We therefore propose a new detection method of the sABR based on spectral feature extraction that will reduce the detection time without reducing the accuracy. This method involves...
Source: Biomedical Signal Processing and Control - May 22, 2018 Category: Biomedical Science Source Type: research

Estimation of the second heart sound split using windowed sinusoidal models
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Rasmus G. Sæderup, Poul Hoang, Simon Winther, Morten Bøttcher, Johannes Struijk, Samuel Schmidt, Jan Østergaard Knowing the time difference between the onsets of the aortic part (A2) and the pulmonic part (P2) of the second heart sound (S2), also referred to as the time split (TS) of S2, can assist in the diagnosis of a variety of heart diseases. However, estimating the TS is a non-trivial task due to the potential overlap between A2 and P2. In this paper, a model-based approach is proposed where both A2 a...
Source: Biomedical Signal Processing and Control - May 18, 2018 Category: Biomedical Science Source Type: research

An ECG compression algorithm with guaranteed reconstruction quality based on optimum truncation of singular values and ASCII character encoding
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Sourav Kumar Mukhopadhyay, M. Omair Ahmad, M.N.S. Swamy An efficient electrocardiogram (ECG) compression algorithm provides two-fold benefits: first, it enlarges the storage capability and second, it enhances the transmission efficiency of the communication-link in real-time tele-monitoring applications. Maintaining the quality of the reconstructed signal at a pre-determined level is a very important criterion of an ECG compression algorithm, but the area of such quality-guaranteed ECG signal compression is still lagging behi...
Source: Biomedical Signal Processing and Control - May 17, 2018 Category: Biomedical Science Source Type: research

Automatic seizure detection by modified line length and Mahalanobis distance function
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Anagh Pathak, Aditya Ramesh, Anupam Mitra, Kaushik Majumdar Automatic seizure detection with high accuracy and in linear time has profound implications on therapeutic intervention mechanisms. In this work taking into account 12 popular seizure detection algorithms we have shown that line length is one feature that is extractable in linear time from EEG signals and capable of automatic seizure onset detection with highest accuracy among linear time extractable features. Also line length is less prone to give false positives. T...
Source: Biomedical Signal Processing and Control - May 16, 2018 Category: Biomedical Science Source Type: research

Creating smooth SI. B-spline basis function representations of insulin sensitivity
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Kent W. Stewart, Christopher G. Pretty, Geoffrey M. Shaw, J. Geoffrey Chase In the intensive care unit (ICU), stress-induced insulin resistance leading to hyperglycemia is commonplace. If safe and effective glycemic control (GC) can be provided, a significant reduction in the negative effects of dysglycemia can be achieved. The Intensive Control Insulin-Nutrition-Glucose (ICING) model has worked particularly well in guiding patient-specific GC. The current method to identify patient- and time- specific insulin sensitivity (SI...
Source: Biomedical Signal Processing and Control - May 16, 2018 Category: Biomedical Science Source Type: research

Diagnosis of shockable rhythms for automated external defibrillators using a reliable support vector machine classifier
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Minh Tuan Nguyen, Ahsan Shahzad, Binh Van Nguyen, Kiseon Kim Sudden cardiac arrest is mainly caused by ventricular fibrillation and ventricular tachycardia, which are known as shockable rhythms. In this paper, a detection algorithm of shockable rhythms including support vector machine (SVM) model uses the public electrocardiogram (ECG) databases for training and testing. The databases are the Creighton University Ventricular Tachyarrhythmia Database (CUDB) and the MIT-BIH Malignant Ventricular Arrhythmia Database (VFDB). At f...
Source: Biomedical Signal Processing and Control - May 15, 2018 Category: Biomedical Science Source Type: research

On clustering based nonlinear projective filtering of biomedical signals
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Tomasz Przybyła, Marian Kotas, Jacek Łęski We propose to modify the method of nonlinear state-space projections (NSSP) by application of the technique of k-means clustering. NSSP performs reconstruction of the state-space representation of the processed signals using the Taken's method of delays. Then it projects each state-space point on the appropriately constructed signal subspace and recovers the one-dimensional signal by averaging the results of all projections. The k-means clustering is applied to form so-called neig...
Source: Biomedical Signal Processing and Control - May 9, 2018 Category: Biomedical Science Source Type: research

Grid cell firing field detection using compressed sensing
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Panagiotis C. Petrantonakis The discovery of the striking tessellating firing fields of the grid cells has boosted research on brain circuits that dynamically represent self-location. The detection of such cells demands long-ran recordings, in order for the whole grid mosaic to be clearly revealed. The scope of this study is to present a methodology for unraveling the complete firing field of a grid cell even when it is poorly represented by the recorded spikes. The proposed approach is based on the fact that the recorded spi...
Source: Biomedical Signal Processing and Control - May 9, 2018 Category: Biomedical Science Source Type: research

Divide-and-conquer muscle synergies: A new feature space decomposition approach for simultaneous multifunction myoelectric control
In this study, we proposed a new feature space decomposition approach to alleviate the difficulty brought by muscle synergies for simultaneous control of hand and wrist movements. In the feature space decomposition approach, Gaussian mixture modeling (GMM) clustering is used to split the whole feature space into a set of Gaussian clusters, each consisting of samples with similar characteristics, to “divide-and-conquer” the complex muscle synergies. Then, a hybrid simultaneous control strategy, which consists of switch control of hand movements and proportional control of wrist movements, is performed in each cl...
Source: Biomedical Signal Processing and Control - May 9, 2018 Category: Biomedical Science Source Type: research

Efficient classification of ventricular arrhythmias using feature selection and C4.5 classifier
This study demonstrated that by using informative features and classifying them with C4.5 algorithms, the system data could be an aid to the clinician for precise detection of ventricular arrhythmias. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - May 9, 2018 Category: Biomedical Science Source Type: research

Classification of ictal and interictal EEG using RMS frequency, dominant frequency, root mean instantaneous frequency square and their parameters ratio
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Arindam Gajendra Mahapatra, Keiichi Horio In this work, we have proposed to use root mean square (RMS) frequency f r and dominant frequency f d along with the ratio of their contributing parameters as features for classification of interictal and ictal electroencephalogram (EEG). Empirical mode decomposition (EMD) is used for decomposing EEG into a finite set of intrinsic mode functions (IMFs). IMFs are then represented into analytic form by applying Hilbert transform over it. Analytical form of these IMFs are utilized to ext...
Source: Biomedical Signal Processing and Control - May 9, 2018 Category: Biomedical Science Source Type: research

Monitoring of fetal heart rate using sharp transition FIR filter
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Niyan Marchon, Gourish Naik, Radhakrishna Pai We propose a novel technique which uses a linear phase sharp transition finite impulse response filter with reduction in band edge ripples due to Gibb’s phenomenon. This is accomplished by a slope matching technique. This design can be used for processing a wide variety of signals irrespective of their bandwidth. This paper includes the mathematical design analysis of the band pass filter with slope matching which used fetal frequency fiduciary edges to filter the raw abdomi...
Source: Biomedical Signal Processing and Control - May 5, 2018 Category: Biomedical Science Source Type: research

Discrimination of four class simple limb motor imagery movements for brain –computer interface
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Eltaf Abdalsalam M, Mohd Zuki Yusoff, Dalia Mahmoud, Aamir Saeed Malik, Mohammad Rida Bahloul The discrimination of four simple limb motor imagery movements for brain-computer interface (BCI) applications is still challenging. This is because most of the movement imaginations have close spatial representations on the motor cortex area. Nevertheless, due to its potential applications in significant areas including BCI, solutions need to be formulated to overcome the task discrimination issues faced when a motor imagery movemen...
Source: Biomedical Signal Processing and Control - May 4, 2018 Category: Biomedical Science Source Type: research

Noise detection in phonocardiograms by exploring similarities in spectral features
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Adriana Leal, Diogo Nunes, Ricardo Couceiro, Jorge Henriques, Paulo Carvalho, Isabel Quintal, César Teixeira Analysis and interpretation of heart sounds (HSs) can be seriously hindered by noise contamination when signals are acquired in noncontrolled environments. Signal processing methodologies are then required in order to robustly analyse HSs collected in different recording settings. Some works already address this problem using complex calculus that are usually dependent on the accurate segmentation of the signals...
Source: Biomedical Signal Processing and Control - April 26, 2018 Category: Biomedical Science Source Type: research

Human fall detection using machine vision techniques on RGB –D images
Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Leila Panahi, Vahid Ghods Falling represents one of the major problems faced by elderly people. In the present research, a machine vision-based system was designed. Depth map images were captured using Microsoft Kinect® camera. They were processed for extracting features and designing the detection algorithm, apply SVM classifier, to distinguish falling pose from normal pose in 70 video samples. Furthermore, another experiment was conducted on the basis of threshold on the feature of distance to the floor, with its output...
Source: Biomedical Signal Processing and Control - April 25, 2018 Category: Biomedical Science Source Type: research