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A model-based control scheme for depth of hypnosis in anesthesia
Publication date: April 2018 Source:Biomedical Signal Processing and Control, Volume 42 Author(s): Luca Merigo, Fabrizio Padula, Andrzej Pawlowski, Sebastián Dormido, José Luis Guzmán Sánchez, Nicola Latronico, Massimiliano Paltenghi, Antonio Visioli In this paper we propose a model-based scheme to control the depth of hypnosis in anesthesia that uses the BIS signal as controlled variable. In particular, the control scheme exploits the propofol pharmacokinetics/pharmacodynamics model of the patient so that the estimated effect-site concentration is used as a feedback signal for a standard PID c...
Source: Biomedical Signal Processing and Control - February 15, 2018 Category: Biomedical Science Source Type: research

Music induced emotion using wavelet packet decomposition —An EEG study
The objective of this study was to analyze the dynamic emotional responses of the participants to self-selected music using Electroencephalography (EEG). The frequency localization with respect to time for the given stimulus (liked and disliked music) in various EEG bands was established by implementing a multi-resolution analysis algorithm using Wavelet Packet Decomposition (WPD).Ten healthy adults with an average age of 20 years (without any formal training in music) participated in this study. The perceived emotion of the participants was assessed using Self-Assessment Manikin (SAM) scale and brain activity,while they w...
Source: Biomedical Signal Processing and Control - February 8, 2018 Category: Biomedical Science Source Type: research

The exclusive presence of the chronic pulmonary disease could be more important in affecting autonomic cardiac modulation than the severity of airflow obstruction: Analysis using heart rate variability
This study aimed to analyze the effects of chronic obstructive pulmonary disease (COPD) on autonomic modulation through heart rate variability (HRV) and its relationship with airflow severity. Outpatients with COPD (n = 30) and a control group (n = 26) were evaluated. The main outcome measures were anthropometry, spirometry and HRV. The presence of COPD had a large effect on autonomic modulation, demonstrated by a significant reduction in 6 out of 12 HRV indices according to the comparisons between the COPD groups (high and low severity) and the control group through HRV indices (rMSSD: 13.5 ± 7.3 vs. 10...
Source: Biomedical Signal Processing and Control - February 7, 2018 Category: Biomedical Science Source Type: research

A convolutional neural network for sleep stage scoring from raw single-channel EEG
We present a novel method for automatic sleep scoring based on single-channel EEG. We introduce the use of a deep convolutional neural network (CNN) on raw EEG samples for supervised learning of 5-class sleep stage prediction. The network has 14 layers, takes as input the 30-s epoch to be classified as well as two preceding epochs and one following epoch for temporal context, and requires no signal preprocessing or feature extraction phase. We train and evaluate our system using data from the Sleep Heart Health Study (SHHS), a large multi-center cohort study including expert-rated polysomnographic records. Performance metr...
Source: Biomedical Signal Processing and Control - February 7, 2018 Category: Biomedical Science Source Type: research

Efficient wavelet-based artifact removal for electrodermal activity in real-world applications
Publication date: April 2018 Source:Biomedical Signal Processing and Control, Volume 42 Author(s): Jainendra Shukla, Miguel Barreda-Ángeles, Joan Oliver, Domènec Puig Online monitoring of electrodermal activity (EDA) may serve as an economical and explicit source of information about actual emotional state and engagement level of users during their interaction with information and communications technologies (ICT) applications in real-world situations. In such contexts, however, EDA signal is affected by motion artifacts that introduce noise in the signal and can make it unusable. As the scope of movement mi...
Source: Biomedical Signal Processing and Control - February 5, 2018 Category: Biomedical Science Source Type: research

Ultrasonic characterization and multiscale analysis for the evaluation of dental implant stability: A sensitivity study
Publication date: April 2018 Source:Biomedical Signal Processing and Control, Volume 42 Author(s): I. Scala, G. Rosi, V.-H. Nguyen, R. Vayron, G. Haiat, S. Seuret, S. Jaffard, S. Naili With the aim of surgical success, the evaluation of dental implant long-term stability is an important task for dentists. About that, the complexity of the newly formed bone and the complex boundary conditions at the bone-implant interface induce the main difficulties. In this context, for the quantitative evaluation of primary and secondary stabilities of dental implants, ultrasound based techniques have already been proven to be effective...
Source: Biomedical Signal Processing and Control - February 5, 2018 Category: Biomedical Science Source Type: research

Comparison of time-domain, frequency-domain and non-linear analysis for distinguishing congestive heart failure patients from normal sinus rhythm subjects
This study therefore investigated the characteristic features of heart rate changes to assess how they differed between both groups. Fifty-two normal sinus rhythm subjects and 18 congestive heart failure patients from the PhysioNet database were studied. Nine common heart rate indices were studied: three time-domain indices (MEAN RR interval, standard deviation of successive RR SDNN, and square root of mean squared differences of successive RR RMSSD), three frequency-domain indices (normalized low-frequency power LFn, normalized high-frequency power HFn, and their ratio LF/HF), and three non-linear indices (vector length i...
Source: Biomedical Signal Processing and Control - February 5, 2018 Category: Biomedical Science Source Type: research

Gait symmetry measures: A review of current and prospective methods
Publication date: April 2018 Source:Biomedical Signal Processing and Control, Volume 42 Author(s): Slavka Viteckova, Patrik Kutilek, Zdenek Svoboda, Radim Krupicka, Jan Kauler, Zoltan Szabo Gait symmetry is important in measuring gait pattern alterations for establishing the level of functional limitation due to pathology, observing its changes over time and evaluating rehabilitative intervention effects. The aim of this topical review is twofold: 1) to present used symmetry measures and summarize their application to a diverse range of gait data and to demonstrate their capabilities in their utilization in research and p...
Source: Biomedical Signal Processing and Control - February 3, 2018 Category: Biomedical Science Source Type: research

A review on CT image noise and its denoising
Publication date: April 2018 Source:Biomedical Signal Processing and Control, Volume 42 Author(s): Manoj Diwakar, Manoj Kumar CT imaging is widely used in medical science over the last decades. The process of CT image reconstruction depends on many physical measurements such as radiation dose, software/hardware. Due to statistical uncertainty in all physical measurements in Computed Tomography, the inevitable noise is introduced in CT images. Therefore, edge-preserving denoising methods are required to enhance the quality of CT images. However, there is a tradeoff between noise reduction and the preservation of actual med...
Source: Biomedical Signal Processing and Control - February 3, 2018 Category: Biomedical Science Source Type: research

Robust insulin estimation under glycemic variability using Bayesian filtering and Gaussian process models
Publication date: April 2018 Source:Biomedical Signal Processing and Control, Volume 42 Author(s): Luis Omar Avila, Mariano De Paula, Ernesto Carlos Martinez, Marcelo Luis Errecalde The ultimate goal of an artificial pancreas (AP) is finding the optimal insulin rates that can effectively reduce high blood glucose (BG) levels in type 1 diabetic patients. To achieve this, most autonomous closed-loop strategies continuously compute the optimal insulin bolus to be administrated on the basis of the estimated plasma concentrations for glucose and insulin. Unlike subcutaneous glucose levels which can be measured in real-time, un...
Source: Biomedical Signal Processing and Control - February 3, 2018 Category: Biomedical Science Source Type: research

Quantitative assessment of parkinsonian tremor based on a linear acceleration extraction algorithm
This study, on the basis of the Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) criteria, proposed a custom quantitative assessment system for parkinsonian tremors. It adopted an attitude estimation-based gradient descent algorithm to separate the linear acceleration (caused by pure translational motion) from the accelerometer output, which combines gravity component. Signal features extracted from the linear accelerations and angular velocities during the tremor tasks were fitted to the clinicians’ ratings with a multiple regression model. Clinical exper...
Source: Biomedical Signal Processing and Control - February 3, 2018 Category: Biomedical Science Source Type: research

Novel approach to human walking speed enhancement based on drift estimation
Publication date: April 2018 Source:Biomedical Signal Processing and Control, Volume 42 Author(s): Krzysztof Brzostowski The speed of human walking is a valuable indicator of individuals’ health status, for example in sports or medicine. Classic methods such as the camera-based approach have serious limitations: (1) they can be used only in the laboratory setting, and (2) the computational complexity of the data processing is remarkably high. The development of small wearable inertial sensing systems and suitable methods of data processing allow the analysis of human motion to be performed outside the laboratory. Mo...
Source: Biomedical Signal Processing and Control - February 3, 2018 Category: Biomedical Science Source Type: research

Layered vasculature segmentation of color conjunctival image based on wavelet transform
Publication date: April 2018 Source:Biomedical Signal Processing and Control, Volume 42 Author(s): Xiang Ma, Kexin Xu, Jingying Jiang, Rong Liu, Xuyao Yu The vasculature segmentation is one of the essential procedures in the conjunctival image analysis in medicine and biometrics. The vascular patterns segmented from the images are affected by the multi-scale, especially the multi-layer feature of the conjunctival vessel. Based on the Monte Carlo simulation and wavelet transform analysis, a layered vasculature segmentation approach for color conjunctival images were developed, so as to extract the conjunctival vessels by l...
Source: Biomedical Signal Processing and Control - February 3, 2018 Category: Biomedical Science Source Type: research

Epilepsy and seizure characterisation by multifractal analysis of EEG subbands
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Debdeep Sikdar, Rinku Roy, Manjunatha Mahadevappa Electroencephalography (EEG) is often used for detection of epilepsy and seizure. To capture chaotic nature and abrupt changes, considering the nonlinear as well as nonstationary behaviour of EEG, a novel nonlinear approach of MultiFractal Detrended Fluctuation Analysis (MFDFA) has been proposed in this paper to address the multifractal behaviour of healthy (Group B), interictal (Group D) and ictal (Group E) patterns. Following wavelet based decomposition of EEG into its freq...
Source: Biomedical Signal Processing and Control - January 31, 2018 Category: Biomedical Science Source Type: research

Open- and closed-loop responses of joint mechanisms in perturbed stance under visual and cognitive interference
This study was aimed at evaluating the roles of visual and cognitive interference on regulations of the joint strategies. Sixteen healthy young males were stood on a rotating support with open and closed eyes and with and without cognitive interference (total four sensory conditions). Motion analysis was employed to obtain kinematic changes in the body. In addition to calculating some classical metrics (path length, range of joint motion, etc), the SDA was applied to the kinematics of the center of mass and lower limb joints to determine how they use sensory information during perturbed stance. Effects of vision were merel...
Source: Biomedical Signal Processing and Control - January 31, 2018 Category: Biomedical Science Source Type: research

Miniaturized-electroneurostimulators and self-powered/rechargeable implanted devices for electrical-stimulation therapy
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Sathish Reddy, Liumin He, Seeram Ramakrishana Advances in technology provide a path towards a new type of medicine that allows physicians to treat diseases with electricity rather than drugs. Recently, miniaturized-electroneurostimulators or electroceuticals which employ electrical-stimulation to affect and modify functions of the body have been attracting great attention. Since the nervous system is criss-crossing in our body to control many aspects of our organ function, bioelectronic implants can treat disease by stimulat...
Source: Biomedical Signal Processing and Control - January 3, 2018 Category: Biomedical Science Source Type: research

A self-adaptive frequency selection common spatial pattern and least squares twin support vector machine for motor imagery electroencephalography recognition
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Duan Li, Hongxin Zhang, Muhammad Saad Khan, Fang Mi Motor imagery brain-computer interface (BCI) systems require accurate and fast recognition of brain activity patterns for reliable communication and interaction. Achieving this accuracy is still a challenge because of the low signal-to-noise ratio in electroencephalography signals and high variability of sensorimotor rhythms. To address this need, we proposed a novel scheme that combined a frequency band selection common spatial pattern algorithm and a particle swarm optimi...
Source: Biomedical Signal Processing and Control - December 31, 2017 Category: Biomedical Science Source Type: research

Classification of imbalanced ECG beats using re-sampling techniques and AdaBoost ensemble classifier
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Kandala N.V.P.S. Rajesh, Ravindra Dhuli Computer-aided heartbeat classification has a significant role in the diagnosis of cardiac dysfunction. Electrocardiogram (ECG) provides vital information about the heartbeats. In this work, we propose a method for classifying five groups of heartbeats recommended by AAMI standard EC57:1998. Considering the nature of ECG signal, we employed a non-stationary and nonlinear decomposition technique termed as improved complete ensemble empirical mode decomposition (ICEEMD). Later, higher or...
Source: Biomedical Signal Processing and Control - December 28, 2017 Category: Biomedical Science Source Type: research

Feature fusion for imbalanced ECG data analysis
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Wei Lu, Honghui Hou, Jinghui Chu World Health Organization (WHO) indicates that cardiovascular disease remains challenging in diagnosis and treatment. The electrocardiogram (ECG) is a very important diagnostic assistant for cardiac diseases. Traditionally, most of the ECG analysis methods are evaluated by their intra-patient performance, which however may not suitable for inter-patient cases. Here, we propose a complete classification system with excellent generalization ability. We first extract the 2D-convolutional and PQR...
Source: Biomedical Signal Processing and Control - December 21, 2017 Category: Biomedical Science Source Type: research

An appraisal of nodules detection techniques for lung cancer in CT images
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Muhammad Zia ur Rehman, Muzzamil Javaid, Syed Irtiza Ali Shah, Syed Omer Gilani, Mohsin Jamil, Shahid Ikramullah Butt Lung cancer has a five-year survival rate of 17.7% which increases to 54.4% when it is diagnosed at early stages. Automated detection techniques have been developed to detect and diagnose nodules at early stages in computer tomography (CT) images. This paper presents a systematic analysis of the recent nodules detection techniques with the goal to summerize current trends and future challenges. The relevant p...
Source: Biomedical Signal Processing and Control - December 21, 2017 Category: Biomedical Science Source Type: research

A novel seizure diagnostic model based on kernel density estimation and least squares support vector machine
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Mingyang Li, Wanzhong Chen, Tao Zhang The automated system can be an effective tool for assisting neurologists in seizure detection. However, most of the existing methods are failed to trade off the effectivity and computation cost, which is not appropriate for on-line application. In this research, we propose a novel method for dealing with 3-class electroencephalogram (EEG) problem, based upon kernel density estimation (KDE) and least squares support vector machine (LS-SVM). The filtered EEG is decomposed into several sub-...
Source: Biomedical Signal Processing and Control - December 17, 2017 Category: Biomedical Science Source Type: research

An efficient approach for EEG sleep spindles detection based on fractal dimension coupled with time frequency image
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Wessam Al-salman, Yan Li, Peng Wen, Mohammed Diykh Detection of the characteristics of the sleep stages, such as sleep spindles and K-complexes in EEG signals, is a challenging task in sleep research as visually detecting them requires high skills and efforts from sleep experts. In this paper, we propose a robust method based on time frequency image (TFI) and fractal dimension (FD) to detect sleep spindles in EEG signals. The EEG signals are divided into segments using a sliding window technique. The window size is set to 0....
Source: Biomedical Signal Processing and Control - December 14, 2017 Category: Biomedical Science Source Type: research

Evaluation of an artificial pancreas in in silico patients with online-tuned internal model control
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Arpita Bhattacharjee, Arvind Easwaran, Melvin Khee-Shing Leow, Namjoon Cho A fully-automated controller in the artificial pancreas (AP) system designed to regulate blood glucose concentration can give better lifestyle to a type 1 diabetic patient. This paper deals with evaluating the benefit of fully-automated online-tuned controller for the AP system over offline-tuned and semi-automated controller based on internal model control (IMC) strategy. The online-tuned controller is fully-automatic in the sense that it can automat...
Source: Biomedical Signal Processing and Control - December 14, 2017 Category: Biomedical Science Source Type: research

An analysis of fear of crime using multimodal measurement
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Seul-Kee Kim, Hang-Bong Kang Fear of crime, which may be present without experiencing an actual crime, can restrict one’s daily physical and mental activities and reduce quality of life. In previous research, fear of crime was measured by regional surveys. Though useful for confirming group characteristics, regional surveys cannot measure in real-time, assess individual characteristics, or provide an objective measure of anxiety. Since the causes and effects of fear of crime are highly individualized, we have developed...
Source: Biomedical Signal Processing and Control - December 13, 2017 Category: Biomedical Science Source Type: research

ECG signal compression and denoising via optimum sparsity order selection in compressed sensing framework
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Tohid Yousefi Rezaii, Soosan Beheshti, Mahdi Shamsi, Siavash Eftekharifar Advanced signal processing is widely used in healthcare systems and equipment. Compressing ECG signals is beneficial in long-term monitoring of patients’ behavior. Compressed Sensing (CS) based ECG compression has shown superiority over the existing ECG compression approaches. In current CS ECG compression methods, sparsity order (number of basis vectors involved in the compression) is determined either empirically or by thresholding approaches. ...
Source: Biomedical Signal Processing and Control - December 13, 2017 Category: Biomedical Science Source Type: research

An automatic glucose monitoring signal denoising method with noise level estimation and responsive filter updating
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Hong Zhao, Chunhui Zhao, Furong Gao Although continuous glucose monitoring (CGM) devices have been the crucial part of the artificial pancreas, their success has been discounted by random measurement noise. The difficulty of denoising methods for CGM is that the filter parameters are hard to be determined to well reflect the internal blood glucose dynamics and the real noise level. Besides, the noise level may change from device to device, subject to subject and also within the subject as time goes on which thus requires tha...
Source: Biomedical Signal Processing and Control - December 13, 2017 Category: Biomedical Science Source Type: research

A novel data acquisition and analyzing approach to spermiogram tests
In this study, we proposed a new computerized approach in which data acquisition is performed as in visual assessment, but analysis is done by computer. This approach provides more generalized results, requires less parameters due to the usage of standard counting chambers as in visual assessment technique, and cheaper than the other computerized techniques. Proposed approach includes two modules; video stabilization and motile sperm detection module. Stabilization is a requirement because it is impossible to fix proposed approach in ocular part completely. Otherwise, vibration affects the detection process of motile sperm...
Source: Biomedical Signal Processing and Control - December 13, 2017 Category: Biomedical Science Source Type: research

New features for scanned bioelectrical activity of motor unit in health and disease
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): N. Tuğrul Artuğ, Imran Goker, Bülent Bolat, Onur Osman, Elif Kocasoy Orhan, M. Baris Baslo The present study aims to find new features that support the differential diagnosis of neuromuscular diseases. Scanning EMG is an experimental method developed for understanding the motor unit organization and for observing temporal and spatial characteristics of motor unit’s electrical activity. A motor unit consists of a motor neuron and muscle fibers that are innervated by its motor neuron. Both simulation and biologica...
Source: Biomedical Signal Processing and Control - December 13, 2017 Category: Biomedical Science Source Type: research

A new priority-based dynamic protocol for multiple access control improves data transfer rates in WBANs
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Sérgio Ricardo de Jesus Oliveira, Alcimar Barbosa Soares Even with the advances made in the so-called Body Area Networks (BAN), there is still a distinct and growing demand for technology that allows for the development of applications involving high sensor density and signals gathered at very distinct sampling rates, which impose non-trivial demands on the Medium Access Control (MAC) protocol for the management of wireless systems (WBANs). In this article, the authors present a new medium access protocol for WBANs, w...
Source: Biomedical Signal Processing and Control - December 13, 2017 Category: Biomedical Science Source Type: research

Combining Improved Euler and Runge-Kutta 4th order for Tractography in Diffusion-Weighted MRI
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Dalila Cherifi, Messaoud Boudjada, Abdelatif Morsli, Gabriel Girard, Rachid Deriche Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) provides information about the local microstructure of the white matter across different voxels; this information can be used to visualize large-scale organization of the brain. Most of previously published diffusion magnetic resonance imaging reconstruction methods are linked to their own track integration method. In this work, we have formulated a general, deterministic tractography alg...
Source: Biomedical Signal Processing and Control - December 13, 2017 Category: Biomedical Science Source Type: research

Detection of sleep breathing sound based on artificial neural network analysis
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Takahiro Emoto, Udantha R. Abeyratne, Kenichiro Kawano, Takuya Okada, Osamu Jinnouchi, Ikuji Kawata Obstructive sleep apnea-hypopnea syndrome (OSAHS) is known to cause daytime drowsiness and an association with diseases such as Type II diabetes, cardiovascular disease, and stroke. A polysomnography (PSG) test is the traditional method for diagnosing OSAHS. However, this test is expensive, inconvenient, and requires the placement of body contact sensors during sleep. Recently, in several studies, the snoring/breathing episode...
Source: Biomedical Signal Processing and Control - December 13, 2017 Category: Biomedical Science Source Type: research

Denoising of dynamic PET images using a multi-scale transform and non-local means filter
In this study, we present a new method based on multi-scale and non-local means method (MNLM) to reduce noise in dynamic PET sequences of small animal heart. MNLM filter takes into account the temporal correlation between images in the dynamic measurement and benefits from the complementary properties of both the Shearlet transform and the wavelet transform to provide best reduction. The method was tested on dynamic digital mouse phantom and a preclinical rat study (n =6). Based on a comparative study with three major algorithms reviewed on the state of the art, the data analysis proved the significance of the MNLM filter....
Source: Biomedical Signal Processing and Control - December 13, 2017 Category: Biomedical Science Source Type: research

Effect of subject training on a movement-related cortical potential-based brain-computer interface
In this study, we investigated if the user could be trained to improve the performance of online detection of movement-related cortical potentials (MRCPs) associated with fast and slow movements. Seven healthy subjects participated in nine experiments over eight weeks while the ability of the online system to detect the movements was accessed. The movements were detected using template matching. No training effect was observed on the performance or MRCP morphology over the eight weeks. The system correctly detected ∼80% of the movements with ∼1.5 false positive detections/min. The findings suggest that the detectio...
Source: Biomedical Signal Processing and Control - December 13, 2017 Category: Biomedical Science Source Type: research

Acoustic analysis of voice signal: Comparison of four applications software
Conclusion Even though it is easier to access software programs and there are numerous proposals for acoustic measures, not all of them are statistically representative nor have numeric semblance among the different applications. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - November 17, 2017 Category: Biomedical Science Source Type: research

An accurate system to distinguish between normal and abnormal electroencephalogram records with epileptic seizure free intervals
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Salim Lahmiri The number of people affected by epilepsy is growing. Therefore, the design of accurate automated systems for detection and classification of electroencephalogram (EEG) signals of epileptic patients is a great aid in the diagnosis process. The purpose of this study is to present an accurate and fast automated diagnosis system to distinguish between normal and abnormal EEG records with seizure free intervals. The system is based on generalized Hurst exponent estimates at different scales used to characterize ...
Source: Biomedical Signal Processing and Control - November 17, 2017 Category: Biomedical Science Source Type: research

Improved computerized cardiac auscultation by discarding artifact contaminated PCG signal sub-sequence
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): A. Kishore Kumar, Goutam Saha Hearts sound signal recording through electronic stethoscope, also termed as phonocardiogram (PCG), is very sensitive to different kind of interferences. These interferences come as extra sounds which can appear at any instance of a heart sound cycle. A novice user may interpret these short duration interferences as a diseased marker. Also, for automated analysis of heart sound signal it is important to discard the artifact-affected signal sub-sequences. In this work, a novel method of detection...
Source: Biomedical Signal Processing and Control - November 15, 2017 Category: Biomedical Science Source Type: research

Dual Kalman filter for estimating load-free human motion kinematic energy expenditure
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Gareth Williams, Saiyi Li, Pubudu N. Pathirana The need for measuring energy expenditure using non-wearable devices in sports science is a complex task involving strict protocols of measurement. Such protocols and measurement involving indirect calorimetry or inertial measurement unit (IMU) based measurement are expensive to setup, too inaccurate or force the subjects being measured to modify their actions in a significant manner. In this paper, we explored the concept of using a parallel Kalman filter setup being used in si...
Source: Biomedical Signal Processing and Control - November 12, 2017 Category: Biomedical Science Source Type: research

SNR improvement and range side lobe suppression in Golay-encoded Doppler detection for ultrasound high-frequency swept-scan imaging system
Conclusion Golay-encoded color-flow imaging has been established using the pre-clinical system to achieve SNR improvement in Doppler detection without suffering from the range side lobe artifacts. To guarantee the performance of PRF/4 decoding, the side lobe aliasing should be avoided by carefully selecting the PRF to the match the flow velocity. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - November 11, 2017 Category: Biomedical Science Source Type: research

Sharpening enhancement technique for MR images to enhance the segmentation
This study presents a sharpening image enhancement technique based on the Laplacian pyramid (LP) and singular value decomposition (SVD) to improve the visibility and segmentation of subtle organs. The technique utilizes the shape-invariant properties of LP and the SVD techniques to enhance the perceptual sharpness of an image. The sharpening enhancement of magnetic resonance images not only sharpens the edges, but also reduces the noise effect. The results are compared with state-of-art enhancement techniques. The performance measures like peak-signal-to noise (PSNR), mean structural similarity index (MSSIM), and absolute ...
Source: Biomedical Signal Processing and Control - November 11, 2017 Category: Biomedical Science Source Type: research

Automatic identification of eye movements using the largest lyapunov exponent
Publication date: March 2018 Source:Biomedical Signal Processing and Control, Volume 41 Author(s): Alexandra I. Korda, Pantelis A. Asvestas, George K. Matsopoulos, Errikos M. Ventouras, Nikolaos Smyrnis The study of eye movements has been increasing over the past decade. It is considered that eye movements, mainly saccades and blinks, provide significant information for cognitive and visual processes of the observers. Saccades and blinks are high velocity eye movements. In this paper, the automatic identification of saccades and blinks, as well as their onset and offset, is proposed based on a novel implementation of nonl...
Source: Biomedical Signal Processing and Control - November 11, 2017 Category: Biomedical Science Source Type: research

A contralateral channel guided model for EEG based motor imagery classification
Conclusions The proposed method could exclude interference among the EOG channels and the cross-interference between the EOG and EEG channel. The results proved that the EOG signal does have certain useful information for MI classification. The proposed method could emphasize ERD/ERS features, and improve MI classification performance. Significance Compared to the regression method, the raw data based and the ipsilateral EOG channel based methods, the proposed method has significantly improved the MI classification performance. In addition, compared to other state-of-the-art methods, our approach also has obtained the best...
Source: Biomedical Signal Processing and Control - November 11, 2017 Category: Biomedical Science Source Type: research

Examination of a spectral-based ultrasonic analysis method for materials characterization and evaluation
This study examines the outcomes due to the selection of pulse width, the use of standard window functions, and spectral normalization using a reference spectrum. The consequences are assessed through the inspection of individual frequency spectra as well as two dimensional images based upon the peak density parameter. It was found that peak density was highly dependent on the window function employed and was also subject to the pulse width. Spectral normalization was found to have little effect on peak density calculations. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - November 6, 2017 Category: Biomedical Science Source Type: research

Multi-model robust control of depth of hypnosis
The objective of the proposed control scheme is to provide an adequate drug administration regime for propofol to avoid overdosing and underdosing of patients. The proposed scheme is designed to withstand the patient's inherent drug response variability, to achieve good output disturbance and sensor noise rejection, and to attain a good set point response. A comprehensive simulation study of 44 patients is presented to assess the performance of the proposed control scheme. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - November 6, 2017 Category: Biomedical Science Source Type: research

Fully automatic Breast ultrasound image segmentation based on fuzzy cellular automata framework
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Yan Liu, Yong Chen, Bo Han, Yingtao Zhang, Xutang Zhang, Yanxin Su In this paper, an effective automatic image segmentation approach based on fuzzy cellular automata (FCA) framework is proposed for handling the uncertain ascription of pixels’ status during segmentation process. Different to the existing methods, the certain outputs of cell characteristics in traditional CA are transformed into the fuzzy decision expression. For selecting the seed pixels automatically, an automatic seed point templates generation app...
Source: Biomedical Signal Processing and Control - November 6, 2017 Category: Biomedical Science Source Type: research

Sex differences in mental rotation: Cortical functional connectivity using direct transfer function
This study investigated possible reasons for sex differences in visuospatial performance by flux of information underlying cortical functional connectivity. In the present study, earlier two stages were identified as a) perceptual encoding, identification, and discrimination of objects, kept under visuospatial attention allocation network (VSAN) and b) rotation ability involving spatial transformation strategy, assigned in mental rotation network (MRN). Participants underwent 3D mental rotation task with varying difficulty levels, simultaneously having electroencephalogram (EEG). It has been confirmed in behavioural outcom...
Source: Biomedical Signal Processing and Control - November 6, 2017 Category: Biomedical Science Source Type: research

Performance assessment of a bleeding detection algorithm for endoscopic video based on classifier fusion method and exhaustive feature selection
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Farah Deeba, Monzurul Islam, Francis M. Bui, Khan A. Wahid Capsule Endoscopy (CE) is a non-invasive clinical procedure that allows examination of the entire gastrointestinal tract including parts of small intestine beyond the scope of conventional endoscope. It requires computer-aided approach for the assessment of video frames to reduce diagnosis time. This paper presents a computer-assisted method based on a classifier fusion algorithm which combines two optimized Support Vector Machine (SVM) classifiers to automaticall...
Source: Biomedical Signal Processing and Control - November 6, 2017 Category: Biomedical Science Source Type: research

3D reconstruction of coronary arteries and atherosclerotic plaques based on computed tomography angiography images
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Vassiliki I. Kigka, George Rigas, Antonis Sakellarios, Panagiotis Siogkas, Ioannis O. Andrikos, Themis P. Exarchos, Dimitra Loggitsi, Constantinos D. Anagnostopoulos, Lampros K. Michalis, Danilo Neglia, Gualtriero Pelosi, Oberdan Parodi, Dimitrios I. Fotiadis The purpose of this study is to present a new semi-automated methodology for three-dimensional (3D) reconstruction of coronary arteries and their plaque morphology using Computed Tomography Angiography (CTA) images. The methodology is summarized in seven stages: pre-...
Source: Biomedical Signal Processing and Control - November 6, 2017 Category: Biomedical Science Source Type: research

A systematic review on fatigue analysis in triceps brachii using surface electromyography
Conclusion Although, many studies in this particular field have considered the TB, further investigations are required to explain some specific facts about fatigue in the TB. The compensation strategy that muscles use to overcome fatigue, the stabilization, overcoming of errors during fatigue along with effect of mental load on brachii muscles and the effect of sports drinks and other eatables on fatigue are a few potential zones that require further in-depth research. This study will guide and direct new researchers to areas that remain hidden. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - October 25, 2017 Category: Biomedical Science Source Type: research

Altered topological properties of brain networks in the early MS patients revealed by cognitive task-related fMRI and graph theory
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Seyedeh Naghmeh Miri Ashtiani, Mohammad Reza Daliri, Hamid Behnam, Gholam-Ali Hossein-Zadeh, Masoud Mehrpour, Mohammad Reza Motamed, Fatemeh Fadaie Cognitive dysfunction or physical impairment is the result of structural lesions in the brains of patients with Multiple Sclerosis (MS), which could impress the brain functional connectivity. Cognitive deficits are frequently found in the early phases of MS disease. The changes in brain functional connectivity associated with cognitive tasks can be detected through blood oxyge...
Source: Biomedical Signal Processing and Control - October 25, 2017 Category: Biomedical Science Source Type: research

Can graph metrics be used for EEG-BCIs based on hand motor imagery?
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Carlos Alberto Stefano Filho, Romis Attux, Gabriela Castellano The study of motor imagery (MI) has been a subject of great interest within the brain-computer interface (BCI) community. Several approaches have been proposed to solve the problem of classifying cerebral responses due to MI, mostly based on the power spectral density of the mu and beta bands; however, no optimum manner of proceeding through the fundamental steps of a MI-BCI has yet been established. In this work, we explored a relatively novel approach regard...
Source: Biomedical Signal Processing and Control - October 23, 2017 Category: Biomedical Science Source Type: research