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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

Quantifying postural stability of patients with cerebellar disorder during quiet stance using three-axis accelerometer
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Barbora Adamová, Patrik Kutilek, Ondrej Cakrt, Zdenek Svoboda, Slavka Viteckova, Pavel Smrcka This work focuses on the novelty of applying a 3-D postural analysis on the cerebellar disorders diagnosis and on introduction of an alternative to recent methods of quantifying the human postural stability during quiet stance, which uses a three-axis accelerometer. It introduces an advantage in the form of an ability to evaluate a complex three-dimensional (3-D) movement, as opposed to a major limitation of todaýs ...
Source: Biomedical Signal Processing and Control - October 23, 2017 Category: Biomedical Science Source Type: research

A new expert system based on fuzzy logic and image processing algorithms for early glaucoma diagnosis
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): A. Soltani, T. Battikh, I. Jabri, N. Lakhoua Decision-making systems based on images have increasingly become essential nowadays mostly in the medical field. Indeed, the image has become one of the most fundamental tools for both clinical research and sicknesses’ diagnosis. In this context, we treat glaucoma disease which can affect the optic nerve head (ONH), thus causing its destruction and leading to an irreversible vision loss. This paper presents a new glaucoma Fuzzy Expert System for early glaucoma diagnosis. ...
Source: Biomedical Signal Processing and Control - October 23, 2017 Category: Biomedical Science Source Type: research

Investigation of brain networks in children with attention deficit/hyperactivity disorder using a graph theoretical approach
In this study, brain networks in children with attention-deficit/hyperactivity disorder (ADHD) were investigated. Electroencephalogram (EEG) data were collected from 16 children with ADHD (ADHD group) and 16 healthy children (control group) while they performed an improved visual continuous performance test. A combination coherence and graph theory method was used to construct each subject’s nerve conduction network using EEG signal data. Differences in brain network topology parameters between the two groups were then compared (two-sample t test). Results revealed the following: when performing functional tasks, alp...
Source: Biomedical Signal Processing and Control - October 23, 2017 Category: Biomedical Science Source Type: research

Multi-modality medical image fusion based on image decomposition framework and nonsubsampled shearlet transform
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Xingbin Liu, Wenbo Mei, Huiqian Du Medical image fusion increases accuracy of clinical diagnosis and analysis through integrating complementary information of multi-modality medical images. A novel multi-modality medical image fusion algorithm exploiting a moving frame based decomposition framework (MFDF) and the nonsubsampled shearlet transform (NSST) is proposed. The MFDF is applied to decompose source images into texture components and approximation components. Maximum selection fusion rule is employed to fuse texture ...
Source: Biomedical Signal Processing and Control - October 23, 2017 Category: Biomedical Science Source Type: research

Surface EMG based continuous estimation of human lower limb joint angles by using deep belief networks
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Jiangcheng Chen, Xiaodong Zhang, Yu Cheng, Ning Xi Surface electromyography (EMG) signals have been widely used in locomotion studies and human-machine interface applications. In this paper, a regression model which relates the multichannel surface EMG signals to human lower limb flexion/extension (FE) joint angles is constructed. In the experimental paradigm, three dimensional trajectories of 16 external markers on the human lower limbs were recorded by optical motion capture system and surface EMG signals from 10 muscle...
Source: Biomedical Signal Processing and Control - October 23, 2017 Category: Biomedical Science Source Type: research

Automated technique for coronary artery disease characterization and classification using DD-DTDWT in ultrasound images
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): U. Raghavendra, Hamido Fujita, Anjan Gudigar, Ranjan Shetty, Krishnananda Nayak, Umesh Pai, Jyothi Samanth, U.Rajendra Acharya Heart is one of the important as well as hardest working organ of human body. Cardiac ischemia is the condition where sufficient blood and oxygen will not reach the heart muscle due to narrowed arteries of the heart. This condition is called coronary artery disease. Several non-invasive diagnostic tests fail to reveal exact impact of coronary artery disease on myocardial segments. The ultrasound i...
Source: Biomedical Signal Processing and Control - October 23, 2017 Category: Biomedical Science Source Type: research

Automatic determination of aortic compliance based on MRI and adapted curvilinear detector
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): J. Mitéran, O. Bouchot, A. Cochet, A. Lalande Parameters of aortic elasticity, such as aortic compliance or aortic distensibility, can be estimated from cine-MRI through the knowledge of the aortic contour on each image. In this context, a completely automatic method for the measurement of aortic elasticity is proposed in this study, and compared with previously published methods which are not fully automatic. An adaptation of a curvilinear region detector was used for the aortic wall detection over the entire card...
Source: Biomedical Signal Processing and Control - October 13, 2017 Category: Biomedical Science Source Type: research

A robust unsupervised epileptic seizure detection methodology to accelerate large EEG database evaluation
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Κostas Μ. Tsiouris, Sofia Markoula, Spiros Konitsiotis, Dimitrios. D. Koutsouris, Dimitrios I. Fotiadis In this work an unsupervised methodology for the detection of epileptic seizures in long-term EEG recordings is presented. The design of the methodology exploits the available medical knowledge to tackle the lack of training data using a simple rule-based seizure detection logic, avoiding complex decision making systems, training and empirical thresholds. The Short-Time Fourier Transform is initially applied to...
Source: Biomedical Signal Processing and Control - October 12, 2017 Category: Biomedical Science Source Type: research

A robust QRS complex detection using regular grammar and deterministic automata
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Salah Hamdi, Asma Ben Abdallah, Mohamed Hedi Bedoui A novel approach is proposed for medical analysis and clinical decision support of the Electrocardiogram (ECG) signals based on the deterministic finite automata (DFA) with the addition of some requirements. This paper proves regular grammar is effective in the extraction of QRS complex and interpretation of ECG signals. The DFA will be used to represent a normalized QRS complex as a sequence of negative and positive peaks. A QRS is considered as a set of adjacent peaks ...
Source: Biomedical Signal Processing and Control - October 12, 2017 Category: Biomedical Science Source Type: research

Application of a reconstruction technique in detection of dominant SSVEP frequency
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Zhenghua Wu Steady-state visual evoked potentials (SSVEPs) have a number of specific properties such as an oscillating feature when compared to event-related potentials (ERPs). Based on this oscillating property, a short electroencephalogram (EEG) segment containing an SSVEP can be used to reconstruct a series of EEG segments where the SSVEP has the same initial phase but the phase of the background EEG varies randomly. When these reconstructed EEG segments are averaged, the background EEG is weakened, whereas the SSVEP i...
Source: Biomedical Signal Processing and Control - October 12, 2017 Category: Biomedical Science Source Type: research

Wavelet analysis of heart rate variability: Impact of wavelet selection
Conclusion It is necessary to report which wavelet is used when performing wavelet transform based heart rate variability analysis and depending on whether one is interested in detecting onset or intensity of changes performance of wavelets will vary. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - October 12, 2017 Category: Biomedical Science Source Type: research

Determination of the relationship between internal auditory canal nerves and tinnitus based on the findings of brain magnetic resonance imaging
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Burhan Ergen, Murat Baykara, Cahit Polat This experimental study aimed to investigate a relationship between tinnitus and thicknesses of internal auditory canal and nerves in it. It was performed on brain magnetic resonance images of patients who consulted the ear, nose, and throat clinic with tinnitus complaint. Statistical hypothesis tests and classification experiments were performed on these data to find out structural differences in internal auditory channel components in patients with tinnitus after obtaining cross-...
Source: Biomedical Signal Processing and Control - October 12, 2017 Category: Biomedical Science Source Type: research

Linear parameter-varying model to design control laws for an artificial pancreas
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): P. Colmegna, R.S. Sánchez-Peña, R. Gondhalekar The contribution of this work is the generation of a control-oriented model for insulin-glucose dynamic regulation in type 1 diabetes mellitus (T1DM). The novelty of this model is that it includes the time-varying nature, and the inter-patient variability of the glucose-control problem. In addition, the model is well suited for well-known and standard controller synthesis procedures. The outcome is an average linear parameter-varying (LPV) model that captures th...
Source: Biomedical Signal Processing and Control - October 12, 2017 Category: Biomedical Science Source Type: research

Validation of μ-volt T-wave alternans analysis using multiscale analysis-by-synthesis and higher-order SVD
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Sibasankar Padhy, S. Dandapat Detection of microvolt T-wave alternans (TWA) and finding its clinical significance remains a challenging task. In this work, we propose a new TWA detection method based on multiscale analysis-by-synthesis followed by higher-order singular value decomposition (MAS–HOSVD). The multilead ECG (MECG) data, after R-peak detection, were represented as a third-order tensor. Then HOSVD was applied on the subband reconstructed T-wave tensor to determine a tensor containing T-wave information (Te...
Source: Biomedical Signal Processing and Control - October 12, 2017 Category: Biomedical Science Source Type: research

Detection of epileptic dysfunctions in EEG signals using Hilbert vibration decomposition
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Ali Yener Mutlu Epilepsy is a neurological brain dysfunction that is manifested by recrudescent seizures. Due to high temporal resolution, brain activities recorded by electroencephalography (EEG) are commonly used for localization of seizures and identification of epileptic dysfunctions. However, it is often time consuming and challenging to detect EEG seizures using conventional Fourier-based methods and manual interpretation due to nonlinear and nonstationary dynamics of EEG. In this paper, we propose a new framework b...
Source: Biomedical Signal Processing and Control - October 12, 2017 Category: Biomedical Science Source Type: research

Optimal selection of features using wavelet fractal descriptors and automatic correlation bias reduction for classifying skin lesions
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Saptarshi Chatterjee, Debangshu Dey, Sugata Munshi The non-invasive computerized image analysis techniques have a great impact on accurate and uniform evaluation of skin abnormalities. The paper reports a method for the texture and morphological feature extraction from skin lesion images to differentiate common melanoma from benign nevi. In this work, a 2D wavelet packet decomposition (WPD) based fractal texture analysis has been proposed to extract the irregular texture pattern of the skin lesion area. On the whole 6214 ...
Source: Biomedical Signal Processing and Control - October 10, 2017 Category: Biomedical Science Source Type: research

Segmentation of vessels in angiograms using convolutional neural networks
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): E. Nasr-Esfahani, N. Karimi, M.H. Jafari, S.M.R. Soroushmehr, S. Samavi, B.K. Nallamothu, K. Najarian Coronary artery disease (CAD) is the most common type of heart disease and it is the leading cause of death in most parts of the world. About fifty percent of all middle-aged men and thirty percent of all middle-aged women in North America develop some type of CAD. The main tool for diagnosis of CAD is the X-ray angiography. Usually these images lack high quality and they contain noise. Accurate segmentation of vessels in...
Source: Biomedical Signal Processing and Control - October 8, 2017 Category: Biomedical Science Source Type: research

Comparison of univariate and multivariate magnitude-squared coherences in the detection of human 40-Hz auditory steady-state evoked responses
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Leonardo Bonato Felix, Felipe Antunes, Jean Antônio da Silva Carvalho, Márcio Falcão dos Santos Barroso, Antonio Mauricio Ferreira Leite Miranda de Sá Objective response detection (ORD) techniques for evaluating bioelectrical evoked responses in the electroencephalogram (EEG) are based on statistical criteria rather than on visual inspection. Hence, they do not depend on human evaluation, which is often a subjective approach. Furthermore, since such techniques do not involve heuristic approaches...
Source: Biomedical Signal Processing and Control - October 7, 2017 Category: Biomedical Science Source Type: research

Non-contact remote estimation of cardiovascular parameters
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Qiang Fan, Kaiyang Li Cardiovascular disease is a serious threat to human health. It is crucial to monitor the cardiovascular parameters reliably and conveniently. Non-contact measurement has been widely studied. However, there are some inevitable factors that limit the use of the platform and even lead to inaccuracy estimation. Hence, a novel non-contact method that estimates cardiovascular parameters under ambient light is proposed. The most suitable region of interest (ROI) is determined by a colormap, which is a map c...
Source: Biomedical Signal Processing and Control - September 29, 2017 Category: Biomedical Science Source Type: research

Fractional models in electrical impedance spectroscopy data for glucose detection
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Oscar Olarte, Kurt Barbé The article presents a methodology to discriminate glucose levels using electrical impedance spectroscopy technology. The method is based on an adequate estimation and assessment of the impedance data followed by identification of a general rational fractional model. The methodology is illustrated on a group of saline–protein–glucose solutions at physiological concentrations, and shows the ability of the fractional models to discriminate glucose levels. The method exhibit signif...
Source: Biomedical Signal Processing and Control - September 28, 2017 Category: Biomedical Science Source Type: research

Computer aided thyroid nodule detection system using medical ultrasound images
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Deepika Koundal, Savita Gupta, Sukhwinder Singh Thyroid nodule is one of the endocrine problem caused due to abnormal growth of cells. This survival rate can be enhanced by earlier detection of nodules. Thus, the accurate detection of nodule is of utmost importance in providing effective diagnosis to increase the survival rate. However, accuracy of nodule detection from ultrasound images is suffered due to speckle noise. It considerably deteriorates the image quality and makes the differentiation of fine details quite dif...
Source: Biomedical Signal Processing and Control - September 28, 2017 Category: Biomedical Science Source Type: research

Thermodynamic analogies for the characterization of 3D human coronary arteries
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): C.A. Bulant, P.J. Blanco, A. Clausse, C. Bezerra, T.P. Lima, L.F.R. Ávila, P.A. Lemos, R.A. Feijóo The thermodynamics of three-dimensional curves is explored through numerical simulations, providing room for a broader range of applications. Such approach, which makes use of elements of information theory, enables the processing of parametric as well as non-parametric data distributed along the curves. Descriptors inspired in thermodynamic concepts are derived to characterize such three-dimensional curves. Th...
Source: Biomedical Signal Processing and Control - September 27, 2017 Category: Biomedical Science Source Type: research

ECG response to submaximal exercise from the perspective of Golden Ratio harmonic rhythm
Conclusions Our results show a fractal dimension of the ECG interval dynamics for the study group. The proposed SFI imposes itself as a relatively simple parameter for assessing heart’s electrical functionality during cardiac cycle that can be applied both at rest and exercise. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - September 27, 2017 Category: Biomedical Science Source Type: research

Dimensionality effect of myoelectric-controlled interface on the coordination of agonist and antagonist muscles during voluntary isometric elbow flexion and extension
This study aimed to investigate the dimensionality effect of myoelectric-controlled interface (MCI) on the coordination of agonist and antagonist muscles during voluntary isometric elbow flexion and extension. Eighteen healthy subjects were recruited to control a controllable cursor to track a target cursor by real-time modulating the biceps and triceps activities within one-dimensional and two-dimensional MCIs. Electromyographic (EMG) signals were collected to calculate the normalized muscle activation, while the slope of the best-fitting linear relationship between the normalized agonist and antagonist activations was us...
Source: Biomedical Signal Processing and Control - September 24, 2017 Category: Biomedical Science Source Type: research

An efficient ECG denoising methodology using empirical mode decomposition and adaptive switching mean filter
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Manas Rakshit, Susmita Das Electrocardiogram (ECG) is a widely employed tool for the analysis of cardiac disorders. A clean ECG is often desired for proper treatment of cardiac ailments. However, in the real scenario, ECG signals are corrupted with various noises during acquisition and transmission. In this article, an efficient ECG denoising methodology using combined empirical mode decomposition (EMD) and adaptive switching mean filter (ASMF) is proposed. The advantages of both EMD and ASMF techniques are exploited to r...
Source: Biomedical Signal Processing and Control - September 24, 2017 Category: Biomedical Science Source Type: research

Spatially adaptive denoising for X-ray cardiovascular angiogram images
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Zhenghua Huang, Yaozong Zhang, Qian Li, Tianxu Zhang, Nong Sang The X-ray angiogram image denoising is always one of the most popular research in the field of computer vision. While the methods removed the noise, the useful structure (such as peripheral vascular) had also been smoothed, the fundamental reason is that the denoising methods cannot efficiently distinguish structural areas from flat areas. In this paper, we have proposed a spatially adaptive image denoising (SAID) method which contains two steps: spatially ad...
Source: Biomedical Signal Processing and Control - September 24, 2017 Category: Biomedical Science Source Type: research

Use of kinematic and mel-cepstrum-related features for fall detection based on data from infrared depth sensors
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Paweł Mazurek, Jakub Wagner, Roman Z. Morawski A methodology for acquisition and preprocessing of measurement data from infrared depth sensors, when applied for fall detection, combined with several approaches to the classification of those data, is proposed. Data processing is initiated with extraction of the silhouette from the depth image and estimation of the coordinates of the center of that silhouette. Next, two groups of features to be applied for a fall/non-fall classification are extracted: kinematic features (v...
Source: Biomedical Signal Processing and Control - September 24, 2017 Category: Biomedical Science Source Type: research

Multiscale sequential convolutional neural networks for simultaneous detection of fovea and optic disc
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Baidaa Al-Bander, Waleed Al-Nuaimy, Bryan M. Williams, Yalin Zheng Detecting the locations of the optic disc and fovea is a crucial task towards developing automatic diagnosis and screening tools for retinal disease. We propose to address this challenging problem by investigating the potential of applying deep learning techniques to this field. In the proposed method, simultaneous detection of the centers of the fovea and the optic disc (OD) from color fundus images is considered as a regression problem. A deep multiscale...
Source: Biomedical Signal Processing and Control - September 23, 2017 Category: Biomedical Science Source Type: research

Time-varying analysis of the heart rate variability during A-phases of sleep: Healthy and pathologic conditions
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Guadalupe Dorantes-Méndez, Martin O. Mendez, Alfonso Alba, Liborio Parrino, Giulia Milioli In the present study, a comparison of the heart rate variability (HRV) behavior between healthy subjects and Nocturnal Front Lobe Epilepsy (NFLE) patients was carried out during the A-phases of sleep. The A-phases are short cortical events that interrupt the basal oscillation of the sleep stages and form the cyclic alternating pattern phenomenon. HRV was assessed by means of standard temporal measures and frequency measures b...
Source: Biomedical Signal Processing and Control - September 23, 2017 Category: Biomedical Science Source Type: research

Reducing vaccination level to eradicate a disease by means of a mixed control with isolation
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Erivelton G. Nepomuceno, Ricardo H.C. Takahashi, Luis A. Aguirre The present study has investigated mixed control strategy to reduce the required level of vaccination to eradicate a disease. It is well known that despite the advances on the development of new vaccines and control strategies to eradicate diseases, many diseases such as measles, tuberculosis and flu are still persistent. Any effort made to bring some light in this issue should be considered and developed. Here, we present a dynamic analysis of the SIR model...
Source: Biomedical Signal Processing and Control - September 18, 2017 Category: Biomedical Science Source Type: research

Research on the ROI registration algorithm of the cardiac CT image time series
Conclusion The proposed algorithm equipped with the robustness and stability can greatly reduce the time required for registration, improve the registration accuracy. (Source: Biomedical Signal Processing and Control)
Source: Biomedical Signal Processing and Control - September 18, 2017 Category: Biomedical Science Source Type: research

Applications of sparse recovery and dictionary learning to enhance analysis of ambulatory electrodermal activity data
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Malia Kelsey, Murat Akcakaya, Ian R. Kleckner, Richard Vincent Palumbo, Lisa Feldman Barrett, Karen S. Quigley, Matthew S. Goodwin Electrodermal Activity (EDA) − an index of sympathetic nervous system arousal − is one of the primary methods used in psychophysiology to assess the autonomic nervous system [1]. While many studies collect EDA data in short, laboratory-based experiments, recent developments in wireless biosensing have enabled longer, ‘out-of-lab’ ambulatory studies to become more common...
Source: Biomedical Signal Processing and Control - September 15, 2017 Category: Biomedical Science Source Type: research

Adaptive overlapping-group sparse denoising for heart sound signals
Publication date: February 2018 Source:Biomedical Signal Processing and Control, Volume 40 Author(s): Shi-Wen Deng, Ji-Qing Han The heart sound (HS) is an important physiological signal of the human body and can provide valuable diagnostic information in the clinical auscultation. The HS signal, however, is often contaminated by noise and the noisy HS signal will cause adverse influence of making the diagnosis. In this paper, we proposed an adaptive denoising algorithm, named adaOGS denoising, based on the overlapping-group sparsity (OGS) of the first-order difference of the HS signal. Under the Bayesian framework, the ad...
Source: Biomedical Signal Processing and Control - September 15, 2017 Category: Biomedical Science Source Type: research