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https://www.readbyqxmd.com/read/28343061/automated-diabetic-macular-edema-dme-grading-system-using-dwt-dct-features-and-maculopathy-index
#1
U Rajendra Acharya, Muthu Rama Krishnan Mookiah, Joel E W Koh, Jen Hong Tan, Sulatha V Bhandary, A Krishna Rao, Yuki Hagiwara, Chua Kuang Chua, Augustinus Laude
The cause of diabetic macular edema (DME) is due to prolonged and uncontrolled diabetes mellitus (DM) which affects the vision of diabetic subjects. DME is graded based on the exudate location from the macula. It is clinically diagnosed using fundus images which is tedious and time-consuming. Regular eye screening and subsequent treatment may prevent the vision loss. Hence, in this work, a hybrid system based on Radon transform (RT), discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed for an automated detection of DME...
March 19, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28339601/characterization-and-consistency-of-interactions-of-triggers-and-substrate-at-the-onset-of-paroxysmal-atrial-fibrillation
#2
David G Jones, Vias Markides, Anthony W C Chow, Richard J Schilling, Prapa Kanagaratnam, Tom Wong, D Wyn Davies, Nicholas S Peters
Aims: Initiating mechanisms of atrial fibrillation (AF) remain poorly understood, involving complex interaction between triggers and the atrial substrate. This study sought to classify the transitional phenomena, hypothesizing that there is consistency within and between patients in trigger-substrate interaction during transition to AF. Methods and results: Non-contact left atrial (LA) mapping was performed in 17 patients undergoing ablation for paroxysmal AF. All had spontaneous ectopy...
January 25, 2017: Europace: European Pacing, Arrhythmias, and Cardiac Electrophysiology
https://www.readbyqxmd.com/read/28339503/rat-retinal-vasomotion-assessed-by-laser-speckle-imaging
#3
Anastasiia Y Neganova, Dmitry D Postnov, Olga Sosnovtseva, Jens Christian B Jacobsen
Vasomotion is spontaneous or induced rhythmic changes in vascular tone or vessel diameter that lead to rhythmic changes in flow. While the vascular research community debates the physiological and pathophysiological consequence of vasomotion, there is a great need for experimental techniques that can address the role and dynamical properties of vasomotion in vivo. We apply laser speckle imaging to study spontaneous and drug induced vasomotion in retinal network of anesthetized rats. The results reveal a wide variety of dynamical patterns...
2017: PloS One
https://www.readbyqxmd.com/read/28335480/weighted-kernel-entropy-component-analysis-for-fault-diagnosis-of-rolling-bearings
#4
Hongdi Zhou, Tielin Shi, Guanglan Liao, Jianping Xuan, Jie Duan, Lei Su, Zhenzhi He, Wuxing Lai
This paper presents a supervised feature extraction method called weighted kernel entropy component analysis (WKECA) for fault diagnosis of rolling bearings. The method is developed based on kernel entropy component analysis (KECA) which attempts to preserve the Renyi entropy of the data set after dimension reduction. It makes full use of the labeled information and introduces a weight strategy in the feature extraction. The class-related weights are introduced to denote differences among the samples from different patterns, and genetic algorithm (GA) is implemented to seek out appropriate weights for optimizing the classification results...
March 18, 2017: Sensors
https://www.readbyqxmd.com/read/28332540/-wavelet-revolution-pioneer-scoops-top-maths-award
#5
Davide Castelvecchi
No abstract text is available yet for this article.
March 21, 2017: Nature
https://www.readbyqxmd.com/read/28329015/adaptive-control-paradigm-for-photovoltaic-and-solid-oxide-fuel-cell-in-a-grid-integrated-hybrid-renewable-energy-system
#6
Sidra Mumtaz, Laiq Khan
The hybrid power system (HPS) is an emerging power generation scheme due to the plentiful availability of renewable energy sources. Renewable energy sources are characterized as highly intermittent in nature due to meteorological conditions, while the domestic load also behaves in a quite uncertain manner. In this scenario, to maintain the balance between generation and load, the development of an intelligent and adaptive control algorithm has preoccupied power engineers and researchers. This paper proposes a Hermite wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control of photovoltaic (PV) systems to extract maximum power and a Hermite wavelet incorporated NeuroFuzzy indirect adaptive control of Solid Oxide Fuel Cells (SOFC) to obtain a swift response in a grid-connected hybrid power system...
2017: PloS One
https://www.readbyqxmd.com/read/28324998/prediction-of-the-outcome-in-cardiac-arrest-patients-undergoing-hypothermia-using-eeg-wavelet-entropy
#7
Hana Moshirvaziri, Nima Ramezan-Arab, Shadnaz Asgari
Cardiac arrest (CA) is the leading cause of death in the United States. Induction of hypothermia has been found to improve the functional recovery of CA patients after resuscitation. However, there is no clear guideline for the clinicians yet to determine the prognosis of the CA when patients are treated with hypothermia. The present work aimed at the development of a prognostic marker for the CA patients undergoing hypothermia. A quantitative measure of the complexity of Electroencephalogram (EEG) signals, called wavelet sub-band entropy, was employed to predict the patients' outcomes...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324996/analysis-of-the-non-stationarity-of-neural-activity-during-an-auditory-oddball-task-in-schizophrenia
#8
P Nunez, J Poza, J Gomez-Pilar, A Bachiller, C Gomez, A Lubeiro, V Molina, R Hornero
The aim of this study was to characterize brain dynamics during an auditory oddball task. For this purpose, a measure of the non-stationarity of a given time-frequency representation (TFR) was applied to electroencephalographic (EEG) signals. EEG activity was acquired from 20 schizophrenic (SCH) patients and 20 healthy controls while they underwent a three-stimulus auditory oddball task. The Degree of Stationarity (DS), a measure of the non-stationarity of the TFR, was computed using the continuous wavelet transform...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324937/data-driven-estimation-of-blood-pressure-using-photoplethysmographic-signals
#9
Shi Chao Gao, Peter Wittek, Li Zhao, Wen Jun Jiang
Noninvasive measurement of blood pressure by optical methods receives considerable interest, but the complexity of the measurement and the difficulty of adjusting parameters restrict applications. We develop a method for estimating the systolic and diastolic blood pressure using a single-point optical recording of a photoplethysmographic (PPG) signal. The estimation is data-driven, we use automated machine learning algorithms instead of mathematical models. Combining supervised learning with a discrete wavelet transform, the method is insensitive to minor irregularities in the PPG waveform, hence both pulse oximeters and smartphone cameras can record the signal...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28321249/mexican-hat-wavelet-kernel-elm-for-multiclass-classification
#10
Jie Wang, Yi-Fan Song, Tian-Lei Ma
Kernel extreme learning machine (KELM) is a novel feedforward neural network, which is widely used in classification problems. To some extent, it solves the existing problems of the invalid nodes and the large computational complexity in ELM. However, the traditional KELM classifier usually has a low test accuracy when it faces multiclass classification problems. In order to solve the above problem, a new classifier, Mexican Hat wavelet KELM classifier, is proposed in this paper. The proposed classifier successfully improves the training accuracy and reduces the training time in the multiclass classification problems...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28316861/complexity-analysis-of-electroencephalogram-dynamics-in-patients-with-parkinson-s-disease
#11
Guotao Liu, Yanping Zhang, Zhenghui Hu, Xiuquan Du, Wanqing Wu, Chenchu Xu, Xiangyang Wang, Shuo Li
In this study, a new combination scheme has been proposed for detecting Parkinson's disease (PD) from electroencephalogram (EEG) signal recorded from normal subjects and PD patients. The scheme is based on discrete wavelet transform (DWT), sample entropy (SampEn), and the three-way decision model in analysis of EEG signal. The EEG signal is noisy and nonstationary, and, as a consequence, it becomes difficult to distinguish it visually. However, the scheme is a well-established methodology in analysis of EEG signal in three stages...
2017: Parkinson's Disease
https://www.readbyqxmd.com/read/28303099/meet-spinky-an-open-source-spindle-and-k-complex-detection-toolbox-validated-on-the-open-access-montreal-archive-of-sleep-studies-mass
#12
Tarek Lajnef, Christian O'Reilly, Etienne Combrisson, Sahbi Chaibi, Jean-Baptiste Eichenlaub, Perrine M Ruby, Pierre-Emmanuel Aguera, Mounir Samet, Abdennaceur Kachouri, Sonia Frenette, Julie Carrier, Karim Jerbi
Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microstructures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is important for sleep studies in both healthy subjects and patients with sleep disorders. Therefore, procedures for automatic detection of spindles and K-complexes could provide valuable assistance to researchers and clinicians in the field...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28301356/local-heating-test-for-detection-of-microcirculation-abnormalities-in-patients-with-diabetes-related-foot-complications
#13
Aleksey Parshakov, Nadezhda Zubareva, Sergey Podtaev, Peter Frick
OBJECTIVE: In this study, authors used a wavelet analysis of skin temperature (WAST) to assess the mechanisms of microvascular tone regulation during the local heating test in patients with diabetic foot syndrome (DFS). PARTICIPANTS: The participants included control subjects and 36 hospitalized patients with DFS between 52 and 79 years old (68 ± 8 years old). They were distributed among 5 groups: 15 control subjects, 8 patients with DFS who did not develop ulcerative or necrotic disorders, 10 patients who developed the neuroischemic form of DFS complicated by foot ulceration, 12 patients with DFS complicated by toe necrosis, and 6 patients with DFS and foot gangrene...
April 2017: Advances in Skin & Wound Care
https://www.readbyqxmd.com/read/28300790/non-destructive-detection-of-wire-rope-discontinuities-from-residual-magnetic-field-images-using-the-hilbert-huang-transform-and-compressed-sensing
#14
Juwei Zhang, Xiaojiang Tan, Pengbo Zheng
Electromagnetic methods are commonly employed to detect wire rope discontinuities. However, determining the residual strength of wire rope based on the quantitative recognition of discontinuities remains problematic. We have designed a prototype device based on the residual magnetic field (RMF) of ferromagnetic materials, which overcomes the disadvantages associated with in-service inspections, such as large volume, inconvenient operation, low precision, and poor portability by providing a relatively small and lightweight device with improved detection precision...
March 16, 2017: Sensors
https://www.readbyqxmd.com/read/28298702/fixed-versus-mixed-rsa-%C3%A2-explaining-visual-representations-by-fixed-and-mixed-feature-sets-from-shallow-and-deep-computational-models
#15
Seyed-Mahdi Khaligh-Razavi, Linda Henriksson, Kendrick Kay, Nikolaus Kriegeskorte
Studies of the primate visual system have begun to test a wide range of complex computational object-vision models. Realistic models have many parameters, which in practice cannot be fitted using the limited amounts of brain-activity data typically available. Task performance optimization (e.g. using backpropagation to train neural networks) provides major constraints for fitting parameters and discovering nonlinear representational features appropriate for the task (e.g. object classification). Model representations can be compared to brain representations in terms of the representational dissimilarities they predict for an image set...
February 2017: Journal of Mathematical Psychology
https://www.readbyqxmd.com/read/28298182/electrocardiogram-his-bundle-potentials-can-be-recorded-noninvasively-beat-by-beat-on-surface-electrocardiogram
#16
Gaopin Wang, Renguang Liu, Qinghua Chang, Zhaolong Xu, Yingjie Zhang, Dianzhu Pan
BACKGROUND: The micro waveform of His bundle potential can't be recorded beat-to-beat on surface electrocardiogram yet. We have found that the micro-wavelets before QRS complex may be related to atrioventricular conduction system potentials. This study is to explore the possibility of His bundle potential can be noninvasively recorded on surface electrocardiogram. METHODS: We randomized 65 patients undergoing radiofrequency catheter ablation of paroxysmal superventricular tachycardia (exclude overt Wolff-Parkinson-White syndrome) to receive "conventional electrocardiogram" and "new electrocardiogram" before the procedure...
March 15, 2017: BMC Cardiovascular Disorders
https://www.readbyqxmd.com/read/28295824/wavelet-entropy-of-bold-time-series-an-application-to-rolandic-epilepsy
#17
Lalit Gupta, Jacobus F A Jansen, Paul A M Hofman, René M H Besseling, Anton J A de Louw, Albert P Aldenkamp, Walter H Backes
PURPOSE: To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy. MATERIALS AND METHODS: The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated...
March 11, 2017: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/28286048/effect-of-age-on-cutaneous-vasomotor-responses-during-local-skin-heating
#18
Gary J Hodges, Matthew M Mallette, Garry A Tew, John M Saxton, James Moss, Alan D Ruddock, Markos Klonizakis
This study examined the effect of ageing on the low-frequency oscillations (vasomotion) of skin blood flow in response to local heating (LH). Skin blood flow was assessed by laser-Doppler flowmetry on the forearm at rest (33°C) and in response to LH of the skin to both 42°C and 44°C in 14 young (24±1years) and 14 older (64±1years) participants. Vasomotion was analyzed using a wavelet transform to investigate power of the frequency intervals associated with endothelial, neural, myogenic, respiratory, and cardiac activities of the laser-Doppler signal...
March 9, 2017: Microvascular Research
https://www.readbyqxmd.com/read/28284000/a-method-for-microcalcifications-detection-in-breast-mammograms
#19
Abbas H Hassin Alasadi, Ahmed Kadem Hamed Al-Saedi
Breast cancer is the most cause of death for women above age 40 around the world. In this paper, we propose a method to detect microcalcifications in digital mammography images using two-dimensional Discrete Wavelets Transform and image enhancement techniques for removing noise as well as to get a better contrast. The initial step is applying a preprocessing techniques to improve the edge of the breast and then segmentation process (Region of interest) for eliminating some regions in the image, which are not useful for the mammography interpretation...
April 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28278203/a-high-performance-seizure-detection-algorithm-based-on-discrete-wavelet-transform-dwt-and-eeg
#20
Duo Chen, Suiren Wan, Jing Xiang, Forrest Sheng Bao
In the past decade, Discrete Wavelet Transform (DWT), a powerful time-frequency tool, has been widely used in computer-aided signal analysis of epileptic electroencephalography (EEG), such as the detection of seizures. One of the important hurdles in the applications of DWT is the settings of DWT, which are chosen empirically or arbitrarily in previous works. The objective of this study aimed to develop a framework for automatically searching the optimal DWT settings to improve accuracy and to reduce computational cost of seizure detection...
2017: PloS One
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