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Discrete wavelet transform

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https://www.readbyqxmd.com/read/29929530/analysis-of-sensory-system-aspects-of-postural-stability-during-quiet-standing-in-adolescent-idiopathic-scoliosis-patients
#1
Taeyong Sim, Hakje Yoo, Dongjun Lee, Seung-Woo Suh, Jae Hyuk Yang, Hyunggun Kim, Joung Hwan Mun
BACKGROUND: The aim of this study was to quantitatively analyze quite standing postural stability of adolescent idiopathic scoliosis (AIS) patients in respect to three sensory systems (visual, vestibular, and somatosensory). METHOD: In this study, we analyzed the anterior-posterior center of pressure (CoP) signal using discrete wavelet transform (DWT) between AIS patients (n = 32) and normal controls (n = 25) during quiet standing. RESULT: The energy rate (∆E EYE %) of the CoP signal was significantly higher in the AIS group than that in the control group at levels corresponding to vestibular and somatosensory systems (p < 0...
June 22, 2018: Journal of Neuroengineering and Rehabilitation
https://www.readbyqxmd.com/read/29927624/applying-a-modified-wavelet-shrinkage-filter-to-improve-cryo-electron-microscopy-imaging
#2
Xinrui Huang, Sha Li, Song Gao
Cryo-electron microscopy (Cryo-EM) imaging has the unique potential to bridge the gap between cellular and molecular biology by revealing the structures of large macromolecular assemblies and cellular complexes. Therefore, cryo-EM three-dimensional (3D) reconstruction has been rapidly developed in recent several years and applied widely in life science research; however, it suffers from reduced contrast and low signal-to-noise ratios with a high degree of noise under low electron dose conditions, resulting in failures of many conventional filters...
June 21, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29923552/understanding-perception-of-active-noise-control-system-through-multichannel-eeg-analysis
#3
Sangeeta Bagha, R K Tripathy, Pranati Nanda, C Preetam, Debi Prasad Das
In this Letter, a method is proposed to investigate the effect of noise with and without active noise control (ANC) on multichannel electroencephalogram (EEG) signal. The multichannel EEG signal is recorded during different listening conditions such as silent, music, noise, ANC with background noise and ANC with both background noise and music. The multiscale analysis of EEG signal of each channel is performed using the discrete wavelet transform. The multivariate multiscale matrices are formulated based on the sub-band signals of each EEG channel...
June 2018: Healthcare Technology Letters
https://www.readbyqxmd.com/read/29914313/multi-objective-genetic-algorithms-to-find-most-relevant-volumes-of-the-brain-related-to-alzheimer-s-disease-and-mild-cognitive-impairment
#4
Olga Valenzuela, Xiaoyi Jiang, Antonio Carrillo, Ignacio Rojas
Computer-Aided Diagnosis (CAD) represents a relevant instrument to automatically classify between patients with and without Alzheimer's Disease (AD) using several actual imaging techniques. This study analyzes the optimization of volumes of interest (VOIs) to extract three-dimensional (3D) textures from Magnetic Resonance Image (MRI) in order to diagnose AD, Mild Cognitive Impairment converter (MCIc), Mild Cognitive Impairment nonconverter (MCInc) and Normal subjects. A relevant feature of the proposed approach is the use of 3D features instead of traditional two-dimensional (2D) features, by using 3D discrete wavelet transform (3D-DWT) approach for performing feature extraction from T-1 weighted MRI...
May 7, 2018: International Journal of Neural Systems
https://www.readbyqxmd.com/read/29877399/multifocus-image-fusion-method-for-image-acquisition-of-3d-objects
#5
Changsheng Li, Xianmin Zhang, Heng Wu
We propose a multifocus image fusion method for achieving all-in-focus images of three-dimensional objects based on the combination of transform domain and spatial domain techniques. First, the source images are decomposed into low-frequency and high-frequency components by the discrete wavelet transform technique. Next, a correlation coefficient is employed to obtain the maximum similarity among low-frequency components. Then, in order not to interrupt the correlations among decomposition layers, the comparison among high-frequency components is executed by transforming them to spatial domain...
June 1, 2018: Applied Optics
https://www.readbyqxmd.com/read/29875334/acoustic%C3%A2-seismic-mixed-feature-extraction-based-on-wavelet-transform-for-vehicle-classification-in-wireless-sensor-networks
#6
Heng Zhang, Zhongming Pan, Wenna Zhang
An acoustic⁻seismic mixed feature extraction method based on the wavelet coefficient energy ratio (WCER) of the target signal is proposed in this study for classifying vehicle targets in wireless sensor networks. The signal was decomposed into a set of wavelet coefficients using the à trous algorithm, which is a concise method used to implement the wavelet transform of a discrete signal sequence. After the wavelet coefficients of the target acoustic and seismic signals were obtained, the energy ratio of each layer coefficient was calculated as the feature vector of the target signals...
June 7, 2018: Sensors
https://www.readbyqxmd.com/read/29865158/development-of-a-low-cost-fpga-based-measurement-system-for-real-time-processing-of-acoustic-emission-data-proof-of-concept-using-control-of-pulsed-laser-ablation-in-liquids
#7
Sebastian F Wirtz, Adauto P A Cunha, Marc Labusch, Galina Marzun, Stephan Barcikowski, Dirk Söffker
Today, the demand for continuous monitoring of valuable or safety critical equipment is increasing in many industrial applications due to safety and economical requirements. Therefore, reliable in-situ measurement techniques are required for instance in Structural Health Monitoring (SHM) as well as process monitoring and control. Here, current challenges are related to the processing of sensor data with a high data rate and low latency. In particular, measurement and analyses of Acoustic Emission (AE) are widely used for passive, in-situ inspection...
June 1, 2018: Sensors
https://www.readbyqxmd.com/read/29858993/derivation-of-optimal-equations-for-prediction-of-sewage-sludge-quantity-using-wavelet-conjunction-models-an-environmental-assessment
#8
Mohammad Najafzadeh, Maryam Zeinolabedini
Determining the quantity of sewage sludge is a major component of designing sludge treatment units and their handling and disposal facilities including its fluctuation over a wide range. In the present study, the capabilities of the hybrid wavelet-gene expression programming (WGEP), wavelet-model tree (WMT), and wavelet-evolutionary polynomial regression (WEPR) models have been investigated to predict the quantity of daily sewage sludge. In the first step, the single gene expression programming (GEP), model tree (MT), and evolutionary polynomial regression (EPR) models were employed to predict the amounts of sewage sludge based on the input vector content produced by the sewage sludge data series, which ranged from lagged-1 day to lagged-4 days...
June 1, 2018: Environmental Science and Pollution Research International
https://www.readbyqxmd.com/read/29843416/identifying-degenerative-brain-disease-using-rough-set-classifier-based-on-wavelet-packet-method
#9
Ching-Hsue Cheng, Wei-Xiang Liu
Population aging has become a worldwide phenomenon, which causes many serious problems. The medical issues related to degenerative brain disease have gradually become a concern. Magnetic Resonance Imaging is one of the most advanced methods for medical imaging and is especially suitable for brain scans. From the literature, although the automatic segmentation method is less laborious and time-consuming, it is restricted in several specific types of images. In addition, hybrid techniques segmentation improves the shortcomings of the single segmentation method...
May 28, 2018: Journal of Clinical Medicine
https://www.readbyqxmd.com/read/29791308/optimal-level-and-order-detection-in-wavelet-decomposition-for-pcg-signal-denoising
#10
Mohamed Rouis, Abdelkrim Ouafi, Salim Sbaa
The recorded phonocardiogram (PCG) signal is often contaminated by different types of noises that can be seen in the frequency band of the PCG signal, which may change the characteristics of this signal. Discrete wavelet transform (DWT) has become one of the most important and powerful tools of signal representation, but its effectiveness is influenced by the issue of the selected mother wavelet and decomposition level (DL). The selection of the DL and the mother wavelet are the main challenges. This work proposes a new approach for finding an optimal DL and optimal mother wavelet for PCG signal denoising...
May 23, 2018: Biomedizinische Technik. Biomedical Engineering
https://www.readbyqxmd.com/read/29783139/inspection-of-baked-carbon-anodes-using-a-combination-of-multi-spectral-acousto-ultrasonic-techniques-and-principal-component-analysis
#11
Moez Ben Boubaker, Donald Picard, Carl Duchesne, Jayson Tessier, Houshang Alamdari, Mario Fafard
This paper reports on the application of an acousto-ultrasonic (AU) scheme for the inspection of industrial-size carbon anode blocks used in the production of primary aluminium by the Hall-Héroult process. A frequency-modulated wave is used to excite the anode blocks at multiple points. The collected attenuated AU signals are decomposed using the Discrete Wavelet Transform (DTW) after which vectors of features are calculated. Principal Component Analysis (PCA) is utilized to cluster the AU responses of the anodes...
May 17, 2018: Ultrasonics
https://www.readbyqxmd.com/read/29782490/an-optimized-digital-watermarking-algorithm-in-wavelet-domain-based-on-differential-evolution-for-color-image
#12
Xinchun Cui, Yuying Niu, Xiangwei Zheng, Yingshuai Han
In this paper, a new color watermarking algorithm based on differential evolution is proposed. A color host image is first converted from RGB space to YIQ space, which is more suitable for the human visual system. Then, apply three-level discrete wavelet transformation to luminance component Y and generate four different frequency sub-bands. After that, perform singular value decomposition on these sub-bands. In the watermark embedding process, apply discrete wavelet transformation to a watermark image after the scrambling encryption processing...
2018: PloS One
https://www.readbyqxmd.com/read/29768928/automated-daily-quality-control-analysis-for-mammography-in-a-multi-unit-imaging-center
#13
Veli-Matti Sundell, Teemu Mäkelä, Alexander Meaney, Touko Kaasalainen, Sauli Savolainen
Background The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom...
January 1, 2018: Acta Radiologica
https://www.readbyqxmd.com/read/29763658/event-related-potential-analysis-techniques-for-autism-spectrum-disorders-a-review
#14
REVIEW
Priyalakshmi Sheela, Subha D Puthankattil
Autism Spectrum Disorders (ASD) comprise all pervasive neurodevelopmental diseases marked by deficits in social and communication skills, delayed cognitive development, restricted and repetitive behaviors. The core symptoms begin in early childhood, may continue life-long resulting in poor performance in adult stage. Event-related potential (ERP) is basically a time-locked electroencephalogram signal elicited by various stimuli, related to sensory and cognitive processes. The various ERP based techniques used for the study of ASD are considered in this review...
May 12, 2018: International Journal of Developmental Neuroscience
https://www.readbyqxmd.com/read/29761953/-epileptic-electroencephalogram-recognition-based-on-discrete-s-transform-and-permutation-entropy
#15
Jianzhao Zhang, Wei Jiang, Hui Yuan, Wei Shang, Shi Liu, Ping Jiao
Electroencephalogram(EEG) analysis has important reference value in the diagnosis of epilepsy. The automatic classification of epileptic EEG can be used to judge the patient's situation in time,which is of great significance in clinical application. In order to solve the problem that the recognition accuracy is not high by using the single feature of EEG signals and avoid the influence of wavelet basis function selection on recognition results,a method of automatic discrimination of epileptic EEG signals based on S transform and permutation entropy is proposed...
October 1, 2017: Sheng Wu Yi Xue Gong Cheng Xue za Zhi, Journal of Biomedical Engineering, Shengwu Yixue Gongchengxue Zazhi
https://www.readbyqxmd.com/read/29758974/emotion-recognition-from-multichannel-eeg-signals-using-k-nearest-neighbor-classification
#16
Mi Li, Hongpei Xu, Xingwang Liu, Shengfu Lu
BACKGROUND: Many studies have been done on the emotion recognition based on multi-channel electroencephalogram (EEG) signals. OBJECTIVE: This paper explores the influence of the emotion recognition accuracy of EEG signals in different frequency bands and different number of channels. METHODS: We classified the emotional states in the valence and arousal dimensions using different combinations of EEG channels. Firstly, DEAP default preprocessed data were normalized...
April 27, 2018: Technology and Health Care: Official Journal of the European Society for Engineering and Medicine
https://www.readbyqxmd.com/read/29752237/cross-comparison-of-motor-unit-potential-features-used-in-emg-signal-decomposition
#17
Mohsen Ghofrani Jahromi, Hossein Parsaei, Ali Zamani, Daniel W Stashuk
Feature extraction is an important step of resolving an electromyographic (EMG) signal into its component motor unit potential trains, commonly known as EMG decomposition. Until now, different features have been used to represent motor unit potentials (MUPs) and improve decomposition processing time and accuracy, but a major limitation is that no systematic comparison of these features exists. In an EMG decomposition system, like any pattern recognition system, the features used for representing MUPs play an important role in the overall performance of the system...
May 2018: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/29745597/-comparative-study-on-evaluation-algorithms-for-neck-muscle-fatigue-based-on-surface-electromyography-signal
#18
Yunxiao Du, Shuyi Wang, Nyakuru Zaphlene Ndaro, Yan Zuo
The purpose of this study is to compare the differences among neck muscle fatigue evaluation algorithms and to find a more effective algorithm which can provide a human factor quantitative evaluation method for neck muscle fatigue during bending over the desk. We collected surface electromyography signal of sternocleidomastoid muscle of 15 subjects using wireless physiotherapy Bio-Radio when they bent over the desk using memory pillows for 12 minutes. Five algorithms including mean power frequency, spectral moments ratio, discrete wavelet transform, fuzzy approximation entropy and the complexity algorithms were used to calculate the corresponding muscle fatigue index...
February 1, 2018: Sheng Wu Yi Xue Gong Cheng Xue za Zhi, Journal of Biomedical Engineering, Shengwu Yixue Gongchengxue Zazhi
https://www.readbyqxmd.com/read/29731106/discrete-wavelet-transform-and-energy-eigen-value-for-rotor-bars-fault-detection-in-variable-speed-field-oriented-control-of-induction-motor-drive
#19
Tarek Ameid, Arezki Menacer, Hicham Talhaoui, Youness Azzoug
This paper presents a methodology for the broken rotor bars fault detection is considered when the rotor speed varies continuously and the induction machine is controlled by Field-Oriented Control (FOC). The rotor fault detection is obtained by analyzing a several mechanical and electrical quantities (i.e., rotor speed, stator phase current and output signal of the speed regulator) by the Discrete Wavelet Transform (DWT) in variable speed drives. The severity of the fault is obtained by stored energy calculation for active power signal...
May 3, 2018: ISA Transactions
https://www.readbyqxmd.com/read/29723996/optimal-sub-band-analysis-based-on-the-envelope-power-spectrum-for-effective-fault-detection-in-bearing-under-variable-low-speeds
#20
Hung Ngoc Nguyen, Jaeyoung Kim, Jong-Myon Kim
Early identification of failures in rolling element bearings is an important research issue in mechanical systems. In this study, a reliable methodology for bearing fault detection is proposed, which is based on an optimal sub-band selection scheme using the discrete wavelet packet transform (DWPT) and envelope power analysis techniques. A DWPT-based decomposition is first performed to extract the characteristic defect features from the acquired acoustic emission (AE) signals. The envelope power spectrum (EPS) of each sub-band signal is then calculated to detect the characteristic defect frequencies to reveal abnormal symptoms in bearings...
May 1, 2018: Sensors
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