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Wavelet analysis

Gary J Hodges, Matthew M Mallette, Zachary T Martin, Andrew T Del Pozzi
Examine the effect of inhibiting sympathetic function on cutaneous vasomotion in the forearm and leg METHODS: Intradermal microdialysis fibres were placed in the forearm and leg, one as an untreated control (lactated Ringer's) the other perfused with bretylium tosylate to block sympathetic nerves. Skin blood flow was monitored using laser-Doppler flowmetry. Baseline was collected for 10 min before local skin temperature was increased to 42°C. Spectral analysis was performed using a Morlet wavelet RESULTS: Bretylium tosylate increased skin blood flow during baseline in the forearm (d=1...
June 19, 2017: Microcirculation: the Official Journal of the Microcirculatory Society, Inc
Yubo Wang, Kalyana C Veluvolu
It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC). In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model...
June 14, 2017: Sensors
Masun Nabhan Homsi, Philip Warrick
Heart sound classification and analysis play an important role in early diagnosis and prevention of cardiovascular disease. To this end, this paper introduces a novel method for automatic classification of normal and abnormal heart sound recordings. Signals are first preprocessed to extract a total of 131 features in time, frequency, wavelet and statistical domains from the entire signal and from the timings of the states. Outlier signals are then detected and separated from those with a standard range using interquartile range algorithm...
June 14, 2017: Physiological Measurement
Luhua Wu, Shijie Wang, Xiaoyong Bai, Weijun Luo, Yichao Tian, Cheng Zeng, Guangjie Luo, Shiyan He
The Yinjiang River watershed is a typical karst watershed in Southwest China. The present study explored runoff change and its responses to different driving factors in the Yinjiang River watershed over the period of 1984 to 2015. The methods of cumulative anomaly, continuous wavelet analysis, Mann-Kendall rank correlation trend test, and Hurst exponent were applied to analyze the impacts of climate change and human activities on runoff change. The contributions of climate change and human activities to runoff change were quantitatively assessed using the comparative method of the slope changing ratio of cumulative quantity (SCRCQ)...
June 8, 2017: Science of the Total Environment
Shoubing Liu, Wenke Lu, Changchun Zhu
The goal of this research is to study two-port network of wavelet transform processor (WTP) using surface acoustic wave (SAW) devices and its application. The motive was prompted by the inconvenience of the long research and design cycle and the huge research funding involved with traditional method in this field, which were caused by the lack of the simulation and emulation method of WTP using SAW devices. For this reason, we introduce the two-port network analysis tool, which has been widely used in the design and analysis of SAW devices with uniform interdigital transducers (IDTs)...
May 29, 2017: Ultrasonics
Ziran Peng, Guojun Wang
This study investigated an electrocardiogram (ECG) eigenvalue automatic analysis and detection method; ECG eigenvalues were used to reverse the myocardial action potential in order to achieve automatic detection and diagnosis of heart disease. Firstly, the frequency component of the feature signal was extracted based on the wavelet transform, which could be used to locate the signal feature after the energy integral processing. Secondly, this study established a simultaneous equations model of action potentials of the myocardial membrane, using ECG eigenvalues for regression fitting, in order to accurately obtain the eigenvalue vector of myocardial membrane potential...
2017: BioMed Research International
Rajkumar Palaniappan, Kenneth Sundaraj, Sebastian Sundaraj, N Huliraj, S S Revadi
BACKGROUND: Auscultation is a medical procedure used for the initial diagnosis and assessment of lung and heart diseases. From this perspective, we propose assessing the performance of the extreme learning machine (ELM) classifiers for the diagnosis of pulmonary pathology using breath sounds. METHODS: Energy and entropy features were extracted from the breath sound using the wavelet packet transform. The statistical significance of the extracted features was evaluated by one-way analysis of variance (ANOVA)...
June 8, 2017: Biomedizinische Technik. Biomedical Engineering
Xingkai Zhao, Zengyao Li, Qingke Zhu, Danhong Zhu, Huifang Liu
The loess hilly-gully region is a focus region of the "Grain for Green" program in China. Drought is the main problem in the study region. Precipitation and temperature are two indicators that directly characterize climatic drought. A thorough analysis of the precipitation, temperature and drought characteristics of the loess hilly-gully region can clarify the current water and heat conditions in the region to improve regional water resource management and provide a reliable reference for effectively improving water use efficiency...
2017: PloS One
Noor Kamal Al-Qazzaz, Sawal Hamid Bin Mohd Ali, Siti Anom Ahmad, Mohd Shabiul Islam, Javier Escudero
Characterizing dementia is a global challenge in supporting personalized health care. The electroencephalogram (EEG) is a promising tool to support the diagnosis and evaluation of abnormalities in the human brain. The EEG sensors record the brain activity directly with excellent time resolution. In this study, EEG sensor with 19 electrodes were used to test the background activities of the brains of five vascular dementia (VaD), 15 stroke-related patients with mild cognitive impairment (MCI), and 15 healthy subjects during a working memory (WM) task...
June 8, 2017: Sensors
Livia M Brandao, Matthias Monhart, Andreas Schötzau, Anna A Ledolter, Anja M Palmowski-Wolfe
PURPOSE: To further improve analysis of the two-flash multifocal electroretinogram (2F-mfERG) in glaucoma in regard to structure-function analysis, using discrete wavelet transform (DWT) analysis. METHODS: Sixty subjects [35 controls and 25 primary open-angle glaucoma (POAG)] underwent 2F-mfERG. Responses were analyzed with the DWT. The DWT level that could best separate POAG from controls was compared to the root-mean-square (RMS) calculations previously used in the analysis of the 2F-mfERG...
June 7, 2017: Documenta Ophthalmologica. Advances in Ophthalmology
Sasskia Brüers, Rufin VanRullen
Recent evidence has shown a rhythmic modulation of perception: prestimulus ongoing electroencephalography (EEG) phase in the θ (4-8 Hz) and α (8-13 Hz) bands has been directly linked with fluctuations in target detection. In fact, the ongoing EEG phase directly reflects cortical excitability: it acts as a gating mechanism for information flow at the neuronal level. Consequently, the key phase modulating perception should be the one present in the brain when the stimulus is actually being processed. Most previous studies, however, reported phase modulation peaking 100 ms or more before target onset...
May 2017: ENeuro
Elisabet Romero, Javier Prior, Alex W Chin, Sarah E Morgan, Vladimir I Novoderezhkin, Martin B Plenio, Rienk van Grondelle
Experimental/theoretical evidence for sustained vibration-assisted electronic (vibronic) coherence in the Photosystem II Reaction Center (PSII RC) indicates that photosynthetic solar-energy conversion might be optimized through the interplay of electronic and vibrational quantum dynamics. This evidence has been obtained by investigating the primary charge separation process in the PSII RC by two-dimensional electronic spectroscopy (2DES) and Redfield modeling of the experimental data. However, while conventional Fourier transform analysis of the 2DES data allows oscillatory signatures of vibronic coherence to be identified in the frequency domain in the form of static 2D frequency maps, the real-time evolution of the coherences is lost...
June 6, 2017: Scientific Reports
Yansong Hao, Liuyang Song, Yanliang Ke, Huaqing Wang, Peng Chen
Compound faults often occur in rotating machinery, which increases the difficulty of fault diagnosis. In this case, blind source separation, which usually includes independent component analysis (ICA) and sparse component analysis (SCA), was proposed to separate mixed signals. SCA, which is based on the sparsity of target signals, was developed to sever the compound faults and effectively diagnose the fault due to its advantage over ICA in underdetermined conditions. However, there is an issue regarding the vibration signals, which are inadequately sparse, and it is difficult to represent them in a sparse way...
June 6, 2017: Sensors
Shuting Chen, Yanjie Zhu, Zaiyi Liu, Changhong Liang
OBJECTIVE: To assess the prognostic value of texture analysis for single hepatocellular carcinomas (HCCs) after hepatectomy. MATERIALS AND METHODS: A total of 61 HCC patients were enrolled in this retrospective study. Textural characteristics of the computed tomography (CT) images were quantified. The differences between the hepatic arterial phase and the portal venous phase were obtained (the Dif.). The receiver operating characteristic (ROC) curves were used for data screening...
May 2017: European Journal of Radiology
Qiang Zhang, Abhir Bhalerao, Charles Hutchinson
PURPOSE: Representation of anatomy appearance is one of the key problems in medical image analysis. An appearance model represents the anatomies with parametric forms, which are then vectorised for prior learning, segmentation and classification tasks. METHODS: We propose a part-based parametric appearance model we refer to as a deformable appearance pyramid (DAP). The parts are delineated by multi-scale local feature pyramids extracted from an image pyramid. Each anatomy is represented by an appearance pyramid, with the variability within a population approximated by local translations of the multi-scale parts and linear appearance variations in the assembly of the parts...
June 3, 2017: International Journal of Computer Assisted Radiology and Surgery
Giulia Da Poian, Chengyu Liu, Riccardo Bernardini, Roberto Rinaldo, Gari Clifford
OBJECTIVE: Compressive Sensing (CS) approaches to electrocardiogram (ECG) analysis provide efficient methods for real time encoding of cardiac activity. In doing so, it is important to assess the downstream effect of the compression on any signal processing and classification algorithms. CS is particularly suitable for low power wearable devices, thanks to its low-complex digital or hardware implementation that directly acquires a compressed version of the signal through random projections...
June 1, 2017: Physiological Measurement
Tanya L Leise
This article is part of a Journal of Biological Rhythms series exploring analysis and statistics topics relevant to researchers in biological rhythms and sleep research. The goal is to provide an overview of the most common issues that arise in the analysis and interpretation of data in these fields. In this article on time series analysis for biological rhythms, we describe some methods for assessing the rhythmic properties of time series, including tests of whether a time series is indeed rhythmic. Because biological rhythms can exhibit significant fluctuations in their period, phase, and amplitude, their analysis may require methods appropriate for nonstationary time series, such as wavelet transforms, which can measure how these rhythmic parameters change over time...
June 2017: Journal of Biological Rhythms
Raheel Zafar, Sarat C Dass, Aamir Saeed Malik
Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity...
2017: PloS One
Deepak Joshi, Aayushi Khajuria, Pradeep Joshi
BACKGROUND AND OBJECTIVE: The automatic noninvasive identification of Parkinson's disease (PD) is attractive to clinicians and neuroscientist. Various analysis and classification approaches using spatiotemporal gait variables have been presented earlier in classifying Parkinson's gait. In this paper, we present a wavelet transform based representation of spatiotemporal gait variables to explore the potential of such representation in the identification of Parkinson's gait. METHODS: Here, we present wavelet analysis as an alternate method and show that wavelet analysis combined with support vector machine (SVM) can produce efficient classification accuracy...
July 2017: Computer Methods and Programs in Biomedicine
A Salar Elahi, M Ghoranneviss
Plasma cooling due to hard x-ray radiation from the Runaway electrons is an important issue in tokamaks. Thus, developing effective methods to reduce the Runaway electrons and the emitted hard x-ray is also important for optimal tokamak plasma operation. In this study, we investigated the effects of external fields on hard x-ray intensity and the Magnetohydrodynamic (MHD) activity. In other words, we presented the effects of positive biased limiter and Resonant Helical Field (RHF) on the MHD fluctuations and hard x-ray emission from the Runaway electrons...
May 24, 2017: Journal of X-ray Science and Technology
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