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Wavelet transform

Zach Marin, J Kent Wallace, Jay Nadeau, Andre Khalil
We propose an automated wavelet-based method of tracking particles in unreconstructed off-axis holograms to provide rough estimates of the presence of motion and particle trajectories in digital holographic microscopy (DHM) time series. The wavelet transform modulus maxima segmentation method is adapted and tailored to extract Airy-like diffraction disks, which represent bacteria, from DHM time series. In this exploratory analysis, the method shows potential for estimating bacterial tracks in low-particle-density time series, based on a preliminary analysis of both living and dead Serratia marcescens, and for rapidly providing a single-bit answer to whether a sample chamber contains living or dead microbes or is empty...
September 12, 2017: Methods: a Companion to Methods in Enzymology
A Menżyk, A Martyna, G Zadora
Polymers have become a ubiquitous element of our culture. Therefore, these materials may play an important role in forensic investigations, serving as mute witnesses of occurrences such as car accidents. In this study, the possibilities provided by the likelihood ratio (LR) approach to estimate the evidential value of observed similarities and differences, and to discriminate among NIR spectral data originating from polypropylene automotive parts and household items, were investigated. Since the construction of LR models requires the introduction of only a few variables, the main objective was to reduce the dimensionality of registered spectra, which are characterised by over a thousand variables...
September 15, 2017: Analyst
Asiya M Al-Busaidi, Lazhar Khriji, Farid Touati, Mohd Fadlee Rasid, Adel Ben Mnaouer
One of the major issues in time-critical medical applications using wireless technology is the size of the payload packet, which is generally designed to be very small to improve the transmission process. Using small packets to transmit continuous ECG data is still costly. Thus, data compression is commonly used to reduce the huge amount of ECG data transmitted through telecardiology devices. In this paper, a new ECG compression scheme is introduced to ensure that the compressed ECG segments fit into the available limited payload packets, while maintaining a fixed CR to preserve the diagnostic information...
September 12, 2017: Journal of Medical Systems
Ning Zhuang, Ying Zeng, Li Tong, Chi Zhang, Hanming Zhang, Bin Yan
This paper introduces a method for feature extraction and emotion recognition based on empirical mode decomposition (EMD). By using EMD, EEG signals are decomposed into Intrinsic Mode Functions (IMFs) automatically. Multidimensional information of IMF is utilized as features, the first difference of time series, the first difference of phase, and the normalized energy. The performance of the proposed method is verified on a publicly available emotional database. The results show that the three features are effective for emotion recognition...
2017: BioMed Research International
Rakesh Pilkar, Arvind Ramanujam, Karen J Nolan
BACKGROUND: A foot drop stimulator (FDS) is a rehabilitation intervention that stimulates the common peroneal nerve to facilitate ankle dorsiflexion at the appropriate time during post-stroke hemiplegic gait. Time-frequency analysis (TFA) of non-stationary surface electromyograms (EMG) and spectral variables such as instantaneous mean frequency (IMNF) can provide valuable information on the long-term effects of FDS intervention in terms of changes in the motor unit (MU) recruitment during gait, secondary to improved dorsiflexion...
2017: Frontiers in Neurology
Rakesh Vasireddy, Corinne Roth, Johannes Mathis, Josef Goette, Marcel Jacomet, Andreas Vogt
An estimated 45 million persons in Europe are annually subjected to sleep-wake disorders. State-of-the-art polysomnography provides sophisticated insights into sleep (patho)physiology. A drawback of the method, however, is the obtrusive setting dependent on a clinical-based sleep laboratory with high operational costs. A contact-less prototype was developed to monitor limb movements and vital signs during sleep. A dual channel K-band Doppler radar transceiver captured limb movements and periodic chest wall motion due to respiration and heart activity...
September 11, 2017: Journal of Clinical Monitoring and Computing
Rajesh Kumar Tripathy, Samarendra Dandapat
The complex wavelet sub-band bi-spectrum (CWSB) features are proposed for detection and classification of myocardial infarction (MI), heart muscle disease (HMD) and bundle branch block (BBB) from 12-lead ECG. The dual tree CW transform of 12-lead ECG produces CW coefficients at different sub-bands. The higher-order CW analysis is used for evaluation of CWSB. The mean of the absolute value of CWSB, and the number of negative phase angle and the number of positive phase angle features from the phase of CWSB of 12-lead ECG are evaluated...
April 2017: Healthcare Technology Letters
Khalid A M Attia, Nasr M El-Abasawi, Ahmed El-Olemy, Ahmed Serag
Five simple spectrophotometric methods were developed for the determination of simeprevir in the presence of its oxidative degradation product namely, ratio difference, mean centering, derivative ratio using the Savitsky-Golay filters, second derivative and continuous wavelet transform. These methods are linear in the range of 2.5-40μg/mL and validated according to the ICH guidelines. The obtained results of accuracy, repeatability and precision were found to be within the acceptable limits. The specificity of the proposed methods was tested using laboratory prepared mixtures and assessed by applying the standard addition technique...
September 5, 2017: Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
Hironori Shigeta, Tomohiro Mashita, Junichi Kikuta, Shigeto Seno, Haruo Takemura, Masaru Ishii, Hideo Matsuda
Emerging bioimaging technologies enable us to capture various dynamic cellular activities in vivo. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on...
August 25, 2017: Journal of Bioinformatics and Computational Biology
Shuto Nagai, Daisuke Anzai, Jianqing Wang
Wearable Electrocardiogram (ECG) is attracting much attention in daily healthcare applications. From the viewpoint of long-term use, it is desired that the electrodes are non-contact with the human body. In this study, the authors propose an algorithm using the stationary wavelet transform (SWT) to remove motion artefact superimposed on ECG signal when using non-contact capacitively coupling electrodes. The authors evaluate the effect on motion artefact removal of this algorithm by applying it to various ECG signals with motion artefacts superimposed...
August 2017: Healthcare Technology Letters
Junjiang Zhu, Xiaolu Li
Noise in ECG signals will affect the result of post-processing if left untreated. Since ECG is highly subjective, the linear denoising method with a specific threshold working well on one subject could fail on another. Therefore, in this Letter, sparse-based method, which represents every segment of signal using different linear combinations of atoms from a dictionary, is used to denoise ECG signals, with a view to myoelectric interference existing in ECG signals. Firstly, a denoising model for ECG signals is constructed...
August 2017: Healthcare Technology Letters
Peng Li, Xu Zhang, Ming Liu, Xiaohui Hu, Bo Pang, Zhaolin Yao, Hanjun Jiang, Hongda Chen
This paper proposes a low power and efficient QRS processor for real-time and continuous mobile ECG monitoring. The QRS detector contains the wavelet transform (WT), the modulus maxima pair identification (MMPI), and the R position modification (RPM). In order to reduce power consumption, we choose the Haar function as the mother wavelet of WT. It is implemented by an optimized FIR filter structure where none of the multiplier is used. The MMPI processes the wavelet coefficients at scale 2 (4) and provides candidate R peak positions for the RPM...
August 29, 2017: IEEE Transactions on Biomedical Circuits and Systems
Alcebiades Dal Col, Paola Valdivia, Fabiano Petronetto, Fabio Dias, Claudio T Silva, L Gustavo Nonato
Dynamic networks naturally appear in a multitude of applications from different fields. Analyzing and exploring dynamic networks in order to understand and detect patterns and phenomena is challenging, fostering the development of new methodologies, particularly in the field of visual analytics. In this work, we propose a novel visual analytics methodology for dynamic networks, which relies on the spectral graph wavelet theory. We enable the automatic analysis of a signal defined on the nodes of the network, making viable the robust detection of network properties...
August 29, 2017: IEEE Transactions on Visualization and Computer Graphics
Zhao Feng, Jie Ling, Min Ming, Xiao-Hui Xiao
For precision motion, high-bandwidth and flexible tracking are the two important issues for significant performance improvement. Iterative learning control (ILC) is an effective feedforward control method only for systems that operate strictly repetitively. Although projection ILC can track varying references, the performance is still limited by the fixed-bandwidth Q-filter, especially for triangular waves tracking commonly used in a piezo nanopositioner. In this paper, a wavelet transform-based linear time-varying (LTV) Q-filter design for projection ILC is proposed to compensate high-frequency errors and improve the ability to tracking varying references simultaneously...
August 2017: Review of Scientific Instruments
Maria Teodora Ferreira, Rosangela Follmann, Margarete O Domingues, Elbert E N Macau, István Z Kiss
Phase synchronization may emerge from mutually interacting non-linear oscillators, even under weak coupling, when phase differences are bounded, while amplitudes remain uncorrelated. However, the detection of this phenomenon can be a challenging problem to tackle. In this work, we apply the Discrete Complex Wavelet Approach (DCWA) for phase assignment, considering signals from coupled chaotic systems and experimental data. The DCWA is based on the Dual-Tree Complex Wavelet Transform (DT-CWT), which is a discrete transformation...
August 2017: Chaos
Asma ElAdel, Mourad Zaied, Chokri Ben Amar
Deep Convolutional Neural Network (DCNN) can be marked as a powerful tool for object and image classification and retrieval. However, the training stage of such networks is highly consuming in terms of storage space and time. Also, the optimization is still a challenging subject. In this paper, we propose a fast DCNN based on Fast Wavelet Transform (FWT), intelligent dropout and layer skipping. The proposed approach led to improve the image retrieval accuracy as well as the searching time. This was possible thanks to three key advantages: First, the rapid way to compute the features using FWT...
August 8, 2017: Neural Networks: the Official Journal of the International Neural Network Society
Fenghua Tian, Michael Craig Morriss, Lina Chalak, Ramgopal Venkataraman, Chul Ahn, Hanli Liu, Lakshmi Raman
Extracorporeal membrane oxygenation (ECMO) is a life-supporting therapy for critically ill patients with severe respiratory and/or cardiovascular failure. Cerebrovascular impairment can result in hemorrhagic and ischemic complications commonly seen in the patients supported on ECMO. We investigated the degree of cerebral autoregulation impairment during ECMO as well as whether it is predictive of neuroimaging abnormalities. Spontaneous fluctuations of mean arterial pressure (MAP) and cerebral tissue oxygen saturation ([Formula: see text]) were continuously measured during the ECMO run...
October 2017: Neurophotonics
Zahra Einalou, Keivan Maghooli, Seyaed Kamaledin Setarehdan, Ata Akin
Functional near-infrared spectroscopy (fNIRS) has been proposed as an affordable, fast, and robust alternative to many neuroimaging modalities yet it still has long way to go to be adapted in the clinic. One request from the clinicians has been the delivery of a simple and straightforward metric (a so-called biomarker) from the vast amount of data a multichannel fNIRS system provides. We propose a simple-straightforward signal processing algorithm derived from [Formula: see text] data collected during a modified version of the color-word matching Stroop task that consists of three different conditions...
October 2017: Neurophotonics
Hongchao Song, Yunpeng Li, Aidong Men
Microwave-based breast cancer detection has been proposed as a complementary approach to compensate for some drawbacks of existing breast cancer detection techniques. Among the existing microwave breast cancer detection methods, machine learning-type algorithms have recently become more popular. These focus on detecting the existence of breast tumours rather than performing imaging to identify the exact tumour position. A key component of the machine learning approaches is feature extraction. One of the most widely used feature extraction method is principle component analysis (PCA)...
August 24, 2017: Medical & Biological Engineering & Computing
Matthew G Siebecker, Donald L Sparks
Layered double hydroxides (LDHs) are anionic clays important in disciplines such as environmental chemistry, geochemistry, and materials science. Developments in signal processing of extended X-ray absorption fine structure (EXAFS) data, such as wavelet transformation (WT), have been used to identify transition metals and Al present in the hydroxide sheets of LDHs. The WT plots of LDHs should be distinct from those of isostructural single metal hydroxides. However, no direct comparison of these minerals appears in the literature using WT...
September 7, 2017: Journal of Physical Chemistry. A
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