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multiscale entropy

Yinghuang Yin, Kehui Sun, Shaobo He
There is considerable interest in analyzing the complexity of electroencephalography (EEG) signals. However, some traditional complexity measure algorithms only quantify the complexities of signals, but cannot discriminate different signals very well. To analyze the complexity of epileptic EEG signals better, a new multiscale permutation Rényi entropy (MPEr) algorithm is proposed. In this algorithm, the coarse-grained procedure is introduced by using weighting-averaging method, and the weighted factors are determined by analyzing nonlinear signals...
2018: PloS One
Md Mosheyur Rahman, Mohammed Imamul Hassan Bhuiyan, Ahnaf Rashik Hassan
Sleep stage classification is an important task for the timely diagnosis of sleep disorders and sleep-related studies. In this paper, automatic scoring of sleep stages using Electrooculogram (EOG) is presented. Single channel EOG signals are analyzed in Discrete Wavelet Transform (DWT) domain employing various statistical features such as Spectral Entropy, Moment-based Measures, Refined Composite Multiscale Dispersion Entropy (RCMDE) and Autoregressive (AR) Model Coefficients. The discriminating ability of the features is studied using the One Way Analysis of Variance (ANOVA) and box plots...
August 22, 2018: Computers in Biology and Medicine
Chiaki Hasegawa, Tetsuya Takahashi, Yuko Yoshimura, Sou Nobukawa, Takashi Ikeda, Daisuke N Saito, Hirokazu Kumazaki, Yoshio Minabe, Mitsuru Kikuchi
The infant brain shows rapid neural network development that considerably influences cognitive and behavioral abilities in later life. Reportedly, this neural development process can be indexed by estimating neural signal complexity. However, the precise developmental trajectory of brain signal complexity during infancy remains elusive. This study was conducted to ascertain the trajectory of magnetoencephalography (MEG) signal complexity from 2 months to 3 years of age in five infants using multiscale entropy (MSE), which captures signal complexity at multiple temporal scales...
2018: Frontiers in Neuroscience
Agata Wawrzkiewicz-Jałowiecka, Paulina Trybek, Łukasz Machura, Beata Dworakowska, Zbigniew J Grzywna
BK channels are potassium selective and exhibit large single-channel conductance. They play an important physiological role in glioma cells: they are involved in cell growth and extensive migrating behavior. Due to the fact that these processes are accompanied by changes in membrane stress, here, we examine mechanosensitive properties of BK channels from human glioblastoma cells (gBK channels). Experiments were performed by the use of patch-clamp method on excised patches under membrane suction (0-40 mmHg) at membrane hyper- and depolarization...
August 9, 2018: Journal of Membrane Biology
Chih-Hao Chen, Sung-Chun Tang, Ding-Yuan Lee, Jiann-Shing Shieh, Dar-Ming Lai, An-Yu Wu, Jiann-Shing Jeng
Acute stroke commonly affects cardiac autonomic responses resulting in reduced heart rate variability (HRV). Multiscale entropy (MSE) is a novel non-linear method to quantify the complexity of HRV. This study investigated the influence of intracerebral hemorrhage (ICH) locations and intraventricular hemorrhage (IVH) on the complexity of HRV. We recruited 93 supratentorial ICH patients (male 59%, mean age 61 years), and the locations of ICH included basal ganglia (n = 40), thalamus (n = 35), and lobar (n = 18) group...
July 31, 2018: Scientific Reports
Everton Falcão de Oliveira, Eunice Aparecida Bianchi Galati, Alessandra Gutierrez de Oliveira, Elizabeth Ferreira Rangel, Bruno Moreira de Carvalho
In some transmission foci of Leishmania infantum in Brazil, Lutzomyia cruzi could be considered the main vector of this pathogen. In addition, L. cruzi is a permissive vector of L. amazonensis. Its geographical distribution seems to be restricted and limited to Cerrado and Pantanal biomes, which includes some areas in Brazil and Bolivia. Considering that predicting the distribution of the species involved in transmission cycles is an effective approach for assessing human disease risk, this study aims to predict the spatial distribution of L...
July 2018: PLoS Neglected Tropical Diseases
Soheil Keshmiri, Hidenobu Sumioka, Junya Nakanishi, Hiroshi Ishiguro
We present the results of the analysis of the effect of a bodily-contact communication medium on the brain activity of the individuals during verbal communication. Our results suggest that the communicated content that is mediated through such a device induces a significant effect on electroencephalogram (EEG) time series of human subjects. Precisely, we find a significant reduction of overall power of the EEG signals of the individuals. This observation that is supported by the analysis of the permutation entropy (PE) of the EEG time series of brain activity of the participants suggests the positive effect of such a medium on the stress relief and the induced sense of relaxation...
2018: Frontiers in Psychology
Oliver K Ernst, Thomas Bartol, Terrence Sejnowski, Eric Mjolsness
Finding reduced models of spatially distributed chemical reaction networks requires an estimation of which effective dynamics are relevant. We propose a machine learning approach to this coarse graining problem, where a maximum entropy approximation is constructed that evolves slowly in time. The dynamical model governing the approximation is expressed as a functional, allowing a general treatment of spatial interactions. In contrast to typical machine learning approaches which estimate the interaction parameters of a graphical model, we derive Boltzmann-machine like learning algorithms to estimate directly the functionals dictating the time evolution of these parameters...
July 21, 2018: Journal of Chemical Physics
Maria Cristina Bisi, Paola Tamburini, Giulia Pacini Panebianco, Rita Stagni
When aiming at assessing motor control development, natural walking (NW) and tandem walking (TW) are two locomotor tasks that allow analysing different characteristics of motor control performance. NW is the reference locomotor task, expected to become more and more automatic with age. TW is a non-paradigmatic task used in clinics to highlight eventual impairments and to evaluate how a child deals with a new challenging motor experience. This work aims at investigating motor development in school-aged children, by assessing quantitatively their performance during TW and NW...
July 20, 2018: Journal of Biomechanical Engineering
Alexey Brazhe
New spatial entropy and complexity measures for two-dimensional patterns are proposed. The approach is based on the notion of disequilibrium and is built on statistics of directional multiscale coefficients of the fast finite shearlet transform. Shannon entropy and Jensen-Shannon divergence measures are employed. Both local and global spatial complexity and entropy estimates can be obtained, thus allowing for spatial mapping of complexity in inhomogeneous patterns. The algorithm is validated in numerical experiments with a gradually decaying periodic pattern and Ising surfaces near critical state...
June 2018: Physical Review. E
Suliang Chen, Mathew J Gallagher, Marios C Papadopoulos, Samira Saadoun
The injured spinal cord is a complex system influenced by many local and systemic factors that interact over many timescales. To help guide clinical management, we developed a technique that monitors intraspinal pressure from the injury site in patients with acute, severe traumatic spinal cord injuries. Here, we hypothesize that spinal cord injury alters the complex dynamics of the intraspinal pressure signal quantified by computing hourly the detrended fluctuation exponent alpha, multiscale entropy, and maximal Lyapunov exponent lambda...
2018: Frontiers in Neurology
Zhenxi Song, Bin Deng, Jiang Wang, Ruofan Wang
OBJECTIVE: This paper aims to explore affordable biomarkers of Alzheimer's disease (AD) based on noninvasive, low-cost and portability electroencephalography (EEG) signals. METHODS: By combining multiscale analysis and embedding space theory, a novel strategy was developed for constructing brain functional network inferred from generalized composite multiscale entropy vector (GCMSEV). Functional network analysis and seed analysis were used for comparing AD pattern vs...
May 9, 2018: IEEE Transactions on Bio-medical Engineering
H Piitulainen, T Rantalainen, J P Kulmala, H Mäenpää
Children with cerebral palsy (CP) have gait impairments, and their gait is affected by concurrent tasks. We used inertial measurement units (IMU) to quantify CP-related gait complexity alterations, and identify effects of dual tasks on gait variability from 12 children with CP and 23 typically developed (TD) controls. The data were collected for normal and dual-tasks (motor; carrying a tray, cognitive; word naming) during walking. Step duration and adjusted multiscale entropy (MSE) index were computed. In overall, children with CP had shorter step duration and greater gait complexity than TD...
July 3, 2018: Gait & Posture
Anne Humeau-Heurtier, Ana Carolina Mieko Omoto, Luiz E V Silva
The multiscale entropy (MSE1D ) measure is now widely used to quantify the complexity of time series. The development of complexity measures for images is also a long-standing goal. Recently, the bi-dimensional version of MSE1D has been proposed (MSE2D ) to analyze images. The interpretation of MSE2D curves and the applications to real data are still emergent. Because the coarse-graining step in the MSE2D computation changes the frequency content of the image, we hypothesized a possible dependence between MSE2D and the discrete Fourier transform (DFT)...
September 1, 2018: Computers in Biology and Medicine
Albert C Yang, Shih-Jen Tsai, Ching-Po Lin, Chung-Kang Peng
Complexity analysis of resting-state blood oxygen level-dependent (BOLD) signals using entropy methods has attracted considerable attention. However, investigation on the bias of entropy estimates in resting-state functional magnetic resonance imaging (fMRI) signals and a general strategy for selecting entropy parameters is lacking. In this paper, we present a minimizing error approach to reduce the bias of sample entropy (SampEn) and multiscale entropy (MSE) in resting-state fMRI data. The strategy explored a range of parameters that minimized the relative error of SampEn of BOLD signals in cerebrospinal fluids where minimal physiologic information was present, and applied these parameters to calculate SampEn of BOLD signals in gray matter regions...
2018: Frontiers in Neuroscience
Hongye Wang, Penny M Pexman, Gary Turner, Filomeno Cortese, Andrea B Protzner
Recent empirical work suggests that the dynamics of brain function, as measured by brain signal variability, differs between younger and older adults. We extended this work by examining how the relationship between brain signal variability and age is altered in the context of expertise. We recorded electroencephalography from Scrabble experts and controls during a visual word recognition task. To measure variability, we used multiscale entropy, which emphasizes the way brain signals behave over a range of timescales and can differentiate the variability of a complex system (the brain) from a purely random system...
September 2018: Neurobiology of Aging
David Rodbard
Glycemic variability (GV) is a major consideration when evaluating quality of glycemic control. GV increases progressively from prediabetes through advanced T2D and is still higher in T1D. GV is correlated with risk of hypoglycemia. The most popular metrics for GV are the %Coefficient of Variation (%CV) and standard deviation (SD). The %CV is correlated with risk of hypoglycemia. Graphical display of glucose by date, time of day, and day of the week, and display of simplified glucose distributions showing % of time in several ranges, provide clinically useful indicators of GV...
June 2018: Diabetes Technology & Therapeutics
Yong Lv, Rui Yuan, Tao Wang, Hewenxuan Li, Gangbing Song
Rolling bearings play a crucial role in rotary machinery systems, and their operating state affects the entire mechanical system. In most cases, the fault of a rolling bearing can only be identified when it has developed to a certain degree. At that moment, there is already not much time for maintenance, and could cause serious damage to the entire mechanical system. This paper proposes a novel approach to health degradation monitoring and early fault diagnosis of rolling bearings based on a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and improved multivariate multiscale sample entropy (MMSE)...
June 14, 2018: Materials
Guangjun Wang, Shuyong Jia, Hongyan Li, Ze Wang, Weibo Zhang
To investigate the relationship between local blood flux and heart rate variability following different thermal stimulations, healthy subjects were recruited and subject to different thermal stimulations on the right forearm. Multiscale entropy and multiscale fuzzy entropy were used to measure the complexity of the local blood flux, and the approximate entropy was calculated to evaluate the HRV complexity. The results indicated that thermal stimulation significantly increased local blood flux and that different temperature stimulations resulted in different complexities in local blood flux...
June 12, 2018: Scientific Reports
J P Chiverton, A Kao, M Roldo, G Tozzi
Fibrous nanomaterials such as electrospun materials have many uses ranging from tissue engineering to biosensors. High-resolution imaging is an important component in the characterization of these materials. Important parameters required to predict and study the properties of fibre rich materials include diameter and orientation distribution as well as fibre spacing. The orientations and the relative dimensions of the fibres can be measured via specially designed imaging software. Difficulties in this measurement process can arise if fibres are distributed in close proximity to each other in relation to the resolution of the imaging modality...
June 6, 2018: Journal of Microscopy
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