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multiscale entropy

Daniela V Vaz, Bruna S Avelar, Renan A Resende
Attentional focus affects performance and learning of motor tasks. An external attentional focus (on the effects of movement) can lead to more efficient and effective movements compared to an internal focus (on body movement itself). According to the "constrained action hypothesis", an external focus facilitates fast and reflexive movement control while an internal focus leads to disruption of automatic coordination processes. Such disruption should be apparent in the complexity of movement. In this study, multiscale entropy measures were used to investigate if the external focus is related to superior coordination complexity compared to internal focus...
February 6, 2019: Human Movement Science
Richard Raubertas, Jeremy Beech, Wendy Watson, Steven Fox, Scott Tiesma, David B Gilberto, Ashleigh Bone, Patricia A Rebbeck, Liza T Gantert, Stacey Conarello, Walter Knapp, Tasha Gray, Larry Handt, Cai Li
Until recently, preclinical and clinical work on diabetes has focused on the understanding of blood glucose elevation and its detrimental metabolic sequelae. The advent of continuous glucose monitoring (CGM) technology now allows real time monitoring of blood glucose levels as a time series, and thus the exploration of glucose dynamics at short time scales. Previous work has shown decreases in the complexity of glucose dynamics, as measured by multiscale entropy (MSE) analysis, in diabetes in humans, mice, and rats...
February 5, 2019: Scientific Reports
Alexander J Pak, Thomas Dannenhoffer-Lafage, Jesper J Madsen, Gregory A Voth
Despite the central role of lipids in many biophysical functions, the molecular mechanisms that dictate macroscopic lipid behavior remain elusive to both experimental and computational approaches. As such, there has been much interest in the development of low-resolution, implicit-solvent coarse-grained (CG) models to dynamically simulate biologically-relevant spatiotemporal scales with molecular fidelity. However, in the absence of solvent, a key challenge for CG models is to faithfully emulate solvent-mediated forces, which include both hydrophilic and hydrophobic interactions that drive lipid aggregation and self-assembly...
January 31, 2019: Journal of Chemical Theory and Computation
Felipe B Santinelli, Fabio A Barbieri, Carina F Pinheiro, Avelino C Amado, Emerson Sebastião, Richard E A van Emmerik
This study investigated changes in postural control complexity in people with multiple sclerosis (PwMS) before and after a fatigue protocol. Thirteen minimally affected PwMS (1.53 ± 1.03- Expanded Disability Status Scale) and 12 non-MS controls. Postural test included quiet stance on a force platform under two visual conditions (saccades and fixation) before and after a fatigue protocol. Postural complexity was assessed through the multiscale entropy. A three-way ANOVA showed a main effect of fatigue in the medial-lateral direction (p <0...
January 28, 2019: Journal of Motor Behavior
Yumeng Li, Melissa A Mache, Teri A Todd
The purpose of this study was to compare the complexity of postural control between children with autism spectrum disorder (ASD) and typical developing children during altered visual and somatosensory conditions using the multiscale entropy. Eleven children with ASD and 11 typical developing children were tested during quiet standing under four conditions: (1) eyes open and standing on a stable surface; (2) eyes open and standing on a compliant surface; (3) eyes closed and standing on a stable surface and (4) eyes closed and standing on a compliant surface...
January 24, 2019: Journal of Applied Biomechanics
Stephen M Glass, Christopher K Rhea, Randy J Schmitz, Scott E Ross
CONTEXT: Movement screening has become increasingly popular among tactical professionals. This popularity has motivated the design of interventions that cater to improving outcomes on the screens themselves, which are often scored in reference to an objective norm. In contrast to the assumptions underlying this approach, dynamical systems theory suggests that movements arise as a function of continuously evolving constraints and that optimal movement strategies may not exist. To date, few data address behavioral complexity in the fundamental movement tasks commonly used in clinical screenings...
January 18, 2019: Journal of Athletic Training
Yali Zhang, Pengjian Shang
The complexity of financial time series is an important issue for nonlinear dynamic systems. We propose multiscale power spectral entropy. Based on this method, this paper uses the complex entropy causal plane ( <mml:math xmlns:mml=""> <mml:msub> <mml:mi>C</mml:mi> <mml:mrow> <mml:mi>p</mml:mi> <mml:mi>s</mml:mi> <mml:mi>e</mml:mi> </mml:mrow> </mml:msub> </mml:math> ) to evaluate the complexity of the stock market...
December 2018: Chaos
Mikito Ogino, Yasue Mitsukura
Drowsiness detection has been studied in the context of evaluating products, assessing driver alertness, and managing office environments. Drowsiness level can be readily detected through measurement of human brain activity. The electroencephalogram (EEG), a device whose application relies on adhering electrodes to the scalp, is the primary method used to monitor brain activity. The many electrodes and wires required to perform an EEG place considerable constraints on the movement of users, and the cost of the device limits its availability...
December 18, 2018: Sensors
Chia-Hsuan Lee, Tien-Lung Sun
BACKGROUND: Previous research on balance mostly focused on the assessment, training, and improvements of balance through interventions. We investigated tools commonly used to study static balance. Differences in postural stability were analyzed using multiscale entropy (MSE) and feature analysis. METHODS: A force plate and inertial sensor were used to collect acceleration and center-of-pressure (COP) nonlinear signals. MSE was also used to detect fractal correlations and assess the complexity of univariate data complexity...
December 13, 2018: Journal of Physiological Anthropology
Sou Nobukawa, Mitsuru Kikuchi, Tetsuya Takahashi
The dynamics of the human brain network has attracted broad attention, in recognition of the concept that functional connectivity is not static, but changes its pattern over time, even in the resting state. We hypothesized that analysis of continuously captured time-varying instantaneous phase synchronization between signals from different brain regions might add another dimension to already identified network dynamics. To validate this hypothesis as an aid to elucidating the physiological mechanisms of aging, we examined time-series of instantaneous phase synchronization events in resting-state EEG activity across the brain, in healthy younger and healthy older subjects...
December 7, 2018: NeuroImage
Intan Low, Po-Chih Kuo, Cheng-Lin Tsai, Yu-Hsiang Liu, Ming-Wei Lin, Hsiang-Tai Chao, Yong-Sheng Chen, Jen-Chuen Hsieh, Li-Fen Chen
The irregularity and uncertainty of neurophysiologic signals across different time scales can be regarded as neural complexity, which is related to the adaptability of the nervous system and the information processing between neurons. We recently reported general loss of brain complexity, as measured by multiscale sample entropy (MSE), at pain-related regions in females with primary dysmenorrhea (PDM). However, it is unclear whether this loss of brain complexity is associated with inter-subject genetic variations...
2018: Frontiers in Neuroscience
M C Bisi, P Tamburini, R Stagni
BACKGROUND: When aiming at studying and monitoring locomotor development in childhood, innovative indexes for the characterization of motor control performance and wearable technologies have highlighted the potential of significant advances. In particular, quantitative assessment of motor performance during natural walking (NW) and tandem walking (TW) has been proposed to highlight manifestations of motor automaticity and complexity, respectively. RESEARCH QUESTION: This work aims at providing a quantitative overview of metrics characterizing locomotor maturation in a typically developing population, by analysing NW and TW...
November 29, 2018: Gait & Posture
Xiaogeng Wan, Lanxi Xu
As the big data science develops, efficient methods are demanded for various data analysis. Granger causality provides the prime model for quantifying causal interactions. However, this theoretic model does not meet the requirement for real-world data analysis, because real-world time series are diverse whose models are usually unknown. Therefore, model-free measures such as information transfer measures are strongly desired. Here, we propose the multi-scale extension of conditional mutual information measures using MORLET wavelet, which are named the WM and WPM...
2018: PloS One
Fengzhen Hou, Zhinan Yu, Chung-Kang Peng, Albert Yang, Chunyong Wu, Yan Ma
Sleep electroencephalography (EEG) provides an opportunity to study sleep scientifically, whose chaotic, dynamic, complex, and dissipative nature implies that non-linear approaches could uncover some mechanism of sleep. Based on well-established complexity theories, one hypothesis in sleep medicine is that lower complexity of brain waves at pre-sleep state can facilitate sleep initiation and further improve sleep quality. However, this has never been studied with solid data. In this study, EEG collected from healthy subjects was used to investigate the association between pre-sleep EEG complexity and sleep quality...
2018: Frontiers in Neuroscience
Tuhin Paul, Kevin G Stanley, Nathaniel D Osgood
Accurate prediction of the motion of objects is a central scientific goal. For deterministic or stochastic processes, models exist which characterize motion with a high degree of reliability. For complex systems, or those where objects have a degree of agency, characterizing motion is far more challenging. The information entropy rate of motion through a discrete space can place a limit on the predictability of even the most complex or history-dependent actor, but the variability in measured encountered locations is inexorably tied to the spatial and temporal resolutions of those measurements...
October 2018: Royal Society Open Science
Wei Wang, Xiyuan Chen
Temperature drift is a major error source of the fiber optic gyroscope (FOG), and the method of modeling is important in eliminating it. A method of multiscale modeling based on improved ensemble empirical mode decomposition (EEMD) is proposed in this paper. First, in order to improve the ability of eliminating mode mixing, the influence of the frequency of the masking signal on mode mixing is analyzed. Then we conclude that the frequency of the masking signal should be higher than that of the signal, and an improved EEMD is proposed based on the conclusion...
October 1, 2018: Applied Optics
Alberto Porta, Beatrice De Maria, Beatrice Cairo, Emanuele Vaini, Vlasta Bari
The study compares a recently proposed shortterm model-based linear multiscale complexity approach to a single-scale application of the same method and to a model-free nonlinear one based on the computation of conditional entropy with the aim at assessing the complementary information. Comparison was carried out over 24 hours Holter recordings of heart period variability during daytime and nighttime in 12 healthy men (age: 34-55 years). Single-scale methods were able to detect the increased complexity of the cardiac control during nighttime...
July 2018: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Hengbing Wang, Haoran Ren, Xinyu Jiang, Yirui Sun, Zeyu Wang, Wei Chen
Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive functional brain imaging technique, through detecting the changes of hemoglobin concentrations to investigate brain activities in various tasks. The aim of this study is to investigate the complexity of near-infrared spectroscopy signals during resting state and upper limb movements. Experimental study was designed by applying NIRS to collect the data especially for both healthy subjects and traumatic brain injury (TBI) patients. The modified multiscale entropy (MMSE) algorithm was employed to assess the complexity of fNIRS signals which may reflect the changes of brain activity when people underwent brain injury...
July 2018: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Khoa D Nguyen, Pubudu N Pathirana, Malcolm Horne, Laura Power, David Szmulewicz
The aim of this study is to investigate the validity of an entropy-based objective assessment of cerebellar ataxia patients performing rhythmic tapping. Previous research conducted, particularly in time and frequency domains, tested the adherence of patients to more stringent experimental requirements. These requirements may inadvertently cause higher level brain functions to influence the performance and possibly obscure the cerebella related disabilities in the data stream. In this study, a multiscale entropy-based learning process that overcomes this practical limitation was considered...
July 2018: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Brandon M Hager, Albert C Yang, Jennifer N Gutsell
Background: EEG mu-desynchronization is an index of motor resonance (MR) and is used to study social interaction deficiencies, but finding differences in mu-desynchronization does not reveal how nonlinear brain dynamics are affected during MR. The current study explores how nonlinear brain dynamics change during MR. We hypothesized that the complexity of the mu frequency band (8-13 Hz) changes during MR, and that this change would be frequency specific. Additionally, we sought to determine whether complexity at baseline and changes in complexity during action observation would predict MR and changes in network dynamics...
2018: Frontiers in Neuroscience
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