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multiscale entropy

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https://www.readbyqxmd.com/read/29165084/advances-on-automatic-speech-analysis-for-early-detection-of-alzheimer-disease-a-non-linear-multi-task-approach
#1
K Lopez-de-Ipina, U Martinez-de-Lizarduy, P M Calvo, Jiri Mekyska, B Beitia, N Barroso, A Estanga, M Tainta, M Ecay-Torres
Nowadays proper detection of cognitive impairment has become a challenge for the scientific community. Alzheimer's Disease (AD), the most common cause of dementia, has a high prevalence that is increasing at a fast pace towards epidemic level. In the not-so-distant future this fact could have a dramatic social and economic impact. In this scenario, an early and accurate diagnosis of AD could help to decrease its effects on patients, relatives and society. Over the last decades there have been useful advances not only in classic assessment techniques, but also in novel non-invasive screening methodologies...
November 20, 2017: Current Alzheimer Research
https://www.readbyqxmd.com/read/29159049/pre-treatment-eeg-signal-variability-is-associated-with-treatment-success-in-depression
#2
Natalia Jaworska, Hongye Wang, Dylan M Smith, Pierre Blier, Verner Knott, Andrea B Protzner
Background: Previous work suggests that major depressive disorder (MDD) is associated with disturbances in global connectivity among brain regions, as well as local connectivity within regions. However, the relative importance of these global versus local changes for successful antidepressant treatment is unknown. We used multiscale entropy (MSE), a measure of brain signal variability, to examine how the propensity for local (fine scale MSE) versus global (coarse scale MSE) neural processing measured prior to antidepressant treatment is related to subsequent treatment response...
2018: NeuroImage: Clinical
https://www.readbyqxmd.com/read/29099846/discrimination-of-emotional-states-from-scalp-and-intracranial-eeg-using-multiscale-r%C3%A3-nyi-entropy
#3
Yelena Tonoyan, Theerasak Chanwimalueang, Danilo P Mandic, Marc M Van Hulle
A data-adaptive, multiscale version of Rényi's quadratic entropy (RQE) is introduced for emotional state discrimination from EEG recordings. The algorithm is applied to scalp EEG recordings of 30 participants watching 4 emotionally-charged video clips taken from a validated public database. Krippendorff's inter-rater statistic reveals that multiscale RQE of the mid-frontal scalp electrodes best discriminates between five emotional states. Multiscale RQE is also applied to joint scalp EEG, amygdala- and occipital pole intracranial recordings of an implanted patient watching a neutral and an emotionally charged video clip...
2017: PloS One
https://www.readbyqxmd.com/read/29098540/multiscale-persistent-functions-for-biomolecular-structure-characterization
#4
Kelin Xia, Zhiming Li, Lin Mu
In this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al...
November 2, 2017: Bulletin of Mathematical Biology
https://www.readbyqxmd.com/read/29096465/development-of-reactive-force-fields-using-ab-initio-molecular-dynamics-simulation-minimally-biased-to-experimental-data
#5
Chen Chen, Christopher Arntsen, Gregory A Voth
Incorporation of quantum mechanical electronic structure data is necessary to properly capture the physics of many chemical processes. Proton hopping in water, which involves rearrangement of chemical and hydrogen bonds, is one such example of an inherently quantum mechanical process. Standard ab initio molecular dynamics (AIMD) methods, however, do not yet accurately predict the structure of water and are therefore less than optimal for developing force fields. We have instead utilized a recently developed method which minimally biases AIMD simulations to match limited experimental data to develop novel multiscale reactive molecular dynamics (MS-RMD) force fields by using relative entropy minimization...
October 28, 2017: Journal of Chemical Physics
https://www.readbyqxmd.com/read/29091053/multiscale-network-representation-of-physiological-time-series-for-early-prediction-of-sepsis
#6
Supreeth Prajwal Shashikumar, Qiao Li, Gari D Clifford, Shamim Nemati
Sepsis, a dysregulated immune-mediated host response to infection, is the leading cause of morbidity and mortality in critically ill patients. Indices of heart rate variability and complexity (such as entropy) have been proposed as surrogate markers of Neuro-immune system dysregulation with diseases such as sepsis. However, these indices only provide an average, one dimensional description of complex neuro-physiological interactions. We propose a novel multiscale network construction and analysis method for multivariate physiological time series, and demonstrate its utility for early prediction of sepsis...
November 1, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/29060576/complexity-analysis-of-resting-state-fmri-signals-in-depressive-patients
#7
Pei-Shan Ho, Chemin Lin, Guan-Yen Chen, Ho-Ling Liu, Chih-Mao Huang, Tatia Mei-Chun Lee, Shwu-Hua Lee, Shun-Chi Wu
Analysis of brain signal complexity reveals the intrinsic network dynamics and is widely utilized in the investigation of mechanisms in mental disorders. In this study, the complexity of resting-state functional magnetic resonance imaging (fMRI) signals was explored in patients with depression using multiscale entropy (MSE). Thirty-five patients diagnosed with depression and 22 age- and gender-matched healthy controls were considered. The MSE profiles in five brain networks of the two participant groups were evaluated and analyzed...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29060574/multiscale-dispersion-entropy-for-the-regional-analysis-of-resting-state-magnetoencephalogram-complexity-in-alzheimer-s-disease
#8
Hamed Azami, Eli Kinney-Lang, Ahmed Ebied, Alberto Fernandez, Javier Escudero
Alzheimer's disease (AD) is a progressive and irreversible brain disorder of the nervous system affecting memory, thinking, and emotion. It is the most important cause of dementia and an influential social problem in all the world. The complexity of brain recordings has been successfully used to help to characterize AD. We have recently introduced multiscale dispersion entropy (MDE) as a very fast and powerful tool to quantify the complexity of signals. The aim of this study is to assess the ability of MDE, in comparison with multiscale permutation entropy (MPE) and multiscale entropy (MSE), to discriminate 36 AD patients from 26 elderly age-matched control subjects using resting-state magnetoencephalogram (MEG) recordings...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29060562/multiscale-sample-entropy-of-heart-rate-and-blood-pressure-methodological-aspects
#9
Paolo Castiglioni, Lorenzo Brambilla, Matteo Bini, Paolo Coruzzi, Andrea Faini
The entropy of heart rate variability is one of the main features characterizing the complexity of the cardiovascular system. In order to take into account the multiscale nature of cardiovascular regulation, it was proposed to evaluate entropy with a multiscale approach, based on the estimation of Sample Entropy on progressively coarse-grained series (Multiscale Sample Entropy, MSE). Aim of this work is to investigate two methodological aspects related to MSE of cardiovascular signals. The first aspect regards the tolerance below which a couple of points are considered similar in a given embedding dimension, in particular how the way the tolerance is set at each level of coarse graining influences the MSE estimates...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29058215/entropy-for-the-complexity-of-physiological-signal-dynamics
#10
Xiaohua Douglas Zhang
Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system...
2017: Advances in Experimental Medicine and Biology
https://www.readbyqxmd.com/read/29041318/composite-multiscale-entropy-analysis-of-reflective-terahertz-signals-for-biological-tissues
#11
Rui Zhang, Yuezhi He, Kai Liu, Liangliang Zhang, Shijing Zhang, Emma Pickwell-MacPherson, Yuejin Zhao, Cunlin Zhang
We demonstrate a composite multiscale entropy (CMSE) method of terahertz (THz) signal complexity analysis to distinguish different biological tissues. The THz signals reflected from fresh porcine skin and muscle tissues were measured and analyzed. The statistically significant difference and separation of the two tissues based on several parameters were analyzed and compared for THz spectroscopy and imaging, which verified the better performance of the CMSE method and further enhancement of the contrast among THz signals that interact with different tissues...
October 2, 2017: Optics Express
https://www.readbyqxmd.com/read/29035207/novel-quantitative-analytical-approaches-for-rotor-identification-and-associated-implications-for-mapping
#12
Elizabeth M Annoni, Shivaram Poigai Arunachalam, Suraj Kapa, Siva K Mulpuru, Paul A Friedman, Elena G Talkachova
OBJECTIVE: Clinical studies identifying rotors confirming these sites for ablation in treating cardiac arrhythmias have had inconsistent results with the current analysis techniques available. The aim of this study is to evaluate four new signal analysis approaches - multiscale frequency (MSF), Shannon entropy (SE), Kurtosis (Kt), and multiscale entropy (MSE) - in their ability to identify the pivot point of rotors. METHODS: Optical mapping movies of ventricular tachycardia were used to evaluate the performance and robustness of SE, Kt, MSF and MSE techniques with respect to several clinical limitations: decreased time duration, reduced spatial resolution, and the presence of meandering rotors...
October 16, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/29031213/impairment-of-heart-rhythm-complexity-in-patients-with-drug-resistant-epilepsy-an-assessment-with-multiscale-entropy-analysis
#13
Hongyun Liu, Zhao Yang, Fangang Meng, Yuguang Guan, Yanshan Ma, Shuli Liang, Jiuluan Lin, Longsheng Pan, Mingming Zhao, Wei Qu, Hongwei Hao, Guoming Luan, Jianguo Zhang, Luming Li
OBJECTIVE: Epilepsy and seizures can have dramatic effects on the cardiac function. The aim of this study was to investigate the heart rhythm complexity in patients with drug-resistant epilepsy (DRE). METHODS: Ambulatory 24-h electrocardiograms (ECG) from 70 DRE patients and 50 healthy control subjects were analyzed using conventional heart rate variability (HRV) and multiscale entropy (MSE) methods The variation of complexity indices (CI), which was calculated from MSE profile, was determined...
October 5, 2017: Epilepsy Research
https://www.readbyqxmd.com/read/28991754/temporal-analysis-of-cardiovascular-and-respiratory-complexity-by-multiscale-entropy-based-on-symbolic-dynamics
#14
Sina Reulecke, Sonia Charleston Villalobos, Andreas Voss, Ramon Gonzalez-Camarena, Jesus Antonio Gonzalez-Hermosillo, Jatziri Gaitan, Guadalupe Hernandez-Pacheco, Rico Schroeder, Tomas Aljama-Corrales
The effect of an orthostatic stress on cardiovascular and respiratory complexity was investigated to detect impaired autonomic regulation in patients with vasovagal syncope (VVS). Sixteen female patients and 12 age-matched healthy female subjects were enrolled in a passive 70° head-up tilt test. Also, 12 age-matched healthy male subjects were enrolled to study gender differences. Analysis was performed dynamically using various short-term (5 min) windows shifted by 1 min as well as by 20 min of orthostatic phase (OP) to evaluate local and global complexity...
October 9, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28983489/study-of-memory-deficit-in-alzheimer-s-disease-by-means-of-complexity-analysis-of-fnirs-signal
#15
David Perpetuini, Roberta Bucco, Michele Zito, Arcangelo Merla
Working memory deficit is a signature of Alzheimer's disease (AD). The free and cued selective reminding test (FCSRT) is a clinical test that quantifies memory deficit for AD diagnosis. However, the diagnostic accuracy of FCSRT may be increased by accompanying it with neuroimaging. Since the test requires doctor-patient interaction, brain monitoring is challenging. Functional near-infrared spectroscopy (fNIRS) could be suited for such a purpose because of the fNIRS flexibility. We investigated whether the complexity, based on sample entropy and multiscale entropy metrics, of the fNIRS signal during FCSRT was correlated with memory deficit in early AD...
January 2018: Neurophotonics
https://www.readbyqxmd.com/read/28964147/assessing-multiscale-complexity-of-short-heart-rate-variability-series-through-a-model-based-linear-approach
#16
Alberto Porta, Vlasta Bari, Giovanni Ranuzzi, Beatrice De Maria, Giuseppe Baselli
We propose a multiscale complexity (MSC) method assessing irregularity in assigned frequency bands and being appropriate for analyzing the short time series. It is grounded on the identification of the coefficients of an autoregressive model, on the computation of the mean position of the poles generating the components of the power spectral density in an assigned frequency band, and on the assessment of its distance from the unit circle in the complex plane. The MSC method was tested on simulations and applied to the short heart period (HP) variability series recorded during graded head-up tilt in 17 subjects (age from 21 to 54 years, median = 28 years, 7 females) and during paced breathing protocols in 19 subjects (age from 27 to 35 years, median = 31 years, 11 females) to assess the contribution of time scales typical of the cardiac autonomic control, namely in low frequency (LF, from 0...
September 2017: Chaos
https://www.readbyqxmd.com/read/28877180/decreased-complexity-of-glucose-dynamics-preceding-the-onset-of-diabetes-in-mice-and-rats
#17
Xiaohua Douglas Zhang, David Pechter, Liming Yang, Xiaoli Ping, Zuliang Yao, Rumin Zhang, Xiaolan Shen, Nina Xiaoyan Li, Jonathan Connick, Andrea R Nawrocki, Manu Chakravarthy, Cai Li
Continuous glucose monitoring (CGM) is a platform to measure blood glucose (BG) levels continuously in real time with high enough resolution to document their underlying fluctuations. Multiscale entropy (MSE) analysis has been proposed as a measure of time-series complexity, and when applied to clinical CGM data, MSE analysis revealed that diabetic patients have lower MSE complexity in their BG time series than healthy subjects. To determine if the clinical observations on complexity of glucose dynamics can be back-translated to relevant preclinical species used routinely in diabetes drug discovery, we performed CGM in both mouse (ob/ob) and rat (Zucker Diabetic Fatty, ZDF) models of diabetes...
2017: PloS One
https://www.readbyqxmd.com/read/28845049/reactive-molecular-dynamics-models-from-ab-initio-molecular-dynamics-data-using-relative-entropy-minimization
#18
Christopher Arntsen, Chen Chen, Gregory A Voth
We present two new multiscale molecular dynamics (MS-RMD) models for the hydrated excess proton in water developed directly from ab initio molecular dynamics (AIMD) simulation data of the same system. The potential of mean force along the proton transfer reaction coordinate and radial distribution functions for the MS-RMD models are shown faithfully reproduce those of AIMD. The models are developed using an algorithm based on relative entropy minimization, thus demonstrating the ability of the method to rapidly generate accurate and highly efficient reactive MD force fields...
September 1, 2017: Chemical Physics Letters
https://www.readbyqxmd.com/read/28839247/spatiotemporal-changes-in-regularity-of-gamma-oscillations-contribute-to-focal-ictogenesis
#19
Yosuke Sato, Simeon M Wong, Yasushi Iimura, Ayako Ochi, Sam M Doesburg, Hiroshi Otsubo
In focal ictogenesis, gamma oscillations (30-70 Hz) recorded by electroencephalography (EEG) are related to the epileptiform synchronization of interneurons that links the seizure onset zone (SOZ) to the surrounding epileptogenic zone. We hypothesized that the synchronization of interneurons could be detected as changes in the regularity of gamma oscillation rhythmicity. We used multiscale entropy (MSE) analysis, which can quantify the regularity of EEG rhythmicity, to investigate how the regularity of gamma oscillations changes over the course of a seizure event...
August 24, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28782680/bilinguals-have-more-complex-eeg-brain-signals-in-occipital-regions-than-monolinguals
#20
John G Grundy, John A E Anderson, Ellen Bialystok
Brain signal complexity increases with development and is associated with better cognitive outcomes in older age. Research has also shown that bilinguals are able to stave off cognitive decline for longer periods of time than monolinguals, but no studies to date have examined whether bilinguals have more complex brain signals than monolinguals. Here we explored the hypothesis that bilingualism leads to greater brain signal complexity by examining multiscale entropy (MSE) in monolingual and bilingual young adults while EEG was recorded during a task-switching paradigm...
October 1, 2017: NeuroImage
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