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1.
J Vis ; 19(14): 14, 2019 12 02.
Artigo em Inglês | MEDLINE | ID: mdl-31845974

RESUMO

The response latency of steady-state visually evoked potentials (SSVEPs) is a sensitive measurement for investigating visual functioning of the human brain, specifically in visual development and for clinical evaluation. This latency can be measured from the slope of phase versus frequency of responses by using multiple frequencies of stimuli. In an attempt to provide an alternative measurement of this latency, this study utilized an envelope response of SSVEPs elicited by amplitude-modulated visual stimulation and then compared with the envelope of the generating signal, which was recorded simultaneously with the electroencephalography recordings. The advantage of this measurement is that it successfully estimates the response latency based on the physiological envelope in the entire waveform. Results showed the response latency at the occipital lobe (Oz channel) was approximately 104.55 ms for binocular stimulation, 97.14 ms for the dominant eye, and 104.75 ms for the nondominant eye with no significant difference between these stimulations. Importantly, the response latency at frontal channels (125.84 ms) was significantly longer than that at occipital channels (104.11 ms) during binocular stimulation. Together with strong activation of the source envelope at occipital cortex, these findings support the idea of a feedforward process, with the visual stimuli propagating originally from occipital cortex to anterior cortex. In sum, these findings offer a novel method for future studies in measuring visual response latencies and also potentially shed a new light on understanding of how long collective neural activities take to travel in the human brain.

2.
Sci Rep ; 9(1): 16919, 2019 Nov 15.
Artigo em Inglês | MEDLINE | ID: mdl-31729410

RESUMO

Natural sensory signals have nonlinear structures dynamically composed of the carrier frequencies and the variation of the amplitude (i.e., envelope). How the human brain processes the envelope information is still poorly understood, largely due to the conventional analysis failing to quantify it directly. Here, we used a recently developed method, Holo-Hilbert spectral analysis, and steady-state visually evoked potential collected using electroencephalography (EEG) recordings to investigate how the human visual system processes the envelope of amplitude-modulated signals, in this case with a 14 Hz carrier and a 2 Hz envelope. The EEG results demonstrated that in addition to the fundamental stimulus frequencies, 4 Hz amplitude modulation residing in 14 Hz carrier and a broad range of carrier frequencies covering from 8 to 32 Hz modulated by 2 Hz amplitude modulation are also found in the two-dimensional frequency spectrum, which have not yet been recognized before. The envelope of the stimulus is also found to dominantly modulate the response to the incoming signal. The findings thus reveal that the electrophysiological response to amplitude-modulated stimuli is more complex than could be revealed by, for example, Fourier analysis. This highlights the dynamics of neural processes in the visual system.

3.
Data Brief ; 23: 103727, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-31372394

RESUMO

Data presented are related to the research article entitled "Using Holo-Hilbert spectral analysis to quantify the modulation of Dansgaard-Oeschger events by obliquity" (J. Deng et al., 2018). The datasets in Deng et al. (2018) are analyzed on the foundation of ensemble empirical mode decomposition (EEMD) (Z.H. Wu and N.E. Huang, 2009), and reveal more occurrences of Dansgaard-Oeschger (DO) events in the decreasing phase of obliquity. Here, we report the number of significant high Shannon entropy (SE) (C.E. Shannon and W. Weaver, 1949) of 95% significance level of DO events in the increasing and decreasing phases of obliquity, respectively. First, the proxy time series are filtered by EEMD to obtain DO events. Then, the time-varying SE of DO modes are calculated on the basis of principle of histogram. The 95% significance level is evaluated through surrogate data (T. Schreiber and A. Schmitz, 1996). Finally, a comparison between the numbers of SE values that are larger than 95% significance level in the increasing and decreasing phases of obliquity, respectively, is reported.

4.
Nat Commun ; 9(1): 3378, 2018 08 23.
Artigo em Inglês | MEDLINE | ID: mdl-30140008

RESUMO

Inference of causality in time series has been principally based on the prediction paradigm. Nonetheless, the predictive causality approach may underestimate the simultaneous and reciprocal nature of causal interactions observed in real-world phenomena. Here, we present a causal-decomposition approach that is not based on prediction, but based on the covariation of cause and effect: cause is that which put, the effect follows; and removed, the effect is removed. Using empirical mode decomposition, we show that causal interaction is encoded in instantaneous phase dependency at a specific time scale, and this phase dependency is diminished when the causal-related intrinsic component is removed from the effect. Furthermore, we demonstrate the generic applicability of our method to both stochastic and deterministic systems, and show the consistency of causal-decomposition method compared to existing methods, and finally uncover the key mode of causal interactions in both modelled and actual predator-prey systems.


Assuntos
Causalidade , Modelos Biológicos , Algoritmos , Estudos de Viabilidade , Fatores de Tempo
5.
Neurobiol Aging ; 70: 59-69, 2018 10.
Artigo em Inglês | MEDLINE | ID: mdl-30007165

RESUMO

The intrinsic composition and functional relevance of resting-state blood oxygen level-dependent signals are fundamental in research using functional magnetic resonance imaging (fMRI). Using the Hilbert-Huang Transform to estimate high-resolution time-frequency spectra, we investigated the instantaneous frequency and amplitude modulation of resting-state fMRI signals, as well as their functional relevance in a large normal-aging cohort (n = 420, age = 21-89 years). We evaluated the cognitive function of each participant and recorded respiratory signals during fMRI scans. The results showed that the Hilbert-Huang Transform effectively categorized resting-state fMRI power spectra into high (0.087-0.2 Hz), low (0.045-0.087 Hz), and very-low (≤0.045 Hz) frequency bands. The high-frequency power was associated with respiratory activity, and the low-frequency power was associated with cognitive function. Furthermore, within the cognition-related low-frequency band (0.045-0.087 Hz), we discovered that aging was associated with the increased frequency modulation and reduced amplitude modulation of the resting-state fMRI signal. These aging-related changes in frequency and amplitude modulation of resting-state fMRI signals were unaccounted for by the loss of gray matter volume and were consistently identified in the default mode and salience network. These findings indicate that resting-state fMRI signal modulations are dynamic during the normal aging process. In summary, our results refined the functionally related blood oxygen level-dependent frequency band in a considerably narrow band at a low-frequency range (0.045-0.087 Hz) and challenged the current method of resting-fMRI preprocessing by using low-frequency filters with a relatively wide range below 0.1 Hz.


Assuntos
Envelhecimento/fisiologia , Mapeamento Encefálico/métodos , Ondas Encefálicas , Encéfalo/fisiologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Envelhecimento/psicologia , Humanos , Imagem por Ressonância Magnética , Pessoa de Meia-Idade , Vias Neurais/fisiologia , Testes Neuropsicológicos , Processamento de Sinais Assistido por Computador , Adulto Jovem
6.
Front Hum Neurosci ; 11: 261, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28572762

RESUMO

Sleep spindles are brief bursts of brain activity in the sigma frequency range (11-16 Hz) measured by electroencephalography (EEG) mostly during non-rapid eye movement (NREM) stage 2 sleep. These oscillations are of great biological and clinical interests because they potentially play an important role in identifying and characterizing the processes of various neurological disorders. Conventionally, sleep spindles are identified by expert sleep clinicians via visual inspection of EEG signals. The process is laborious and the results are inconsistent among different experts. To resolve the problem, numerous computerized methods have been developed to automate the process of sleep spindle identification. Still, the performance of these automated sleep spindle detection methods varies inconsistently from study to study. There are two reasons: (1) the lack of common benchmark databases, and (2) the lack of commonly accepted evaluation metrics. In this study, we focus on tackling the second problem by proposing to evaluate the performance of a spindle detector in a multi-objective optimization context and hypothesize that using the resultant Pareto fronts for deriving evaluation metrics will improve automatic sleep spindle detection. We use a popular multi-objective evolutionary algorithm (MOEA), the Strength Pareto Evolutionary Algorithm (SPEA2), to optimize six existing frequency-based sleep spindle detection algorithms. They include three Fourier, one continuous wavelet transform (CWT), and two Hilbert-Huang transform (HHT) based algorithms. We also explore three hybrid approaches. Trained and tested on open-access DREAMS and MASS databases, two new hybrid methods of combining Fourier with HHT algorithms show significant performance improvement with F1-scores of 0.726-0.737.

7.
PLoS One ; 11(12): e0168108, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27973590

RESUMO

Empirical mode decomposition (EMD) is an adaptive filter bank for processing nonlinear and non-stationary signals, such as electroencephalographic (EEG) signals. EMD works well to decompose a time series into a set of intrinsic mode functions with specific frequency bands. An IMF therefore represents an intrinsic component on its correspondingly intrinsic frequency band. The word of 'intrinsic' means the frequency is totally adaptive to the nature of a signal. In this study, power density and nonlinearity are two critical parameters for characterizing the amplitude and frequency modulations in IMFs. In this study, a nonlinearity level is quantified using degree of waveform distortion (DWD), which represents the characteristic of waveform distortion as an assessment of the intra-wave modulation of an IMF. In the application of anesthesia EEG analysis, the assessments of power density and DWD for a set of IMFs represent dynamic responses in EEG caused by two different anesthesia agents, Ketamine and Alfentanil, on different frequency bands. Ketamine causes the increase of power density and the decrease of nonlinearity on γ-band neuronal oscillation, which cannot be found EEG responses of group B using Alfentanil. Both agents cause an increase of power density and a decrease of nonlinearity on ß-band neuronal oscillation accompany with a loss of consciousness. Moreover, anesthesia agents cause the decreases of power density and nonlinearity (i.e. DWD) for the low-frequency IMFs.


Assuntos
Alfentanil/química , Anestesia/métodos , Eletroencefalografia , Ketamina/química , Alfentanil/administração & dosagem , Algoritmos , Anestesiologia , Bases de Dados Factuais , Humanos , Ketamina/administração & dosagem , Monitorização Intraoperatória/métodos , Neurônios/fisiologia , Dinâmica não Linear , Oscilometria , Oximetria , Reprodutibilidade dos Testes , Risco , Processamento de Sinais Assistido por Computador , Procedimentos Cirúrgicos Operatórios
8.
Chaos ; 26(2): 023109, 2016 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-26931590

RESUMO

The complex fluctuations in heart rate variability (HRV) reflect cardiac autonomic modulation and are an indicator of congestive heart failure (CHF). This paper proposes a novel nonlinear approach to HRV investigation, the multi dynamic trend analysis (MDTA) method, based on the empirical mode decomposition algorithm of the Hilbert-Huang transform combined with a variable-sized sliding-window method. Electrocardiographic signal data obtained from the PhysioNet database were used. These data were from subjects with CHF (mean age = 59.4 ± 8.4), an age-matched elderly healthy control group (59.3 ± 10.6), and a healthy young group (30.3 ± 4.8); the HRVs of these subjects were processed using the MDTA method, time domain analysis, and frequency domain analysis. Among all HRV parameters, the MDTA absolute value slope (MDTS) and MDTA deviation (MDTD) exhibited the greatest area under the curve (AUC) of the receiver operating characteristics in distinguishing between the CHF group and the healthy controls (AUC = 1.000) and between the healthy elderly subject group and the young subject group (AUC = 0.834 ± 0.067 for MDTS; 0.837 ± 0.066 for MDTD). The CHF subjects presented with lower MDTA indices than those of the healthy elderly subject group. Furthermore, the healthy elderly subjects exhibited lower MDTA indices than those of the young controls. The MDTA method can adaptively and automatically identify the intrinsic fluctuation on variable temporal and spatial scales when investigating complex fluctuations in the cardiac autonomic regulation effects of aging and CHF.


Assuntos
Envelhecimento/fisiologia , Insuficiência Cardíaca/fisiopatologia , Frequência Cardíaca/fisiologia , Adulto , Fatores Etários , Idoso , Área Sob a Curva , Feminino , Determinação da Frequência Cardíaca , Humanos , Masculino , Pessoa de Meia-Idade , Fatores de Tempo
9.
Philos Trans A Math Phys Eng Sci ; 374(2065): 20150207, 2016 Apr 13.
Artigo em Inglês | MEDLINE | ID: mdl-26953179
10.
Philos Trans A Math Phys Eng Sci ; 374(2065): 20150206, 2016 Apr 13.
Artigo em Inglês | MEDLINE | ID: mdl-26953180

RESUMO

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert-Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time-frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities.

11.
Philos Trans A Math Phys Eng Sci ; 374(2065): 20150204, 2016 Apr 13.
Artigo em Inglês | MEDLINE | ID: mdl-26953181

RESUMO

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease.


Assuntos
Algoritmos , Processamento de Sinais Assistido por Computador , Adulto , Idoso , Eletrocardiografia , Entropia , Fractais , Insuficiência Cardíaca/fisiopatologia , Frequência Cardíaca/fisiologia , Humanos , Pessoa de Meia-Idade , Fatores de Tempo
12.
JACC Clin Electrophysiol ; 2(6): 667-678, 2016 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-29759744

RESUMO

OBJECTIVES: This prospective study compared the efficacy of atrial substrate modification guided by a nonlinear phase mapping technique with that of conventional substrate ablation. BACKGROUND: The optimal ablation strategy for persistent atrial fibrillation (AF) was unknown. METHODS: In phase 1 study, we applied a cellular automation technique to simulate the electrical wave propagation to improve the phase mapping algorithm, involving analysis of high-similarity electrogram regions. In addition, we defined rotors and focal AF sources, using the physical parameters of the divergence and curvature forces. In phase 2 study, we enrolled 68 patients with persistent AF undergoing substrate modification into 2 groups, group-1 (n = 34) underwent similarity index (SI) and phase mapping techniques; group-2 (n = 34) received complex fractionated atrial electrogram ablation with commercially available software. Group-1 received real-time waveform similarity measurements in which a phase mapping algorithm was applied to localize the sources. We evaluated the single-procedure freedom from AF. RESULTS: In group-1, we identified an average of 2.6 ± 0.89 SI regions per chamber. These regions involved rotors and focal sources in 65% and 77% of patients in group-1, respectively. Group-1 patients had shorter ablation procedure times, higher termination rates, and significant reduction in AF recurrence compared to group-2 and a trend toward benefit for all atrial arrhythmias. Multivariate analysis showed that substrate mapping using nonlinear similarity and phase mapping was the independent predictor of freedom from AF recurrence (hazard ratio: 0.26; 95% confidence interval: 0.09 to 0.74; p = 0.01). CONCLUSIONS: Our study showed that for persistent AF ablation, a specified substrate modification guided by nonlinear phase mapping could eliminate localized re-entry and non-pulmonary focal sources after pulmonary vein isolation.

13.
J Headache Pain ; 16: 533, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-26018293

RESUMO

BACKGROUND: Researches to date on the association between headache and weather have yielded inconsistent results. Only a limited number of studies have examined the clinical significance of self-reported weather sensitivity. This study aimed to identify the difference in the association of headache with temperature between migraine patients with and without temperature sensitivity. METHODS: 66 migraine patients (75.8 % female; mean age 43.3 ± 12.9 years) provided their 1-year headache diaries from 2007 to a headache clinic in Taipei, Taiwan. 34 patients (51.5 %) reported sensitivity to temperature change but 32 (48.5 %) did not. Time series of daily headache incidence was modeled and stratified by temperature sensitivity. Empirical mode decomposition was used to identify temporal weather patterns that were correlated to headache incidence, and regression analysis was used to examine the amount of variance in headache incidence that could be explained by temperature in different seasons. RESULTS: Among all migraine patients, temperature change accounted for 16.5 % of variance in headache incidence in winter and 9.6 % in summer. In winter, the explained variance increased to 29.2 % among patients with temperature sensitivity, but was not significant among those without temperature sensitivity. Overall, temperature change explained 27.0 % of the variance of the mild headache incidence but only 4.8 % of the incidence of moderate to severe headache during winter. CONCLUSIONS: This diary-based study provides evidence to link the perception of temperature sensitivity and headache incidence in migraine patients. Those who reported temperature sensitivity are more likely to have headache increase during the winter, particular for mild headaches.


Assuntos
Transtornos de Enxaqueca/etiologia , Estações do Ano , Temperatura , Adulto , Feminino , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Índice de Gravidade de Doença , Taiwan
14.
Hum Brain Mapp ; 36(6): 2174-86, 2015 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-25664834

RESUMO

Schizophrenia is characterized by heterogeneous pathophysiology. Using multiscale entropy (MSE) analysis, which enables capturing complex dynamics of time series, we characterized MSE patterns of blood-oxygen-level-dependent (BOLD) signals across different time scales and determined whether BOLD activity in patients with schizophrenia exhibits increased complexity (increased entropy in all time scales), decreased complexity toward regularity (decreased entropy in all time scales), or decreased complexity toward uncorrelated randomness (high entropy in short time scales followed by decayed entropy as the time scale increases). We recruited 105 patients with schizophrenia with an age of onset between 18 and 35 years and 210 age- and sex-matched healthy volunteers. Results showed that MSE of BOLD signals in patients with schizophrenia exhibited two routes of decreased BOLD complexity toward either regular or random patterns. Reduced BOLD complexity toward regular patterns was observed in the cerebellum and temporal, middle, and superior frontal regions, and reduced BOLD complexity toward randomness was observed extensively in the inferior frontal, occipital, and postcentral cortices as well as in the insula and middle cingulum. Furthermore, we determined that the two types of complexity change were associated differently with psychopathology; specifically, the regular type of BOLD complexity change was associated with positive symptoms of schizophrenia, whereas the randomness type of BOLD complexity was associated with negative symptoms of the illness. These results collectively suggested that resting-state dynamics in schizophrenia exhibit two routes of pathologic change toward regular or random patterns, which contribute to the differences in syndrome domains of psychosis in patients with schizophrenia.


Assuntos
Encéfalo/fisiopatologia , Esquizofrenia/fisiopatologia , Adulto , Idade de Início , Mapeamento Encefálico , Circulação Cerebrovascular/fisiologia , Estudos de Coortes , Feminino , Humanos , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Oxigênio/sangue , Descanso , Adulto Jovem
15.
Hum Brain Mapp ; 35(7): 3238-48, 2014 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-24193893

RESUMO

The apolipoprotein E (APOE) gene is associated with structural and functional brain changes. We have used multiscale entropy (MSE) analysis to detect changes in the complexity of resting blood oxygen level-dependent (BOLD) signals associated with aging and cognitive function. In this study, we further hypothesized that the APOE genotype may affect the complexity of spontaneous BOLD activity in younger and older adults, and such altered complexity may be associated with certain changes in functional connectivity. We conducted a resting-state functional magnetic resonance imaging experiment in a cohort of 100 younger adults (aged 20-39 years; mean 27.2 ± 4.3 years; male/female: 53/47) and 112 older adults (aged 60-79 years; mean 68.4 ± 6.5 years; male/female: 54/58), and applied voxelwise MSE analysis to assess the main effect of APOE genotype on resting-state BOLD complexity and connectivity. Although the main effect of APOE genotype on BOLD complexity was not observed in younger group, we observed that older APOE ɛ4 allele carriers had significant reductions in BOLD complexity in precuneus and posterior cingulate regions, relative to noncarriers. We also observed that reduced BOLD complexity in precuneus and posterior cingulate regions was associated with increased functional connectivity to the superior and inferior frontal gyrus in the older group. These results support the compensatory recruitment hypothesis in older APOE ɛ4 carriers, and confer the impact of the APOE genotype on the temporal dynamics of brain activity in older adults.


Assuntos
Envelhecimento/genética , Apolipoproteína E4/genética , Encéfalo/fisiologia , Descanso/fisiologia , Adulto , Idoso , Encéfalo/irrigação sanguínea , Mapeamento Encefálico , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Modelos Lineares , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Oxigênio/sangue , Adulto Jovem
16.
J Cardiovasc Electrophysiol ; 25(4): 411-417, 2014 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-24320556

RESUMO

INTRODUCTION: Antitachycardia pacing (ATP), a quick, painless, and effective therapy available in implantable cardioverter-defibrillators (ICDs), can terminate most, but not all, sustained ventricular tachycardias (VTs). This study investigated the possible ventricular electrogram (EGM) factors for predicting the effectiveness of ATP therapy from ICD recordings. METHODS AND RESULTS: In this study, we analyzed 113 EGMs of VT episodes acquired from 20 patients who received ATP or shock to terminate tachyarrhythmias during follow-up after ICD implantations. The relationship between the outcome of ATP and VT EGM features (such as voltage, width, cycle length, and beat-to-beat morphologic variation) was investigated. The divergence (beat-to-beat morphologic variation) of the VT EGMs was determined by calculating the total deviation of all EGMs away from the average template after all VT EMGs were aligned. In total, 72 (63.7%) successful (Group I) and 41 (36.3%) unsuccessful (Group II) ATP therapy episodes were analyzed. The mean amplitude, cycle length, and EGM width were similar between these 2 groups (P > 0.05). A multivariate analysis demonstrated that the only predictor of successful ATP was the divergence among the VT EGMs (0.56 ± 0.32 vs 1.07 ± 0.64, P < 0.001, for Groups 1 and 2, respectively). The optimal cutoff value for determining a successful ATP therapy was 0.73 (with an area under the curve of 0.769, sensitivity of 81.9% [95% CI = 71.1-90.0], and specificity of 65.9% [95% CI = 49.4-79.9], P < 0.0001). CONCLUSION: Signal analyses from stored EGMs of VT can predict the response of ATP therapy in patients with ICD implantations. A lesser ventricular beat-to-beat morphologic variation in the intracardiac recordings from ICDs correlated with a higher probability of a successful ATP.


Assuntos
Estimulação Cardíaca Artificial/métodos , Desfibriladores Implantáveis , Eletrocardiografia/métodos , Processamento de Sinais Assistido por Computador/instrumentação , Taquicardia Ventricular/fisiopatologia , Taquicardia Ventricular/terapia , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Eletrocardiografia/instrumentação , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes
17.
Circ Arrhythm Electrophysiol ; 6(5): 851-8, 2013 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-23983246

RESUMO

BACKGROUND: Identification of critical atrial substrates in patients with nonparoxysmal atrial fibrillation (AF) failing to respond to pulmonary vein isolation is important. This study investigated the signal characteristics, substrate nature, and ablation results of rotors during AF. METHODS AND RESULTS: In total, 53 patients (age=55±8), 31 with persistent AF and 22 with long-lasting AF, underwent pulmonary vein isolation and substrate modification of complex fractionated atrial electrograms. Small-radius-reentrant rotors were identified from signal analyses of the dominant frequency and fractionation interval and nonlinear analyses (newly developed, beat-to-beat nonlinear measurement of the repetitiveness of the electrogram morphology>6 seconds). In 15% of the patients, activation maps demonstrated occurrences of rotor-like small-radius reentrant circuits (n=9; 1.1 per patient; cycle length=110±21 ms; diameter=11±6 mm) with fibrillation occurring outside these areas. Rotors were identified by conventional point-by-point mapping and signal analyses and were subsequently eradicated by catheter ablation in these patients. Persistent AF for <1 year, a smaller left atrial size, substrates with higher mean voltages and shorter total activation durations predicted a higher incidence of rotors (all P<0.05). In the multivariable model, areas of reentrant circuits exhibited a higher dominant frequency, kurtosis, and higher degree of a beat-to-beat electrogram similarity than areas without or outside the rotors (all P<0.05). CONCLUSIONS: Rotor-like re-entry with fibrillatory conduction was found in a limited number of patients with nonparoxysmal AF after pulmonary vein isolation. Those areas were characterized by rapid repetitive activity with a high degree of electrogram similarity.


Assuntos
Fibrilação Atrial/fisiopatologia , Fibrilação Atrial/cirurgia , Ablação por Cateter/métodos , Sistema de Condução Cardíaco/fisiopatologia , Sistema de Condução Cardíaco/cirurgia , Veias Pulmonares/fisiopatologia , Veias Pulmonares/cirurgia , Adulto , Idoso , Eletrocardiografia , Técnicas Eletrofisiológicas Cardíacas , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Prevalência
18.
Artigo em Inglês | MEDLINE | ID: mdl-23954738

RESUMO

This study assessed the utility of multiscale entropy (MSE), a complexity analysis of biological signals, to identify changes in dynamics of surface electroencephalogram (EEG) in patients with Alzheimer's disease (AD) that was correlated to cognitive and behavioral dysfunction. A total of 108 AD patients were recruited and their digital EEG recordings were analyzed using MSE methods. We investigate the appropriate parameters and time scale factors for MSE calculation from EEG signals. We then assessed the within-subject consistency of MSE measures in different EEG epochs and correlations of MSE measures to cognitive and neuropsychiatric symptoms of AD patients. Increased severity of AD was associated with decreased MSE complexity as measured by short-time scales, and with increased MSE complexity as measured by long-time scales. MSE complexity in EEGs of the temporal and occipitoparietal electrodes correlated significantly with cognitive function. MSE complexity of EEGs in various brain areas was also correlated to subdomains of neuropsychiatric symptoms. MSE analysis revealed abnormal EEG complexity across short- and long-time scales that were correlated to cognitive and neuropsychiatric assessments. The MSE-based EEG complexity analysis may provide a simple and cost-effective method to quantify the severity of cognitive and neuropsychiatric symptoms in AD patients.


Assuntos
Doença de Alzheimer/complicações , Ondas Encefálicas/fisiologia , Transtornos Cognitivos/etiologia , Dinâmica não Linear , Idoso , Idoso de 80 Anos ou mais , Análise de Variância , Eletroencefalografia , Entropia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Testes Neuropsicológicos , Escalas de Graduação Psiquiátrica , Índice de Gravidade de Doença , Estatística como Assunto
19.
Chronobiol Int ; 30(4): 478-85, 2013 May.
Artigo em Inglês | MEDLINE | ID: mdl-23281718

RESUMO

Bipolar disorder seasonality has been documented previously, though information on the effect of demographic and clinical variables on seasonal patterns is scant. This study examined effects of age, sex, index admission, and predominant polarity on bipolar disorder seasonality in a nationwide population. An inpatient cohort admitted to hospital exclusively for mental illness was derived from the Taiwan National Health Insurance Research Database for 2002-2007. The authors identified 9619 inpatients with bipolar disorder, who had generated 15 078 acute admission records. An empirical mode decomposition method was used to identify seasonal oscillations in bipolar admission data, and regression and cross-correlation analyses were used to quantify the degree and timing of bipolar admission seasonality. Results for seasonality timing found that manic or mixed episodes peak in spring or summer, and depressive episodes peak in winter. Analysis for degree of seasonality revealed that (1) the polarity of patients' index admission predicted the seasonality of relapse admissions; (2) seasonality was significant in female admissions for depressive episodes and in male admissions for manic episodes; (3) young adults displayed a higher degree of seasonality for acute admissions than middle-aged adults; and (4) patients with predominantly depressive admissions displayed a higher degree of seasonality than patients with predominantly manic admissions. Demographic and clinical variables were found to affect the seasonality of acute admissions for bipolar disorders. These findings highlight the need for research on identification and management of seasonal features in bipolar patients.


Assuntos
Envelhecimento , Transtorno Bipolar/patologia , Estações do Ano , Fatores Sexuais , Adolescente , Adulto , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Fotoperíodo , Temperatura , Adulto Jovem
20.
J Cardiovasc Electrophysiol ; 24(3): 280-9, 2013 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-23130721

RESUMO

INTRODUCTION: Currently, the identification of complex fractionated atrial electrograms (CFEs) in the substrate modification is mostly based on cycle length-derived algorithms. The characteristics of the fibrillation electrogram morphology and their consistency over time are not clear. The aim of this study was to optimize the detection algorithm of crucial CFEs by using nonlinear measure electrogram similarity. METHODS AND RESULTS: One hundred persistent atrial fibrillation patients that underwent catheter ablation were included. In patients who required CFE ablation (79%), the time-domain fibrillation signals (6 seconds) were acquired for a linear analysis (mean fractionation interval and dominant frequency [DF]) and nonlinear-based waveform similarity analysis of the local electrograms, termed the similarity index (SI). Continuous CFEs were targeted with an endpoint of termination. Predictors of the various signal characteristics on the termination and clinical outcome were investigated. Procedural termination was observed in 39% and long-term sinus rhythm maintenance in 67% of the patients. The targeted CFEs didn't differ based on the linear analysis modalities between the patients who responded and did not respond to CFE ablation. In contrast, the average SI of the targeted CFEs was higher in termination patients, and they had a better outcome. Multivariate regression analysis showed that a higher SI independently predicted sites of termination (≥ 0.57; OR = 4.9; 95% CI = 1.33-18.0; P = 0.017). CONCLUSIONS: In persistent AF patients, a cycle length-based linear analysis could not differentiate culprit CFEs from bystanders. This study suggested that sites with a high level of fibrillation electrogram similarity at the CFE sites were important for AF maintenance.


Assuntos
Algoritmos , Fibrilação Atrial/diagnóstico , Técnicas Eletrofisiológicas Cardíacas , Sistema de Condução Cardíaco/fisiopatologia , Dinâmica não Linear , Processamento de Sinais Assistido por Computador , Adulto , Idoso , Fibrilação Atrial/fisiopatologia , Fibrilação Atrial/cirurgia , Ablação por Cateter , Distribuição de Qui-Quadrado , Feminino , Sistema de Condução Cardíaco/cirurgia , Humanos , Modelos Lineares , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Razão de Chances , Valor Preditivo dos Testes , Fatores de Tempo , Resultado do Tratamento
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