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1.
Psychiatry Res ; 293: 113454, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-32977051

RESUMO

BACKGROUND: Restless legs syndrome (RLS) has been thought to increase the risk of hypertension, cardiovascular events, and all-cause mortality. Periodic limb movements in sleep (PLMS) can be observed in most patients with RLS. Using non-invasive physiologic measurement and analysis, including heart rate variability (HRV) analysis, we aimed to investigate sleep quality and sleep state stability. METHOD: A total of 53 healthy controls and 15 patients with RLS and PLMS were recruited. Patients with other sleep-related disorders such as obstructive sleep apnea (OSA) and major depressive disorder (MDD) were excluded. Each subject was evaluated using sleep and mood questionnaires and had to undergo polysomnography (PSG). HRV analysis was applied to assess autonomic function and analyze correlations with the severity of periodic leg movements (PLM). The power of different brainwaves was analyzed using electroencephalogram (EEG). Electromyogram (EMG) was also used to explore the temporal correlation between changes in HRV and leg movement events. RESULTS: Compared with healthy controls, PLMS group had not only poorer perceived sleep and mood questionnaires scales but also reductions in parasympathetic-related HRV indices and increases in sympathetic-related HRV parameters. The changes were in proportion to the severity of PLM. Brainwaves and sleep stage which indicate "deep sleep" decreased in the PLMS group. There were no significant temporal correlations between changes in HRV and leg movement events. CONCLUSIONS: Our findings suggest that patients with RLS and PLMS have poorer subjective sleep and mood scales. Besides, objective sleep quality including HRV analysis and brainwaves analysis revealed reduced parasympathetic tone, increased sympathetic tone, and sleep disturbance, which reveal the possibility of a higher risk for secondary disease.

2.
Sci Rep ; 10(1): 14916, 2020 09 10.
Artigo em Inglês | MEDLINE | ID: mdl-32913306

RESUMO

Heart failure (HF) is a major cardiovascular disease worldwide, and the early detection and diagnosis remain challenges. Recently, heart rhythm complexity analysis, derived from non-linear heart rate variability (HRV) analysis, has been proposed as a non-invasive method to detect diseases and predict outcomes. In this study, we aimed to investigate the diagnostic value of heart rhythm complexity in HF patients. We prospectively analyzed 55 patients with symptomatic HF with impaired left ventricular ejection fraction and 97 participants without HF symptoms and normal LVEF as controls. Traditional linear HRV parameters and heart rhythm complexity including detrended fluctuation analysis (DFA) and multiscale entropy (MSE) were analyzed. The traditional linear HRV, MSE parameters and DFAα1 were significantly lower in HF patients compared with controls. In regression analysis, DFAα1 and MSE scale 5 remained significant predictors after adjusting for multiple clinical variables. Among all HRV parameters, MSE scale 5 had the greatest power to differentiate the HF patients from the controls in receiver operating characteristic curve analysis (area under the curve: 0.844). In conclusion, heart rhythm complexity appears to be a promising tool for the detection and diagnosis of HF.

3.
Psychiatry Res ; 291: 113257, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32619826

RESUMO

Research suggests that the aging relates to variability of resting-state fMRI (rs-fMRI) signal and the functional connectivity. However, the association between the spatial and temporal activity of resting-state fMRI signal was less documented. We recruited 477 healthy Han Chinese participants, who were separated into young, middle and old groups to investigate the relationship between the variability and global functional connectivity (gFC) in different age ranges using standard deviation (SD) of time series and gFC, respectively. Our analysis revealed the changing patterns during healthy aging: 1) 17 brain regions(Olfactory_L, Orbital_L etc.) were identified to have significant association of age with both SD and gFC respectively by linear regression analysis; 2) Two typical associations could be observed between SD and gFC: positive and negative correlations; 3) The variation ratio of SD to gFC was changing with age at the voxel level by using unsupervised clustering method. It is the first time to combine voxel-wise variability and gFC together for the study of age-related changes with rs-fMRI signal. This study may provide a new clue for understanding the synchronization of human brain based on SD and gFC due to the effect of aging.

4.
J Am Heart Assoc ; 9(2): e013036, 2020 01 21.
Artigo em Inglês | MEDLINE | ID: mdl-31910780

RESUMO

Background Cardiovascular disease is the leading cause of morbidity and mortality in patients with end-stage renal disease. Heart rhythm complexity analysis has been shown to be useful in predicting outcomes in various diseases; however, data on patients with end-stage renal disease are limited. In this study, we analyzed the association between heart rhythm complexity and long-term cardiovascular outcomes in patients with end-stage renal disease receiving peritoneal dialysis. Methods and Results We prospectively enrolled 133 patients receiving peritoneal dialysis and analyzed linear heart rate variability and heart rhythm complexity variables including detrended fluctuation analysis (DFA) and multiscale entropy. The primary outcome was cardiovascular mortality, and the secondary outcome was the occurrence of major adverse cardiovascular events. After a median of 6.37 years of follow-up, 21 patients (22%) died from cardiovascular causes. These patients had a significantly lower low-frequency band of heart rate variability, low/high-frequency band ratio, total power band of heart rate variability, heart rate turbulence slope, deceleration capacity, short-term DFA (DFAα1); and multiscale entropy slopes 1 to 5, scale 5, area 1 to 5, and area 6 to 20 compared with the patients who did not die from cardiovascular causes. Time-dependent receiver operating characteristic curve analysis showed that DFAα1 had the greatest discriminatory power for cardiovascular mortality (area under the curve: 0.763) and major adverse cardiovascular events (area under the curve: 0.730). The best cutoff value for DFAα1 was 0.98 to predict both cardiovascular mortality and major adverse cardiovascular events. Multivariate Cox regression analysis showed that DFAα1 (hazard ratio: 0.076; 95% CI, 0.016-0.366; P=0.001) and area 1 to 5 (hazard ratio: 0.645; 95% CI, 0.447-0.930; P=0.019) were significantly associated with cardiovascular mortality. Conclusions Heart rhythm complexity appears to be a promising noninvasive tool to predict long-term cardiovascular outcomes in patients receiving peritoneal dialysis.

5.
Sleep Breath ; 24(1): 231-240, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-31222591

RESUMO

PURPOSE: Despite the increasing number of research studies of cardiopulmonary coupling (CPC) analysis, an electrocardiogram-based technique, the use of CPC in underserved population remains underexplored. This study aimed to first evaluate the reliability of CPC analysis for the detection of obstructive sleep apnea (OSA) by comparing with polysomnography (PSG)-derived sleep outcomes. METHODS: Two hundred five PSG data (149 males, age 46.8 ± 12.8 years) were used for the evaluation of CPC regarding the detection of OSA. Automated CPC analyses were based on ECG signals only. Respiratory event index (REI) derived from CPC and apnea-hypopnea index (AHI) derived from PSG were compared for agreement tests. RESULTS: CPC-REI positively correlated with PSG-AHI (r = 0.851, p < 0.001). After adjusting for age and gender, CPC-REI and PSG-AHI were still significantly correlated (r = 0.840, p < 0.001). The overall results of sensitivity and specificity of CPC-REI were good. CONCLUSION: Compared with the gold standard PSG, CPC approach yielded acceptable results among OSA patients. ECG recording can be used for the screening or diagnosis of OSA in the general population.

6.
J Clin Monit Comput ; 34(6): 1311-1319, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-31872311

RESUMO

Poor sleep quality is associated with autonomic dysfunctions and altered pain perception and tolerance. To investigate whether autonomic dysregulations related to insomnia would still exist under general anesthesia, we adopt heart rate variability (HRV) analysis to evaluate ANS activity and surgical pleth index (SPI) to compare nociceptive/anti-nociceptive balance. We enrolled 61 adult females scheduled for gynecological surgeries under general anesthesia. All the subjects were ASA Class I to III without using medicines affecting HRV. We used the Insomnia Severity Index to evaluate sleep qualities. ECG data were recorded and signals which denote four different surgical stages were extracted (baseline, incision, mid-surgery, and end of surgery). We analyzed the HRV changes across the whole surgical period and differences among good and poor sleepers. We also compared the SPI differences among groups. For baseline HRV analysis, we found significant differences in the RMSSD (p = 0.043), pNN50 (p = 0.029), VLF power (p = 0.035), LF power (p = 0.004), and HF power (p = 0.037) between the good and poor sleeper groups. However, all intergroup differences disappeared after anesthesia induction. Temporal HRV changes significantly among different perioperative stages (RMSSD, p < 0.001; pNN50, p = 0.004; LF, p < 0.001; and HF, p < 0.001). Patients with different sleep qualities did not exhibit different SPI levels in all four periods. Poor sleepers exhibited attenuated parasympathetic activities at the baseline but no differences after the induction. Nociceptive/anti-nociceptive balance seems not be altered by poor sleep condition under general anesthesia.

7.
Sci Rep ; 9(1): 10710, 2019 07 24.
Artigo em Inglês | MEDLINE | ID: mdl-31341216

RESUMO

Pulmonary hypertension is a fatal disease, however reliable prognostic tools are lacking. Heart rhythm complexity analysis is derived from non-linear heart rate variability (HRV) analysis and has shown excellent performance in predicting clinical outcomes in several cardiovascular diseases. However, heart rhythm complexity has not previously been studied in pulmonary hypertension patients. We prospectively analyzed 57 patients with pulmonary hypertension (31 with pulmonary arterial hypertension and 26 with chronic thromboembolic pulmonary hypertension) and compared them to 57 age- and sex-matched control subjects. Heart rhythm complexity including detrended fluctuation analysis (DFA) and multiscale entropy (MSE) and linear HRV parameters were analyzed. The patients with pulmonary hypertension had significantly lower mean RR, SDRR, pNN20, VLF, LF, LF/HF ratio, DFAα1, MSE slope 5, scale 5, area 1-5 and area 6-20 compared to the controls. Receiver operating characteristic curve analysis showed that heart rhythm complexity parameters were better than traditional HRV parameters to predict pulmonary hypertension. Among all parameters, scale 5 had the greatest power to differentiate the pulmonary hypertension patients from controls (AUC: 0.845, P < 0.001). Furthermore, adding heart rhythm complexity parameters significantly improved the discriminatory power of the traditional HRV parameters in both net reclassification improvement and integrated discrimination improvement models. In conclusion, the patients with pulmonary hypertension had worse heart rhythm complexity. MSE parameters, especially scale 5, had excellent single discriminatory power to predict whether or not patients had pulmonary hypertension.

8.
Sci Rep ; 9(1): 7500, 2019 05 16.
Artigo em Inglês | MEDLINE | ID: mdl-31097732

RESUMO

Measures characterizing the complexity of heart rate (HR) dynamics have been informative in predicting age- and disease-related decline in cardiovascular health, but few studies have evaluated whether mind-body exercise can impact HR complexity. This study evaluated the effects of long-term Tai Chi (TC) practice on the complexity of HR dynamics using an observational comparison of TC experts and age- and gender-matched TC-naïve individuals. Shorter-term effects of TC were assessed by randomly assigning TC-naïve participants to either TC group to receive six months of TC training or to a waitlist control group. 23 TC experts (age = 63.3 ± 8.0 y; 24.6 ± 12.0 y TC experience) and 52 TC-naïve (age = 64.3 ± 7.7 y) were enrolled. In cross-sectional analyses, TC experts had a higher overall complexity index (CI, p = 0.004) and higher entropy at multiple individual time scales (p < 0.05); these findings persisted in models accounting for age, gender, body mass index (BMI), and physical activity levels. Longitudinal changes in complexity index did not differ significantly following random assignment to six months of TC vs. a waitlist control; however, within the TC group, complexity at select time scales showed statistically non-significant trends toward increases. Our study supports that longer-term TC mind-body training may be associated with increased complexity of HR dynamics.

9.
Front Hum Neurosci ; 12: 484, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30574079

RESUMO

The study of the healthy brain in elders, especially age-associated alterations in cognition, is important to understand the deficits created by Alzheimer's disease (AD), which imposes a tremendous burden on individuals, families, and society. Although, the changes in synaptic connectivity and reorganization of brain networks that accompany aging are gradually becoming understood, little is known about how normal aging affects brain inter-regional synchronization and functional networks when items are held in working memory (WM). According to the classic Sternberg WM paradigm, we recorded multichannel electroencephalography (EEG) from healthy adults (young and senior) in three different conditions, i.e., the resting state, 0-back (control) task, and 2-back task. The phase lag index (PLI) between EEG channels was computed and then weighted and undirected network was constructed based on the PLI matrix. The effects of aging on network topology were examined using a brain connectivity toolbox. The results showed that age-related alteration was more prominent when the 2-back task was engaged, especially in the theta band. For the younger adults, the WM task evoked a significant increase in the clustering coefficient of the beta-band functional connectivity network, which was absent in the older adults. Furthermore, significant correlations were observed between the behavioral performance of WM and EEG metrics in the theta and gamma bands, suggesting the potential use of those measures as biomarkers for the evaluation of cognitive training, for instance. Taken together, our findings shed further light on the underlying mechanism of WM in physiological aging and suggest that different EEG frequencies appear to have distinct functional correlates in cognitive aging. Analysis of inter-regional synchronization and topological characteristics based on graph theory is thus an appropriate way to explore natural age-related changes in the human brain.

10.
Front Neurosci ; 12: 809, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30483046

RESUMO

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. Multiscale entropy analysis (MSE) was applied to pre-sleep EEG signals recorded immediately after light-off (while subjects were awake) for measuring the complexities of brain dynamics by a proposed index, CI1-30. Slow wave activity (SWA) in sleep, which is commonly used as an indicator of sleep depth or sleep intensity, was quantified based on two methods, traditional Fast Fourier transform (FFT) and ensemble empirical mode decomposition (EEMD). The associations between wake EEG complexity, sleep latency, and SWA in sleep were evaluated. Our results demonstrated that lower complexity before sleep onset is associated with decreased sleep latency, indicating a potential facilitating role of reduced pre-sleep complexity in the wake-sleep transition. In addition, the proposed EEMD-based method revealed an association between wake complexity and quantified SWA in the beginning of sleep (90 min after sleep onset). Complexity metric could thus be considered as a potential indicator for sleep interventions, and further studies are encouraged to examine the application of EEG complexity before sleep onset in populations with difficulty in sleep initiation. Further studies may also examine the mechanisms of the causal relationships between pre-sleep brain complexity and SWA, or conduct comparisons between normal and pathological conditions.

11.
Sci Rep ; 8(1): 15627, 2018 10 23.
Artigo em Inglês | MEDLINE | ID: mdl-30353094

RESUMO

Abdominal aorta calcification (AAC) has been associated with clinical outcomes in peritoneal dialysis (PD) patients. Heart rhythm complexity analysis has been shown to be a promising tool to predict outcomes in patients with cardiovascular disease. In this study, we aimed to analyze the association between heart rhythm complexity and AAC in PD patients. We prospectively analyzed 133 PD patients. Heart rhythm complexity including detrended fluctuation analysis and multiscale entropy was performed. In linear analysis, the patients in the higher AAC group (AAC ≥15%) had a significantly lower standard deviation of normal RR intervals, very low frequency, low frequency, high frequency and low/high frequency ratio. In non-linear analysis, DFAα1, slope 1-5, scale 5 and area 6-20 were significantly lower in the patients with higher AAC. Receiver operating characteristic curve analysis showed that DFAα1 had the greatest discriminatory power to differentiate these two groups. Multivariate logistic regression analysis showed that DFAα1 and HbA1c were significantly associated with higher AAC ratio. Adding DFAα1 significantly improved the discriminatory power of the linear parameters in both net reclassification improvement and integrated discrimination improvement models. In conclusion, DFAα1 is highly associated with AAC and a potential cardiovascular marker in PD patients.


Assuntos
Aorta Abdominal/fisiopatologia , Frequência Cardíaca/fisiologia , Diálise Peritoneal , Calcificação Vascular/fisiopatologia , Área Sob a Curva , Entropia , Feminino , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Curva ROC
12.
Stroke ; 49(11): 2605-2611, 2018 11.
Artigo em Inglês | MEDLINE | ID: mdl-30355198

RESUMO

Background and Purpose- Cerebral autoregulation is impaired in patients with acute ischemic stroke. The purpose of this study was to investigate whether dynamic cerebral autoregulation (dCA) indices constitute an independent functional outcome predictor of acute ischemic stroke. Methods- In this study, 86 patients at days 3 to 7 after acute ischemic stroke and 40 age- and sex-matched controls were enrolled for assessing their dCA indices under spontaneous hemodynamic fluctuations. The dCA indices of patients with favorable outcomes (modified Rankin Scale score ≤1 at 3 months, n=65), patients with unfavorable outcomes (modified Rankin Scale score ≥2 at 3 months, n=21), and controls were compared. Results- The dCA indices, namely the phase shift at very low frequency band (phase_VLF), in the patients with unfavorable outcomes were significantly worse than those in the patients with favorable outcomes. However, the phase_VLF in the patients with favorable outcomes did not differ from those in the controls. Impaired dCA was associated with elevated mean arterial pressure and large infarction volume but was also present in patients with normal mean arterial pressure or small infarction volume. Phase_VLF was a predictor of outcomes in the receiver operating characteristic analysis (area under the curve: 0.722; P<0.001). Multivariate analysis revealed that a phase_VLF value of <61° was independently associated with unfavorable outcomes (odds ratio=4.90; P=0.024). Conclusions- Phase_VLF is an independent functional outcome predictor of acute ischemic stroke.


Assuntos
Isquemia Encefálica/fisiopatologia , Circulação Cerebrovascular , Hemodinâmica , Homeostase , Acidente Vascular Cerebral/fisiopatologia , Angiografia Cerebral , Imagem de Difusão por Ressonância Magnética , Feminino , Humanos , Angiografia por Ressonância Magnética , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Prognóstico , Índice de Gravidade de Doença
13.
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
14.
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
15.
Front Neurosci ; 12: 398, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29950971

RESUMO

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. We examined the effect of various parameters on the results of SampEn and MSE analyses of a large normal aging adult cohort (354 healthy subjects aged 21-89 years). The results showed that a tradeoff between pattern length m and tolerance factor r was necessary to maintain the accuracy of SampEn estimates. Furthermore, an increased relative error of SampEn was associated with an increased coefficient of variation in voxel-wise statistics. Overall, the parameters m = 1 and r = 0.20-0.45 provided reliable MSE estimates in short resting-state fMRI signals. For a single-scale SampEn analysis, a wide range of parameters was available with data lengths of at least 97 time points. This study provides a minimization error strategy for future studies on the non-linear analysis of resting-state fMRI signals to account for the bias of entropy estimates.

16.
Artigo em Inglês | MEDLINE | ID: mdl-29807061

RESUMO

Abnormal brain lateralization has been implicated in schizophrenia but few studies have focused on the variability of resting-state fMRI signal and its lateralization in schizophrenia. Here we utilized standard deviations (SD) to quantify the variability of resting-state fMRI signal and measured the lateralization index (LI), on the basis of SD of the resting-state fMRI signal in order to assess the difference of brain signal variability across the hemispheres. We recruited 180 patients with schizophrenia and 358 age- and sex-matched healthy volunteers. Between-group comparison revealed that in comparison to healthy volunteers, schizophrenia patients have significantly higher SD of resting-state fMRI activity in left inferior temporal, left fusiform, and right superior medial frontal cortex, and lower SD in right precuneus, posterior cingulum on both sides, right lingual, and left calcarine in the occipital region. Using region of interest approach, most brain regions showed increased leftward lateralization in patients with schizophrenia, as compared with healthy controls. SD and LI were also found to be correlated to age of onset or duration of illness. These results provide further evidence that abnormal variability and lateralization exist in schizophrenia patients, and abnormality in fusiform, lingual and inferior temporal could have potential help to identify the dysfunctional brain lateralization in schizophrenia.


Assuntos
Encéfalo/diagnóstico por imagem , Encéfalo/fisiopatologia , Imagem por Ressonância Magnética , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/fisiopatologia , Mapeamento Encefálico , Estudos de Coortes , Feminino , Lateralidade Funcional , Humanos , Masculino , Pessoa de Meia-Idade , Descanso
18.
Behav Sleep Med ; 16(4): 398-411, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-27676270

RESUMO

OBJECTIVE: This pilot study evaluated the effects of Tai Chi training on sleep quality (primary outcomes), and depression and social functioning levels (secondary outcomes) among patients with depression. PARTICIPANTS: Sixteen depressed Chinese patients. METHODS: Participants received 1-hr Tai Chi training sessions 2 times per week for 10 weeks. Patients' subjective sleep quality ratings, objective sleep quality measurements, and depression and social functioning levels were measured before, during, and after the intervention. RESULTS: Sleep quality and depression outcomes improved significantly. Patients reported improved Pittsburgh Sleep Quality Index (PSQI) scores (9.6 ± 3.3 to 6.6 ± 5.2, p = 0.016), and cardiopulmonary coupling (CPC) analysis of electrocardiogram (ECG) showed decreased stable sleep onset latency (75.7 ± 100.6 to 20.9 ± 18.0, p = 0.014), increased stable sleep percentages (31.5 ± 18.7 to 46.3 ± 16.9, p = 0.016), and decreased unstable sleep percentages (45.3 ± 20.1 to 30.6 ± 16.5, p = 0.003). Patients also reported decreased Hamilton Rating Scale for Depression (HAM-D-17; 20.1 ± 3.7 to 7.8 ± 5.9, p < 0.001) and Beck Depression Inventory (BDI) scores (22.3 ± 9.1 to 11.1 ± 10.6, p = 0.006). Significant correlations were found between the changes in subjective sleep assessments ΔPSQI and ΔHAM-D-17 (r = 0.6, p = 0.014), and ΔPSQI and ΔBDI (r = 0.62, p = 0.010). Correlations between changes in objective sleep measurements and changes in depression symptoms were low and not significant. CONCLUSIONS: Tai Chi training improved sleep quality and mood symptoms among depressed patients.


Assuntos
Transtorno Depressivo Maior/terapia , Transtornos do Sono-Vigília/terapia , Tai Ji/métodos , Adulto , Americanos Asiáticos , Transtorno Depressivo Maior/patologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Projetos Piloto
19.
Sleep Med Rev ; 37: 85-93, 2018 02.
Artigo em Inglês | MEDLINE | ID: mdl-28392169

RESUMO

The analysis of electroencephalography (EEG) recordings has attracted increasing interest in recent decades and provides the pivotal scientific tool for researchers to quantitatively study brain activity during sleep, and has extended our knowledge of the fundamental mechanisms of sleep physiology. Conventional EEG analyses are mostly based on Fourier transform technique which assumes linearity and stationarity of the signal being analyzed. However, due to the complex and dynamical characteristics of EEG, nonlinear approaches are more appropriate for assessing the intrinsic dynamics of EEG and exploring the physiological mechanisms of brain activity during sleep. Therefore, this article introduces the most commonly used nonlinear methods based on the concepts of fractals and entropy, and we review the novel findings from their clinical applications. We propose that nonlinear measures may provide extensive insights into brain activities during sleep. Further studies are proposed to mitigate the limitations and to expand the applications of nonlinear EEG analysis for a more comprehensive understanding of sleep dynamics.


Assuntos
Eletroencefalografia/métodos , Entropia , Fractais , Dinâmica não Linear , Sono/fisiologia , Humanos , Fases do Sono
20.
PLoS One ; 12(10): e0186212, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-29020106

RESUMO

PURPOSE: To determine if Tai Chi (TC) has an impact on long-range correlations and fractal-like scaling in gait stride time dynamics, previously shown to be associated with aging, neurodegenerative disease, and fall risk. METHODS: Using Detrended Fluctuation Analysis (DFA), this study evaluated the impact of TC mind-body exercise training on stride time dynamics assessed during 10 minute bouts of overground walking. A hybrid study design investigated long-term effects of TC via a cross-sectional comparison of 27 TC experts (24.5 ± 11.8 yrs experience) and 60 age- and gender matched TC-naïve older adults (50-70 yrs). Shorter-term effects of TC were assessed by randomly allocating TC-naïve participants to either 6 months of TC training or to a waitlist control. The alpha (α) long-range scaling coefficient derived from DFA and gait speed were evaluated as outcomes. RESULTS: Cross-sectional comparisons using confounder adjusted linear models suggest that TC experts exhibited significantly greater long-range scaling of gait stride time dynamics compared with TC-naïve adults. Longitudinal random-slopes with shared baseline models accounting for multiple confounders suggest that the effects of shorter-term TC training on gait dynamics were not statistically significant, but trended in the same direction as longer-term effects although effect sizes were very small. In contrast, gait speed was unaffected in both cross-sectional and longitudinal comparisons. CONCLUSION: These preliminary findings suggest that fractal-like measures of gait health may be sufficiently precise to capture the positive effects of exercise in the form of Tai Chi, thus warranting further investigation. These results motivate larger and longer-duration trials, in both healthy and health-challenged populations, to further evaluate the potential of Tai Chi to restore age-related declines in gait dynamics. TRIAL REGISTRATION: The randomized trial component of this study was registered at ClinicalTrials.gov (NCT01340365).


Assuntos
Fractais , Marcha , Saúde , Tai Ji , Adulto , Idoso , Cognição , Intervalos de Confiança , Estudos Transversais , Função Executiva , Feminino , Fidelidade a Diretrizes , Humanos , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Seleção de Pacientes , Fatores de Tempo
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