Background: A randomized controlled study (RCT) recently showed that short-term heart rate variability (HRV) biofeedback in addition to standard rehabilitation care for alcohol dependence can reduce craving, anxiety and improve cardiovascular autonomic function. In this one-year follow-up study we aimed to explore whether completion of 2-week HRV-Biofeedback training is associated with long-term abstinence. Furthermore, we sought to identify potential predictors of post-treatment abstinence. Methods: We conducted a survey on abstinence in patients with alcohol dependence 1 year after completion of an RCT comparing HRV-biofeedback in addition to inpatient rehabilitation treatment alone (controls). Abstinence rates were compared and analysed for association with demographic data as well as psychometric and autonomic cardiac assessment before and after completion of the biofeedback training using bivariate and multivariate regression analyses. Results: Out of 48 patients who participated in the RCT, 27 patients (9 females, ages 42.9 ± 8.6, mean ± SD) completed our one-year follow-up. When including in the analysis only patients who completed follow-up, the rate of abstinence tended to be higher in patients who underwent HRV-biofeedback 1 year earlier compared to those who received rehabilitative treatment alone (66.7% vs 50%, p = ns). This non-significant trend was also observed in the intention-to-treat analysis where patients who did not participate in the follow-up were assumed to have relapsed (46,7% biofeedback vs. 33.3% controls, p = ns). Neither cardiac autonomic function nor psychometric variables were associated with abstinence 1 year after HRV-biofeedback. Conclusion: Our follow-up study provide a first indication of possible increase in long-term abstinence after HRVbiofeedback for alcohol dependence in addition to rehabilitation. Trial registration: The original randomized controlled trial was registered in the German Clinical Trials Register (DRKS00004618). This one-year follow-up survey has not been registered.

Physiological signals, electroencephalogram (EEG) and heart rate variability (HRV), are generated by complex self-regulating systems. These signals are extremely inhomogeneous and nonstationary, and fluctuate in an irregular and highly complex manner. These fluctuations are due to underlying dynamics of the system. The synchronous neural activity measured as scalp EEG indicates underlying neural dynamics of the brain. Hence, quantitative EEG analysis has become a very useful tool in interpreting results from physiological experiments. The analysis of HRV provides valuable information to assess the autonomous nervous system (ANS). The HRV can be significantly affected by physiological state changes and many disease states. Hence, HRV analysis is becoming a major experimental and diagnostic tool. In this thesis, we focus on the study of EEG and HRV time series using tools from nonlinear time series analysis with special emphasis on its implications in detecting physiological state changes such as, in diseases like epileptic seizure and schizophrenia, and in altered states of consciousness as in sleep and meditation. The proposed nonlinear techniques are used in discriminating different physiological states from control states. Artifact processing of EEG signal Interferences (artifacts) from various sources unavoidably contaminate EEG recordings. In quantitative analysis, results can differ significantly by these artifacts, which may lead to wrong interpretation of the results. In this part of the thesis, we have devised methods to minimize ocular and muscle artifacts in EEG. The artifact correction methods are based on blind source separation (BSS) techniques such as singular value decomposition (SVD), algorithm for multiple signal extraction (AMUSE), canonical correlation analysis (CCA), information maximization (INFOMAX) independent component analysis (ICA) and joint approximate diagonalization of eigen-matrices (JADE) ICA. We have proposed a method to simulate clean and artifact corrupted EEG data based on the BSS methods. In order to enhance the performance of BSS methods, a technique called wavelet-filtered component inclusion method has been introduced. In addition, second-order statistics (SOS) and higher-order statistics (HOS) based BSS methods have been studied considering less number of EEG channels; and performance comparison of these methods has also been made. We have also addressed the problem of simultaneous correction of ocular and muscle artifacts in EEG recordings using the BSS methods. Irrespective of the BSS methods, the component elimination method has introduced high spectral error in all the bands after reconstruction of clean EEG. However, the wavelet filtered component inclusion method has retained almost all spectral powers of EEG channels in theta, alpha, and beta bands after ocular artifact minimization. When the number of EEG channels is very less, the enhanced CCA (SOS BSS) has given superior artifact minimization results than HOS BSS methods, especially in delta band. The component elimination method is used in muscle artifact minimization, and hence the SVD method cannot be used for this purpose since it leads to large spectral distortion of reconstructed EEG. The AMUSE and CCA methods have given comparable performance in muscle artifact minimization. In addition, the JADE method has introduced less mean spectral error compared to other methods. The CCA method has shown superior performance in simultaneous minimization of ocular and muscle artifacts, and AMUSE and JADE methods have given comparable results. Furthermore, the less computation time of wavelet enhanced SOS BSS methods make them very useful in real clinical environments. Fractal characterization of time series In biomedical signal analysis, fractal dimension (FD) is used as a quantitative measure to estimate complexity of physiological signals. Such analysis helps to study physiological processes of underlying systems. The FD can also be used to study dynamics of transitions between different states of systems like brain and ANS, in various physiological and pathological states. In this part, we have proposed a method to estimate FD of time series, called multiresolution box-counting (MRBC) method. A modification of this method resulted in multiresolution length (MRL) method. The estimation performance of the proposed methods is compared with that of Katz, Sevcik, and Higuchi methods, by simulating mathematically defined fractal signals, and also the computation time is compared between the methods. The MRBC and MRL methods have given comparable performance to that of Higuchi method, in estimating FD of waveforms, with the advantage of less computational time. In addition, various properties of the FD are studied and discussed in connection with classical signal processing concepts such as amplitude, frequency, sampling frequency, effect of noise, band width, correlation, etc. The FD value of signals has increased with number of harmonics, noise variance, band-width, and mid-band frequency, and decreased with degree of correlation in AR signal. An analogy between Katz FD and smoothed Teager energy operator has also been made. Application of fractal analysis to EEG and HRV time series The fluctuation of EEG potentials normally depends upon degree of alertness, and varies in amplitude and frequency. Hence, the EEG is an important clinical tool for studying sleep and sleep related disorders, epileptic seizures, schizophrenia, and meditation. In this part of the thesis, we have used FD which gives signal complexity, and detrended fluctuation analysis (DFA) which gives multiscale exponent of time series to quantify EEG. We have extended the concept of FD to multiscale FD to compute complexity of time series at multiple scales. The main applications of the proposed method are epileptic seizure detection, sleep stage detection, schizophrenia EEG analysis, and analysis of heart rate variability during meditation. For seizure detection, we have used intracranial EEG recordings with seizure-free and seizure intervals. In sleep EEG analysis, whole-night sleep EEG is used and results are compared with the manually scored hypnogram. The schizophrenia symptom is further categorized into positive and negative symptoms and complexity is estimated using FD and DFA. We have also analyzed HRV data of Chi and Kundalini meditation using FD and DFA techniques. In all the applications considered, we have tested for statistical significance of the computed parameters, between the case of interest and corresponding control cases, to discriminate between the physiological states. The ocular artifact has reduced FD while muscle artifact increased FD of EEG. The FD of seizure EEG has shown high value compared to that of seizure-free EEG. In addition, the seizure-free EEG has more DFA exponent-1 than seizure EEG. The value of FD of EEG is decreased with deepening of sleep, wake state having high FD value. The FD of REM state sleep EEG showed value between that of wake and state-1. The DFA exponent-1 has increased with deepening of sleep state, having small value for wake state. The REM state has given exponent-1 value between wake and state-1. The schizophrenia subjects have shown lower FD value than healthy controls in all the EEG channels except the bilateral temporal and occipital regions. The positive symptom sub-group has shown comparatively high FD values than healthy controls as well as overall schizophrenia sample in the bilateral tempero-parietal-occipital region. In addition, the positive symptom sub-group has shown significantly higher regional FD values than negative symptom sub-group especially in right temporal region. The overall schizophrenia samples as well as the positive and negative subgroup have shown least FD values in the bilateral frontal region. The values of DFA exponent-2 have shown significant high value in schizophrenia samples. In addition, the schizophrenia group has shown less DFA exponent-1 in bilateral temporal region than healthy control. The FD, multiscale FD, DFA exponents have shown significant performance in discriminating different physiological states from control states. The FD value of HRV time series during meditation is less compared to pre-meditation state in both Chi and Kundalini meditation. Irrespective of the type of meditation, meditation state has shown significantly high DFA exponent-1 than pre-meditation state, and significantly high DFA exponent-2 in pre-meditation state compared to meditation state. Functional connectivity analysis of brain during meditation In functionally related regions of the brain, even in those regions separated by substantial distances, the EEG fluctuations are synchronous, which is termed as functional connectivity. In this part, a novel application of functional connectivity analysis of brain using graph theoretic approach has been made on the EEG recorded from meditation practitioners. We have used 16 channel EEG data from subjects while performing Raja Yoga meditation. The pre-meditation condition is used as control state, against which meditation state is compared. For finding connectivity between EEG of various channels, we have computed pair-wise linear correlation and mutual information between the EEG channels, to form a connection matrix of size 16x16. Then, various graph parameters, such as average connection density, degree of nodes, characteristic path length, and cluster index, are computed from the connection matrix. The computed parameters are projected on to the scalp to get topographic head maps that give spatial variation of the parameter, and results are compared between meditation and pre-meditation states. The meditation state has shown low average connection density, less characteristic path length, and high average degree in fronto-central and central regions. Furthermore, high cluster index is shown in frontal and central regions than pre-meditation state. The parameters such as complexity, characteristic path length and average connection density are used as features in quadratic discriminant classifier to classify meditation and pre-meditation state, and have given good accuracy performance. Connectivity analysis using mutual information has given high average connection density in meditation state in theta, alpha and beta bands compared to pre-meditation state. The characteristic path length is high in delta, alpha and beta bands in meditation state. In addition, the meditation state has shown high degree and cluster index in theta and beta bands compared to pre-meditation state. Nonlinear dynamical characterization of HRV during meditation The cardiovascular system is influenced by internal dynamics as well as from various external factors, which makes the system more dynamic and nonlinear. In this part of the thesis, a novel application of using HRV data for studying Chi and Kundalini meditation has been made. The HRV time series are embedded into higher dimensional phase-space using Takens’ embedding theorem to reconstruct the attractor. After estimating the minimum embedding dimension to unfold the attractor dynamics, the complexity of the attractor is computed using correlation dimension, Lyapunov exponent, and nonlinearity scores. In all the analyses, the pre-meditation state is used as control state against which meditation state is compared. The statistical significance of the parameters estimated is tested to discriminate meditation state from control state. The HRV time series of both pre-meditation and meditation have shown similar minimum embedding dimensions in both Chi and Kundalini meditation. Irrespective of the type of meditation, the meditation state has shown high correlation dimension, largest Lyapunov exponent, and low nonlinearity score compared to pre-meditation state. Recurrent quantification analysis of HRV during meditation In this part, a novel application of recurrent quantification analysis (RQA) to HRV during meditation is studied. Here, the time series is embedded into a higher dimensional phase-space and Euclidean distance between the embedded vectors is calculated to form a distance matrix. The matrix is converted into binary matrix by applying a suitable threshold, and plotted as image to get recurrence plot. Various parameters are extracted from the recurrence plot such as percent recurrence rate, diagonal parameters (determinism, divergence, entropy, ratio), and vertical or horizontal parameters (laminarity, trapping time, maximal vertical line length). The procedure is applied to HRV data during meditation and pre-meditation (control) to discriminate between the states. The HRV of meditation state has shown more diagonal line structure whereas more black patches are observed in pre-meditation state. In addition, at low embedding dimensions, the meditation state has shown low recurrence rate, high determinism, low divergence, low entropy, high ratio, high laminarity, high trapping time, and less maximal vertical line length compared to pre-meditation state. These RQA parameters have shown superior performance in discriminating meditation state from control state.

For most of the naturally occurring signals, especially biomedical signals, the underlying physical process generating the signal is often not fully known, making it difficult to obtain a parametric model. Therefore, signal processing techniques are used to analyze the signal for non-parametrically characterizing the underlying system from which the signals are produced. Most of the real life systems are nonlinear and time varying, which poses a challenge while characterizing them. Additionally, multiple sensors are used to extract signals from such systems, resulting in multichannel signals which are inherently coupled. In this thesis, we counter this challenge by using Recurrence Plot based techniques for characterizing biomedical systems such as heart or brain, using signals such as heart rate variability (HRV), electroencephalogram(EEG) or functional magnetic resonance imaging (fMRI), respectively, extracted from them. In time series analysis, it is well known that a system can be represented by a trajectory in an N-dimensional state space, which completely represents an instance of the system behavior. Such a system characterization has been done using dynamical invariants such as correlation dimension, Lyapunov exponent etc. Takens has shown that when the state variables of the underlying system are not known, one can obtain a trajectory in ‘phase space’ using only the signals obtained from such a system. The phase space trajectory is topologically equivalent to the state space trajectory. This enables us to characterize the system behavior from only the signals sensed from them. However, estimation of correlation dimension, Lyapunov exponent, etc, are vulnerable to non-stationarities in the signal and require large number of sample points for accurate computation, both of which are important in the case of biomedical signals. Alternatively, a technique called Recurrence Plots (RP) has been proposed, which addresses these concerns, apart from providing additional insights. Measures to characterize RPs of single and two channel data are called Recurrence Quantification Analysis (RQA) and cross RQA (CRQA), respectively. These methods have been applied with a good measure of success in diverse areas. However, they have not been studied extensively in the context of experimental biomedical signals, especially multichannel data. In this thesis, the RP technique and its associated measures are briefly reviewed. Using the computational tools developed for this thesis, RP technique has been applied on select single channel, multichannel and multimodal (i.e. multiple channels derived from different modalities) biomedical signals. Connectivity analysis is demonstrated as post-processing of RP analysis on multichannel signals such as EEG and fMRI. Finally, a novel metric, based on the modification of a CRQA measure is proposed, which shows improved results. For the case of single channel signal, we have considered a large database of HRV signals of 112 subjects recorded for both normal and abnormal (anxiety disorder and depression disorder) subjects, in both supine and standing positions. Existing RQA measures, Recurrence Rate and Determinism, were used to distinguish between normal and abnormal subjects with an accuracy of 58.93%. A new measure, MLV has been introduced, using which a classification accuracy of 98.2% is obtained. Correlation between probabilities of recurrence (CPR) is a CRQA measure used to characterize phase synchronization between two signals. In this work, we demonstrate its utility with application to multimodal and multichannel biomedical signals. First, for the multimodal case, we have computed running CPR (rCPR), a modification proposed by us, which allows dynamic estimation of CPR as a function of time, on multimodal cardiac signals (electrocardiogram and arterial blood pressure) and demonstrated that the method can clearly detect abnormalities (premature ventricular contractions); this has potential applications in cardiac care such as assisted automated diagnosis. Second, for the multichannel case, we have used 16 channel EEG signals recorded under various physiological states such as (i) global epileptic seizure and pre-seizure and (ii) focal epilepsy. CPR was computed pair-wise between the channels and a CPR matrix of all pairs was formed. Contour plot of the CPR matrix was obtained to illustrate synchronization. Statistical analysis of CPR matrix for 16 subjects of global epilepsy showed clear differences between pre-seizure and seizure conditions, and a linear discriminant classifier was used in distinguishing between the two conditions with 100% accuracy. Connectivity analysis of multichannel EEG signals was performed by post-processing of the CPR matrix to understand global network-level characterization of the brain. Brain connectivity using thresholded CPR matrix of multichannel EEG signals showed clear differences in the number and pattern of connections in brain connectivity graph between epileptic seizure and pre-seizure. Corresponding brain headmaps provide meaningful insights about synchronization in the brain in those states. K-means clustering of connectivity parameters of CPR and linear correlation obtained from global epileptic seizure and pre-seizure showed significantly larger cluster centroid distances for CPR as opposed to linear correlation, thereby demonstrating the efficacy of CPR. The headmap in the case of focal epilepsy clearly enables us to identify the focus of the epilepsy which provides certain diagnostic value. Connectivity analysis on multichannel fMRI signals was performed using CPR matrix and graph theoretic analysis. Adjacency matrix was obtained from CPR matrices after thresholding it using statistical significance tests. Graph theoretic analysis based on communicability was performed to obtain community structures for awake resting and anesthetic sedation states. Concurrent behavioral data showed memory impairment due to anesthesia. Given the fact that previous studies have implicated the hippocampus in memory function, the CPR results showing the hippocampus within the community in awake state and out of it in anesthesia state, demonstrated the biological plausibility of the CPR results. On the other hand, results from linear correlation were less biologically plausible. In biological systems, highly synchronized and desynchronized systems are of interest rather than moderately synchronized ones. However, CPR is approximately a monotonic function of synchronization and hence can assume values which indicate moderate synchronization. In order to emphasize high synchronization/ desynchronization and de-emphasize moderate synchronization, a new method of Correlation Synchronization Convergence Time (CSCT) is proposed. It is obtained using an iterative procedure involving the evaluation of CPR for successive autocorrelations until CPR converges to a chosen threshold. CSCT was evaluated for 16 channel EEG data and corresponding contour plots and histograms were obtained, which shows better discrimination between synchronized and asynchronized states compared to the conventional CPR. This thesis has demonstrated the efficacy of RP technique and associated measures in characterizing various classes of biomedical signals. The results obtained are corroborated by well known physiological facts, and they provide physiologically meaningful insights into the functioning of the underlying biological systems, with potential diagnostic value in healthcare.

L’objectif de ce travail de thèse a été d’étudier la réactivité autonomique cardiaque à des stimulations aversives au cours du sommeil et les phénomènes pouvant la moduler. Pour ce faire, nous avons utilisé une technique d’analyse temps-fréquence de la variabilité du signal RR (inverse de la fréquence cardiaque), basée sur des transformées en ondelettes de ce signal, lors de stimuli nociceptifs chez des sujets sains et en réponse à des évènements respiratoires obstructifs chez des patients apnéiques. Notre première étude suggère que la réactivité autonomique cardiaque en réaction à des stimuli nociceptifs est dépendante d’une activation sympathique qui est préservée dans tous les stades du sommeil. De plus, bien que cette réactivité cardiaque soit présente même lorsque la stimulation ne donne pas lieu à une réaction d’éveil, elle est plus importante si la stimulation est suivie d’une réaction d’éveil cortical, et ceci quelque soit le stade de sommeil. La deuxième étude, réalisée chez des patients apnéiques, montre que la réactivité autonomique en réponse aux évènements respiratoires obstructifs est dépendante essentiellement de la réactivité sympathique qui est modulée par le processus de réaction d’éveil plutôt que par les stades de sommeil ou par la sévérité des évènements respiratoires. Enfin, la troisième étude révèle qu’un niveau d’activité sympathique cardiaque élevé avant les stimulations nociceptives ou pendant les évènements respiratoires obstructifs peut favoriser l’apparition de réactions d’éveil. En conclusion, nos résultats sont en faveur du maintien de la réactivité sympathique cardiaque à des évènements aversifs au cours du sommeil et ceci dans tous les stades de sommeil. Cette réactivité sympathique est essentiellement modulée par le processus qui mène à la réaction d’éveil cortical, processus auquel semble participer un niveau sympathique basal élevé / The aim of this work was to study cardiac autonomic reactivity to aversive stimulations during sleep and the phenomena that could modulate this reactivity. We used time-frequency method of RR intervals variability (or heart rate variability), based on wavelet transform during nociceptive stimulations in healthy subjects and obstructive respiratory events in apnoeic patients. Our first study showed that the cardiac autonomic reactivity to nociceptive stimulations is sympathetically-driven cardiac activation in reaction, and preserved during all sleep stages. Furthermore, albeit cardiac reactivity persisted even in the absence of arousals, it was higher when a cortical arousal followed the noxious stimulus whatever the sleep stages. Our second work showed, in apnoeic patients, that cardiac autonomic reactivity in response to obstructive respiratory events was also dependent on sympathetic reactivity, mainly modulated by arousal process rather than sleep stages or severity of respiratory events. At last, our third work showed that cardiac sympathetic level before nociceptive stimuli or during respiratory events could favour cortical arousal. In conclusion, cardiac sympathetic reactivity in response to aversive stimuli during sleep is preserved during all sleep stages. This sympathetic reactivity is modulated by arousal process rather than sleep stages or severity of respiratory events. Cardiac sympathetic activity during sleep could take part in arousal process, by favouring cortical arousal

La syncope est une perte brusque de conscience. Bien qu'elle ne soit pas généralement mortelle, elle présente un impact économique sur le système de soins et sur la vie personnelle de personnes en souffrant. L'objet de la présente étude est de réduire la durée du test clinique (environ 1 heure) et d'éviter aux patients de développer une syncope en la prédisant. L'ensemble de travail s'inscrit dans une démarche de datamining associant l'extraction de paramètres, la sélection des variables et la classification. Trois approches complémentaires sont proposées, la première exploite des méthodes d'analyse non-linéaires de séries temporelles extraites de signaux acquises pendant le test, la seconde s'intéresse aux relations cardiovasculaires en proposant des indices dans le plan temps-fréquence et la troisième, plus originale, prendre en compte leurs dynamiques temporelles. / Syncope is a sudden loss of consciousness. Although it is not usually fatal, it has an economic impact on the health care system and the personal lives of people suffering. The purpose of this study is to reduce the duration of the clinical test (approximately 1 hour) and to avoid patients to develop syncope by early predicting the occurrence of syncope. The entire work fits into a data mining approach involving the feature extraction, feature selection and classification. 3 complementary approaches are proposed, the first one exploits nonlinear analysis methods of time series extracted from signals acquired during the test, the second one focuses on time- frequency (TF) relation between signals and suggests new indexes and the third one, the most original, takes into account their temporal dynamics.

Indications are that autonomic under-arousal exists in children with ADHD. Published results are, however, controversial and few studies examine the relationship between the autonomic nervous system and focussed attention. In line with the indications of sympathetic under-arousal, patients with the disorder are treated with sympathomimetic stimulants such as Ritalin (methylphenidate). Since these medications stimulate the sympathetic nervous system, they possess the potential to influence cardiac function. The aims of this study were a) to assess autonomic nervous system functioning in 20 children with ADHD, as compared to controls, and to examine the effects of focussed attention and sympathomimetic medication on this system, b) to investigate cardiac functioning in 20 children with ADHD, as compared to controls, and to examine the effects of sympathomimetic medication on this system and c) to assess EEG functioning in children with ADHD, as compared to controls, and to examine the effects of sympathomimetic medication on this functioning. Children with ADHD were tested while they were stimulant-free and during a period in which they were on stimulant medication, while controls were tested once. Autonomic nervous system activity of the children was assessed at baseline and during focussed attention by means of heart rate variability (HRV) and skin conductivity. Attention was evoked by means of a program on the BioGraph Infiniti biofeedback apparatus, which is used specifically to train ADHD individuals to increase their attentive abilities. HRV was determined by time-domain, frequency-domain and Poincaré analysis of RR interval data. Skin conductivity was determined by BioGraph Infiniti biofeedback apparatus. Cardiac functioning of the children was assessed at baseline by means of blood pressure recordings and electrocardiograms (ECGs). Blood pressure was measured by means of a stethoscope and mercurial sphygmomanometer. ECGs were obtained by means of a Schiller CardioLaptop AT-110 ECG recorder using the standard 12-lead cable positioning for a resting ECG and parameters measured included HR, RR, QT, JT, QTc, JTc, QTd, JTd, QTcd and JTcd. EEG values were determined at baseline and during focussed attention by means of BioGraph Infiniti biofeedback apparatus. EEG values measured in this study included theta/beta ratios, theta/SMR ratios and thalpha, low alpha and high alpha power. The main findings of this study are that: <ul> <li>Stimulant-free ADHD children show a parasympathetic dominance of the sympathovagal balance relative to controls.</li> <li>Methylphenidate usage shifts the autonomic balance of children with ADHD towards normal levels; however a normal autonomic balance is not reached.</li> <li>Stimulant-free ADHD children exhibit a shift in the sympathovagal balance towards the sympathetic nervous system from baseline to focussed attention; however, methylphenidate abolishes this shift.</li> <li>Methylphenidate usage does not, in general, cause QTc or JTc prolongation but it may cause QTc or JTc prolongation in susceptible individuals.</li> <li>Children with ADHD can not be differentiated from normal children on the basis of theta/beta ratios, theta/SMR ratios or alpha power.</li> <li>Methylphenidate increases the level of centering in children with ADHD.</li> <li>Stimulant-free ADHD children display an alpha block from baseline to focussed attention; however, methylphenidate abolishes this alpha block.</li></ul> Copyright / Dissertation (MSc)--University of Pretoria, 2009. / Physiology / unrestricted

O propósito do presente estudo foi obter evidências de validade e reprodutibilidade dos limiares de variabilidade da frequência cardíaca (VFC) durante a corrida. Dezenove sujeitos homens, saudáveis e praticantes de corrida (30,4 ± 4,1 anos; 175,9 ± 6,4 cm; 74,3 ± 8,5 kg) foram submetidos a um teste progressivo máximo em esteira rolante com velocidade inicial 5 km.h-1 e incrementos de 1 km.h-1 a cada 3 minutos (1% de inclinação constante) até exaustão voluntária. Todos os indivíduos realizaram o reteste em um intervalo de tempo entre 48 horas e uma semana. Foram realizadas as medidas das trocas gasosas, do lactato sanguíneo e da VFC (plotagem de Poincaré). Os limiares aeróbio (LAe) e anaeróbio (LAn) foram determinados pelos limares de lactato, ventilatórios e da VFC. Para a comparação entre os métodos foi uitlizada ANOVA para medidas repetidas, acompanhada de teste de post hoc de Bonferroni. A reprodutibilidade das variáveis analisadas foram verificadas pela plotagem de Bland-Altman e pelo coeficiente de correlação intraclasse (CCI). Os resultados do presente estudo demonstraram que a velocidade correspondente ao segundo e terceiro modelos utilizados para se determinar o LA pela VFC não eram significativamente diferentes (p > 0,05) do primeiro limiar de lactato e ventilatório. Em relação ao LAn, não foram observadas diferenças significativas nas velocidades correspondentes ao LAn detectado pelos diferentes métodos (p > 0,05). Os valores do CCI estavam entre 0,69 a 0,80 (p < 0,001). Conclui-se que o LAe e o LAn podem ser identificados pela análise da VFC, desde que se utilize os procedimentos empregados na presente investigação / The aim of the present study was to obtain evidences of validity and reliability of the thresholds of heart rate variability (HRV). Nineteen male subjects, healthy and runners (30,4 ± 4,1 years; 175,9 ± 6,4 cm; 74,3 ± 8,5 kg) performed a progressive maximal test on a treadmill with initial velocity 5 km.h-1 e increases of 1 km.h-1 every 3 minutes (1% slope) until voluntary exhaustion. All subjects performed the retest at an interval of time between 48 hours and one week. It was measured gas exchange, blood lactate and heart rate variability (Poincaré plot). The aerobic threshold (AT) and anaerobic (AnT) were determined by lactate, ventilatory and heart rate variability. ANOVA for repeated measures and post-hoc test of Bonferroni was used to compare the methods. To analyze the reproducibility of the variables were used the Bland- Altman plots and intraclass correlation coefficient (ICC). The results of this study show that the velocity at the second and third models employed to determine the AT by HRV were not significantly different (p > 0.05) of the first lactate threshold and ventilatory. Similarly, there were no significant differences in the velocities corresponding to AnT detected by different methods (p> 0.05). The ICC values were between 0.69 to 0.80 (p < 0.001). We conclude that the AT and the AnT can be estimated by HRV analysis, since it utilizes the procedures employed in this study

Submitted by Nadir Basilio (nadirsb@uninove.br) on 2018-07-19T19:15:24Z No. of bitstreams: 1 Mário César Nascimento.pdf: 1745805 bytes, checksum: ad4c8a4e2dc9ca8de775e2bd0ca30068 (MD5) / Made available in DSpace on 2018-07-19T19:15:24Z (GMT). No. of bitstreams: 1 Mário César Nascimento.pdf: 1745805 bytes, checksum: ad4c8a4e2dc9ca8de775e2bd0ca30068 (MD5) Previous issue date: 2017-12-15 / The objective of the present study was to evaluate the impact of the level of physical activity and overweight in offspring of normotensives or hypertensives, as well as to validate a scale of prediction of adherence to physical activity. This thesis was divided into two studies. In Study I, we observed that among the twenty items on the adherence scale, ten presented good reproducibility (Kappa> 0.70, Pearson's correlation> 0.81), good internal consistency (Cronbach's Alpha 0.84), good clarity and discriminant validity (p = 0.0006 vs sedentary, t = 4.12), correlation between the sum of the scale and the Mets (metabolic equivalent) evaluated by IPAQ with r = 0.073 and p = 0.048. In Study II, 114 males, young, physically active and insufficiently active adults, offspring of normotensives or hypertensives, overweight or eutrophic were selected. The IPAQ was used for the level of physical activity, the PSS-10 for perceived stress, the WHOQOL for quality of life analysis. Anthropometric, hematological and biochemical analyzes and systemic oxidative stress evaluations were performed. In addition, blood pressure (BP) recording beat-to-beat using the Finometer® was used for evaluation of hemodynamic parameters and of heart rate (HRV) and BP variability (BPV). The results showed a higher BMI and % of fat, both by folds and Bioelectrical impedance analysis, in the overweight groups compared to the eutrophic groups, as well as higher weekly caloric expenditure among the active groups in relation to the sedentary groups, independently of the familial history of hypertension (FHH). In the hematological and biochemical profile all groups presented values within the normal range. The BP values were similar between the studied groups, but a lower heart rate was observed in the active groups with a negative FHH. There was no difference in perceived stress levels, but the quality of life was better in the active groups, with lower benefits in the group with a positive FHH. In relation to HRV, the active eutrophic groups, both with a positive and negative FHH, had higher values of RMSSD (cardiac parasympathetic modulation) and lower sympatho/vagal balance in relation to their respective eutrophic sedentary groups, which was not observed in overweight groups. The groups with a positive FHH presented higher values of both simpato/vagal balance (eutrophic and overweight), SAP variance (just overweight) and vascular sympathetic modulation (LF) (eutrophic and overweight) compared to the group with negative FHH, and these differences were attenuated in the physically active group with FHH and overweight. The active eutrophic group with a negative FHH presented better baroreflex sensitivity in relation to their respective sedentary group, which was not observed in the group with a FHH. With regard to oxidative stress, active groups with a negative FHH had lower levels of hydrogen peroxide and nitrites and greater activity of the antioxidant enzyme glutathione peroxidase (just eutrophic) when compared to their respective sedentary groups, which was not observed for the offspring of hypertensives (sedentary vs actives). In addition, these two parameters and the oxidation of proteins (carbonyls) were increased in the overweight and non-overweight groups with a FHH in relation to the eutrophic group with a negative FHH, being attenuated in the active group with FHH and overweight. In conclusion, the scale of adherence to the physical active developed in this study showed good reproducibility, good internal consistency, clarity and discriminating validity. In addition, our results showed that even under normal clinical conditions, a positive FHH, regardless of the presence of overweight, induced autonomic dysfunction and increases in oxidative stress markers that may be precursors of cardiometabolic diseases in this genetically predisposed population. On the other hand, a physically active lifestyle improves HRV, baroreflex and parameters related to redox status in individuals with a negative FHH. Such benefits seem to be attenuated by the positive FHH, but a physically active lifestyle seems to prevent/attenuate the dysfunctions observed in this condition. / O objetivo do presente estudo foi avaliar o impacto do nível de atividade física e do sobrepeso em filhos de pais normotensos ou hipertensos, bem como validar uma escala de predição da aderência a atividade física. Esta tese foi dividida em dois estudos. No Estudo I, nossos resultados demonstram que entre os vinte itens da escala de aderência, dez apresentaram boa reprodutibilidade (Kappa > 0,70, correlação de Pearson >0,81), boa consistência interna (Alfa de Cronbach 0,84), boa clareza e validade discriminante (ativos p=<0,0006 vs. Sedentários; t= 4,12), Correlação entre o somatório da escala e o Mets (equivalente metabólico) avaliado pelo IPAQ com r=0,073 e p=0,048. No Estudo II, foram selecionados 114 sujeitos do sexo masculino, adultos jovens, fisicamente ativos e insuficientemente ativos, filhos biológicos de pais normotensos ou hipertensos, com sobrepeso ou eutróficos. Foram utilizados o IPAQ para o nível de atividade física, o PSS-10 para estresse percebido, e o WHOQOL para qualidade de vida. Foram realizadas análises antropométrica, hematológicas e bioquímicas sanguínea e de estresse oxidativo sistêmica, além de registro da pressão arterial (PA) batimento-a-batimento utilizando o Finometer® para avaliação de parâmetros hemodinâmicos e avaliação da variabilidade da frequência cardíaca (VFC) e da PA (VPA). Os resultados evidenciaram conforme esperado maior IMC e %G tanto por dobras quanto por bioimpedância, nos grupos com sobrepeso em relação aos eutróficos, bem como maior gasto calórico semanal entre os grupos ativos em relação aos grupos sedentários, independentemente do histórico familiar de hipertensão (HFH). No perfil hematológico e bioquímico sanguíneo todos os grupos apresentaram valores dentro da faixa de normalidade. Os valores de PA foram semelhantes entre os grupos estudados, porém foi observada menor frequência cardíaca nos grupos ativos com histórico negativo de hipertensão. Não houve diferença para níveis de estresse percebido, mas a qualidade de vida foi melhor nos grupos ativos, com menores benefícios no grupo com HFH positivo. Em relação a VFC, os grupos eutróficos ativos, tantos com HFH positivo quanto negativo, apresentaram valores maiores de RMSSD (modulação parassimpática cardíaca) e menores de balanço simpato/vagal em relação aos seus respectivos grupos sedentários eutróficos, o que não foi observado nos grupos com sobrepeso. Os grupos com HFH apresentaram maior balanço simpato/vagal que os eutróficos com HFH negativo. Quanto a VPA, os grupos com HFH positivo, eutrófico e com sobrepeso, apresentaram valores maiores tanto de variância de PAS quanto modulação simpática vascular (LF) em comparação ao grupo sem HFH, e essas diferenças foram atenuadas no grupo fisicamente ativo. O grupo de eutrófico ativo com HFH negativo apresentou melhor sensibilidade barorreflexa em relação ao seu respectivo grupo sedentário, o que não foi observado no grupo entre os sujeitos com HFH positivo. Com relação ao estresse oxidativo, os grupos ativos com HFH negativo apresentaram menores níveis de peróxido de hidrogênio e nitritos e maior atividade da enzima antioxidante glutationa peroxidase quando comparados aos seus respectivos grupos sedentários, o que não foi observado para os filhos de pais hipertensos. Além disto, estes dois parâmetros e a oxidação de proteínas (carbonilas) estavam aumentados nos grupos com e sem sobrepeso com HFH positivo em relação ao grupo eutrófico com HFH negativo, sendo atenuadas no grupo ativo com HFH positivo e sobrepeso. Em conclusão, a escala de aderência ao exercício desenvolvida neste estudo apresentou boa reprodutibilidade, boa consistência interna, clareza e validade descriminante. Além disto, os resultados evidenciam que mesmo sob condições clínicas de normalidade, o HFH positivo, independentemente da presença de sobrepeso, induz disfunção autonômica e aumento de marcadores de estresse oxidativo que podem ser precursores de doenças cardiometabólicas nesta população geneticamente predisposta. Por outro lado, um estilo de vida fisicamente ativo melhora a VFC, o baroreflexo e parâmetros relacionados ao estado redox em indivíduos com HFH negativo. Tais benefícios parecem atenuados pelo HFH positivo, mas um estilo de vida fisicamente ativo parece prevenir/atenuar as disfunções observadas nesta condição.

Nearly all functional magnetic resonance imaging (fMRI) studies are conducted in the supine body posture, which has been discussed as a potential confounder of such examinations. The literature suggests that cognitive functions, such as problem solving or perception, differ between supine and upright postures. However, the effect of posture on many cognitive functions is still unknown. Therefore, the aim of the present study was to investigate the effects of body posture (supine vs. sitting) on one of the most frequently used paradigms in the cognitive sciences: the N-back working memory paradigm. Twenty-two subjects were investigated in a randomized within-subject design. Subjects performed the N-back task on two consecutive days in either the supine or the upright posture. Subjective sleep quality and chronic stress were recorded as covariates. Furthermore, changes in mood dimensions and heart rate variability (HRV) were assessed during the experiment. Results indicate that the quality of sleep strongly affects reaction times when subjects performed a working memory task in a supine posture. These effects, however, could not be observed in the sitting position. The findings can be explained by HRV parameters that indicated differences in autonomic regulation in the upright vs. the supine posture. The finding is of particular relevance for fMRI group comparisons when group differences in sleep quality cannot be ruled out.

Background: Unemployment may impair mental and physical health. The influencing factors causing such negative effects are relevant from an individual and public health perspective. The personality as one possible influencing factor was discussed. This study investigated the prevalence of the type-D personality in an unemployed population and its connections to socio-demographic, psychological and heart rate variability (HRV) parameters. Methods: A questionnaire set including socio-demographics, type-D scale (DS14), Complaint list (BL), Beck-Depression-Inventory II (BDI-II) and the General Self-Efficacy Scale (GSE) was handed out to 203 unemployed individuals [126 females, mean age ± SD: 42.36 ± 11.08]. For HRV assessment (RMSSD), a subsample of 83 participants [50 females, median age ± IQR: 47.00 ± 17.00] passed the “stress-tests” (timed breathing, d2-attention-stress-test, math test) while heart frequency (HF) was acquired via the Stressball software (BioSign GmbH, Ottenhofen, Germany). Results: 53% of the unemployed had a type-D personality. Compared to non-type-D individuals, type-D individuals had rarely children and by trend a lower educational level; they showed significantly higher scores in the BDI-II and lower scores in the GSE and BL. No differences were observed in mean HF or RMSSD during all the stress-tests. Conclusion: The HRV of individuals with a type-D personality is no worse than that of individuals without a type-D personality. Type-D personality was significantly associated with negative health effects regarding depressiveness, self-efficacy and physical complaints. Our main findings implicate that the DS14 could serve as a short and reliable screening instrument to select concerned unemployed individuals who might be at risk for negative health effects for adequate intervention.