Use of Meixner functions in estimation of Volterra kernels of nonlinear systems with delay

Volterra series representation of nonlinear systems is a mathematical analysis tool that has been successfully applied in many areas of biological sciences, especially in the area of modeling of hemodynamic response. In this study, we explored the possibility of using discrete time Meixner basis functions (MBFs) in estimating Volterra kernels of nonlinear systems. The problem of estimation of Volterra kernels can be formulated as a multiple regression problem and solved using least squares estimation. By expanding system kernels with some suitable basis functions, it is possible to reduce the number of parameters to be estimated and obtain better kernel estimates. Thus far, Laguerre basis functions have been widely used in this framework. However, research in signal processing indicates that when the kernels have a slow initial onset or delay, Meixner functions, which can be made to have a slow start, are more suitable in terms of providing a more accurate approximation to the kernels. We, therefore, compared the performance of Meixner functions, in kernel estimation, to that of Laguerre functions in some test cases that we constructed and in a real experimental case where we studied photoreceptor responses of photoreceptor cells of adult fruitflies (Drosophila melanogaster). Our results indicate that when there is a slow initial onset or delay, MBF expansion provides better kernel estimates

Parametric Complexity Reduction of Discrete-Time Linear Systems Having a Slow Initial Onset or Delay

This paper is concerned with an optimal expansion of linear discrete time systems on Meixner functions. Many orthogonal functions have been widely used to reduce the model parameter number such as Laguerre functions, Kautz functions and orthogonal basis functions. However, when the system has a slow initial onset or delay, Meixner functions, which have a slow start, are more suitable in terms of providing a more accurate approximation to the system. The optimal approximation of Meixner model is ensured once the pole characterizing the Meixner functions is set to its optimal value. In this paper, a new recursive representation of Meixner model is proposed. Further we propose, from input/output measurements, an iterative pole optimization algorithm of the Meixner pole functions. The method consists in applying the Newton-Raphson’s technique in which their elements are expressed analytically by using the derivative of the Meixner functions. Simulation results show the effectiveness of the proposed optimal modeling method

Fly Photoreceptors Encode Phase Congruency

More than five decades ago it was postulated that sensory neurons detect and selectively enhance behaviourally relevant features of natural signals. Although we now know that sensory neurons are tuned to efficiently encode natural stimuli, until now it was not clear what statistical features of the stimuli they encode and how. Here we reverse-engineer the neural code of Drosophila photoreceptors and show for the first time that photoreceptors exploit nonlinear dynamics to selectively enhance and encode phase-related features of temporal stimuli, such as local phase congruency, which are invariant to changes in illumination and contrast. We demonstrate that to mitigate for the inherent sensitivity to noise of the local phase congruency measure, the nonlinear coding mechanisms of the fly photoreceptors are tuned to suppress random phase signals, which explains why photoreceptor responses to naturalistic stimuli are significantly different from their responses to white noise stimuli

Solution Approximation for Atmospheric Flight Dynamics Using Volterra Theory

This dissertation introduces a set of novel approaches in order to facilitate and enrich Volterra theory as a nonlinear approximation technique for constructing mathematical solutions from the governing relationships describing aircraft dynamic behavior. These approaches reconnect Volterra theory and flight mechanics research, which has not been addressed in the technical literature for over twenty years. Volterra theory is known to be viable in modeling weak nonlinearities, but is not particularly well suited for directly describing high performance aircraft dynamics. In order to overcome these obstacles and restrictions of Volterra theory, the global Piecewise Volterra Approach has been developed. This new approach decomposes a strong nonlinearity into weaker components in several sub-regions, which individually only require a low order truncated series. A novel Cause-and-Effect Analysis of these low order truncated series has also been developed. This new technique in turn allows system prediction before employing computer simulation, as well as decomposition of existing simulation results. For a computationally complex and large envelope airframe system, a Volterra Parameter-Varying Model Approach has also been developed as a systematically efficient approach to track the aircraft dynamic model and its response across a wide range of operating conditions. The analytical and numerical solutions based on the proposed methodology show the ability of Volterra theory to help predict, understand, and analyze nonlinear aircraft behavior beyond that attainable by linear theory, or more difficult to extract from nonlinear simulation, which in turn leads to a more efficient nonlinear preliminary design tool

Nonlinear stochastic system identification techniques for biological tissues/

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 205-212).This research develops a device capable of measuring the nonlinear dynamic mechanical properties of human tissue in vivo. The enabling technology is the use of nonlinear stochastic system identification techniques in conjunction with a high bandwidth actuator to perturb the tissue. The desktop and handheld instruments used for this investigation were custom-built Lorentz force actuators which were able to measure the dynamic compliance between the input force and the output displacement. The actuators have a nominal stroke of 32 mm and were actuated with forces under 15 N. The design includes custom electronics and user software which collects and analyses the information. This research also explores nonlinear stochastic system identification techniques that would be applicable to biological tissues. Several system identification techniques were used including linear, Wiener static nonlinear, Volterra kernel and partitioning techniques. Real time system identification and real time input generation schemes are also implemented. The mathematical formulation and implementation details of these techniques are also discussed. It was found that a simple linear stochastic system identification technique had a variance accounted for (VAF) of 70 to 75 %. More complicated representations using Volterra kernels or partitioning techniques had a VAF of 90 to 97 %. More complex nonlinear system identification techniques can not only capture more of the nonlinear dynamics but also capture those dynamics in an interpretable way. Indentation, extension, and surface mechanics experiments were conducted to investigate the nonlinear mechanical compliance of skin in vivo. The techniques and devices used in this research can be applied directly to consumer product efficacy analysis, medical diagnosis as well as research in biomechanical tissues.by Yi Chen.S.M

Quantitative analysis of the autonomic nervous system : toolbox development and application

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2017.A dinâmica entre a PA e a FC é de malha fechada, na qual a PA influencia a FC através do baroreflexo e a FC influencia a PA através da dinâmica circulatória. A respiração exerce uma influência direta sobre a FC que é mediada pelo SNA, chamada de acoplamento cardiorrespiratório (ACR), e também um efeito mecânico indireto mediado pelo baroreflexo. Enquanto análises espectrais univariáveis e bivariáveis podem ser usadas para avaliar esses mecanismos, são técnicas de malha aberta que são incapazes de diferenciar efeitos de retroalimentação dos efeitos de alimentação direta e também de separar o ACR das influências indiretas da respiração na FC. Para lidar com essas limitações, uma abordagem de identificação de sistemas foi aplicada. O CRSIDLab implementa três modelos: o modelo AR com entradas exógenas (ARX), o modelo de funções de base de Laguerre (FBL) e o modelo de funções de base de Meixner (FBM). As respostas ao impulso, que caracterizam a dinâmica entre cada par de variáveis, são calculadas a partir do modelo estimado. Esses modelos são capazes de isolar o ACR ao considerar ambos VPI e PAS como entradas e conseguem abrir a malha do baroreflexo computacionalmente pela imposição de atrasos entre a PAS e o IRR, caracterizando a resposta ao impulso do baroreflexo arterial (BRA). A partir dessas análises, não só o ganho em cada banda de frequência é fornecido através da transformada de Fourier da resposta ao impulso, mas também informações temporais como o atraso entre duas variáveis. Os resultados mostram que ficar de pé é acompanhado por uma supressão vagal e tom vascular simpático aumentado. Análises de correlação mostraram que as estimativas de ASR e SBR baseadas em análises espectrais não apresentam a mesma informação que as estimativas baseadas no modelo de ACR e BRA. As diferenças encontradas sugerem que as análises baseadas em modelo são efetivas em representar o ACR como uma medida dos efeitos diretos da respiração na FC e o BRA como expressão do baroreflexo independente da dinâmica circulatória. Assim, o CRSIDLab é uma ferramenta poderosa para a determinação não-invasiva de diferentes indicadores quantitativos do SNA. Os resultados mostram que os indicadores estimados refletem a fisiologia subjacente, pois ficar de pé é um estímulo simpático que deveria levar a supressão vagal, conforme observado. Os resultados obtidos também mostram que a abordagem de modelagem de sistemas multivariáveis pode fornecer importantes informações adicionais àquelas encontradas pelas abordagens espectrais mais tradicionais, podendo levar a indicadores quantitativos mais específicos do SNA.Fundação de Apoio à Pesquisa do Distrito Federal (FAP-DF).The autonomic nervous system (ANS) controls the involuntary functions of the body and its imbalance has been linked to increased risk of cardiac mortality. Heart rate variability (HRV) analysis is usually employed as a non-invasive method for assessing ANS modulation. Traditional measures of HRV are based on the analysis of the beat-to-beat oscillations in heart rate (or its reciprocal, the interval between consecutive R waves on the electrocardiogram - RRI), since heart rate (HR) rhythm is a consequence of sympathetic and parasympathetic activity on the sinoatrial node of the heart. However, these oscillations in beat-to-beat HR are also influenced by mechanisms, such as baroreflex and respiratory sinus arrhythmia (RSA), that affect HRV. Therefore, in this work, a multivariate analysis of the cardiorespiratory system is used. This study consists of two parts: the development of the cardiorespiratory system identification lab (CRSIDLab), a Matlab graphical user interface that provides quantitative indicators of ANS activity from a multivariate system model analysis of cardiorespiratory data, followed by its application on data obtained from subjects in supine and standing postures, illustrating its capabilities. Electrocardiogram (ECG), continuous blood pressure (BP) and airflow were recorded from 23 subjects in supine and standing postures for 10 min and preprocessed on CRSIDLab. In this work the classical HRV and BP variability (BPV) analyses were performed though power spectral density (PSD) analysis of the RRI and the systolic BP (SBP), respectively. CRSIDLab implements three methods for spectral analysis: the Fourier transform, Welch method and AR model. All methods were used to calculate the power of the low frequency (LF: 0.04-0.15 Hz) and high frequency (HF: 0.15-0.4 Hz) bands, as the areas under the PSD curve. For the HRV, the LF/HF ratio was also calculated. Traditional baroreflex sensitivity (BRS) estimates were calculated from the relation between HRV and BPV in the LF and HF regions. Spectral transfer functions were estimated between SBP and RRI, characterizing baroreflex, and between instantaneous lung volume (ILV, derived from the airflow record) and RRI, characterizing RSA, or the effects of respiration on HR, for the determination of the LF and HF gains. BRS was estimated from the gains of the transfer function between SBP and RRI.The dynamics between BP and HR are closed-loop, where BP influences HR through baroreflex and HR influences BP through circulatory dynamics. Respiration has a direct influence on HR that is mediated through the ANS, called the respiratory-cardiac coupling (RCC), and also a mechanical indirect effect mediated through baroreflex. While univariate and bivariate spectral analyses can be used to assess these effects, they are open-loop techniques that are unable to differentiate feedforward from feedback effects and also to separate RCC from the indirect effects of respiration on HR. To address these limitations a system model identification approach was applied. CRSIDLab implements three types of models: the autoregressive with exogenous inputs (ARX) model, the Laguerre basis function (LBF) model, and the Meixner basis function (MBF) model. The impulse responses, which characterize the dynamics between each pair of variables, are calculated from the estimated model. These multivariate models are able to isolate RCC by considering both SBP and ILV as system inputs and are able to computationally open the baroreflex loop through the imposition of time delays between SBP and RRI, characterizing the arterial baroreflex (ABR) impulse response. From this analysis not only the gain for each frequency band is provided from the Fourier transform of the impulse response, but also temporal information such as delays between variables. The results show that standing is accompanied by significant vagal withdrawal and increased sympathetic vascular tone. Correlation analyses showed that the spectral-based RSA and BRS estimates do not present the same information as the model-based RCC and ABR estimates. The differences found suggest the model-based analyses are effective in representing RCC as a measure of the direct effects of respiration on HR and ABR as an expression of baroreflex that is independent from circulatory dynamics. Thus, CRSIDLab is a powerful tool for the non-invasive determination of different quantitative indicators of the ANS. The results show that all estimated indicators reflect the underlying physiology, in the sense that standing is a sympathetic stimulus that should lead to vagal withdrawal, as observed. The results obtained also show that the multivariate system modeling approach can provide important additional information to those found by the more traditional spectral analyses approaches, which could potentially lead to more specific quantitative indicators of the ANS

Microsaccadic sampling of moving image information provides Drosophila hyperacute vision.

Small fly eyes should not see fine image details. Because flies exhibit saccadic visual behaviors and their compound eyes have relatively few ommatidia (sampling points), their photoreceptors would be expected to generate blurry and coarse retinal images of the world. Here we demonstrate that Drosophila see the world far better than predicted from the classic theories. By using electrophysiological, optical and behavioral assays, we found that R1-R6 photoreceptors' encoding capacity in time is maximized to fast high-contrast bursts, which resemble their light input during saccadic behaviors. Whilst over space, R1-R6s resolve moving objects at saccadic speeds beyond the predicted motion-blur-limit. Our results show how refractory phototransduction and rapid photomechanical photoreceptor contractions jointly sharpen retinal images of moving objects in space-time, enabling hyperacute vision, and explain how such microsaccadic information sampling exceeds the compound eyes' optical limits. These discoveries elucidate how acuity depends upon photoreceptor function and eye movements

Apneia obstrutiva do sono e sua influência no sistema nervoso

Trabalho de Conclusão Curso (graduação)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2018.A apneia do sono atinge uma parcela considerável da população e está ligada a riscos cardíacos como hipertensão e insuficiência cardíaca, além de uma má qualidade de vida dos pacientes que sofrem com a quebra constante da arquitetura do sono. O objetivo do trabalho é identificar os efeitos da apneia do sono no SNA, que possui um papel importante na regulação das funções involuntárias como frequência cardíaca e respiração. Tal estudo se dá por meio de duas abordagens que caracterizam o SNA: a VFC e a estimação de respostas ao impulso, utilizando dois modelos, o modelo ARX e o modelo LBF, com a finalidade de atender limitações da abordagem clássica da VFC. Utilizando uma base de dados de 8 pacientes segregados em dois grupos de acordo com seu grau de apneia do sono, foram realizados procedimentos de processamento de sinais nos registros de ECG e respiração utilizados. Os resultados indicam atividade simpática mais acentuada nos pacientes com SAOS e atividade vagal mais acentuada nos pacientes saudáveis.Sleep apnea affects a considerable part of the population and is related to several cardiac problems, such as high blood pressure and heart failure, in addition to a bad quality of life for the patients that suffer from constant interruptions in sleep architecture. The main objective of this study is to identify the effects of sleep apnea in the autonomic nervous system, a system that provides an important role in the regulation of involuntary actions such as heartbeat and respiration. This study is divided into two approaches used to measure the autonomic nervous system, the HRV and the estimation of impulse responses, itself estimated by two methods, the ARX model and the LBF model, to circumvent the limitations of the classic HRV method. With a database of 8 patients, clustered by the degree of sleep apnea into two groups, signal processing methods were applied to the biological signals analyzed, the ECG and the respiratory data. The results indicate an accentuated sympathetic activity in OSAS patients, and an accentuated parasympathetic activity in healthy patients

Sickle Cell Disease Subjects Have a Distinct Abnormal Autonomic Phenotype Characterized by Peripheral Vasoconstriction With Blunted Cardiac Response to Head-Up Tilt

In sickle cell disease (SCD), prolonged capillary transit times, resulting from reduced peripheral blood flow, increase the likelihood of rigid red cells entrapment in the microvasculature, predisposing to vaso-occlusive crisis. Since changes in peripheral flow are mediated by the autonomic nervous system (ANS), we tested the hypothesis that the cardiac and peripheral vascular responses to head-up tilt (HUT) are abnormal in SCD. Heart rate, respiration, non-invasive continuous blood pressure and finger photoplethysmogram (PPG) were monitored before, during, and after HUT in SCD, anemic controls and healthy subjects. Percent increase in heart rate from baseline was used to quantify cardiac ANS response, while percent decrease in PPG amplitude represented degree of peripheral vasoconstriction. After employing cluster analysis to determine threshold levels, the HUT responses were classified into four phenotypes: (CP) increased heart rate and peripheral vasoconstriction; (C) increased heart rate only; (P) peripheral vasoconstriction only; and (ST) subthreshold cardiac and peripheral vascular responses. Multinomial logistic regression (MLR) was used to relate these phenotypic responses to various parameters representing blood properties and baseline cardiovascular activity. The most common phenotypic response, CP, was found in 82% of non-SCD subjects, including those with chronic anemia. In contrast, 70% of SCD subjects responded abnormally to HUT: C-phenotype = 22%, P-phenotype = 37%, or ST-phenotype = 11%. MLR revealed that the HUT phenotypes were significantly associated with baseline cardiac parasympathetic activity, baseline peripheral vascular variability, hemoglobin level and SCD diagnosis. Low parasympathetic activity at baseline dramatically increased the probability of belonging to the P-phenotype in SCD subjects, even after adjusting for hemoglobin level, suggesting a characteristic autonomic dysfunction that is independent of anemia. Further analysis using a mathematical model of heart rate variability revealed that the low parasympathetic activity in P-phenotype SCD subjects was due to impaired respiratory-cardiac coupling rather than reduced cardiac baroreflex sensitivity. By having strong peripheral vasoconstriction without compensatory cardiac responses, P-phenotype subjects may be at increased risk for vaso-occlusive crisis. The classification of autonomic phenotypes based on HUT response may have potential use for guiding therapeutic interventions to alleviate the risk of adverse outcomes in SCD

Identificação de sistemas fisiológicos : técnicas univariáveis e multivariáveis

Trabalho de conclusão de curso (graduação)—Universidade de Brasília, Faculdade de Tecnologia, Curso de Graduação em Engenharia de Controle e Automação, 2019.Aplicando técnicas de identificação de sistemas é possível construir modelos capazes de representar o sistema cardiorrespiratório. A análise desses modelos fornece informações importantes em relação ao desempenho do sistema nervoso autônomo (SNA). Neste trabalho, foram analisados dados da respiração, da pressão arterial e dos batimentos cardíacos de pacientes em duas bases de dados: a Apnea-ECG Database, focada em pacientes com e sem apneia obstrutiva do sono e a Fantasia Database, cujos sinais são distribuídos entre grupos de jovens e idosos. Estes sinais foram, então, utilizados para a obtenção de índices para caracterização do funcionamento do SNA. A primeira técnica implementada para avaliação do comportamento do SNA foi a análise da variabilidade da frequência cardíaca (VFC) a partir da densidade espectral de potência (DEP) do sinal de intervalos RR (RRI, do inglês R-R Interval) nas regiões de baixa (LF) e alta (HF) frequência. No entanto, a análise tradicional da VFC possui uma desvantagem: a influência da respiração sobre o RRI. Esta influência da respiração é independente da atividade do SNA, logo, pode prejudicar sua correta avaliação. Para contornar este problema, o sinal RRI foi decomposto em duas componentes, uma componente correlacionada a respiração e outra não correlacionada. A componente do RRI não correlacionada a respiração foi utilizada para análise da VFC. Além disso, também foram analisados os resultados para a resposta ao impulso de sistemas com a respiração ou a pressão arterial como entrada e com o RRI como saída (foram construídos sistemas com o RRI original como saída e também com o componente do RRI não correlacionado a respiração como saída). Ao contrário da análise VFC pela DEP, que envolve a análise de uma única variável, o RRI; a resposta ao impulso aplica um modelo multivariável que permite a estimação das relações dinâmicas que conectam alterações na respiração e na pressão a flutuações no RRI. Nesta técnica, foram obtidos os índices magnitude da resposta ao impulso (IRM) e ganhos dinâmicos na faixa de alta (HF) e baixa (LF) frequência. Os resultados da Apnea-ECG Database obtidos pelas análise da VFC não apontaram uma diferença estatística entre os grupos de estudo. Porém, o valor médio do parâmetro HF foi consideravelmente menor nos pacientes apneicos. Para esta base de dados, a remoção da influência da respiração sobre o RRI não alterou significativamente os resultados obtidos a partir da VFC. Já para a resposta ao impulso, no modelo LBF, percebeu-se uma diferença significativa entre os grupos ao analisar o parâmetro IRM. Porém, após a remoção da influência da respiração sobre o RRI, o IRM foi capaz de distinguir os grupos em todos os modelos. Este resultado sugere que os índices obtidos após a remoção da influência da respiração são mais sensíveis à detecção de alterações no SNA. Além disso, notou-se que a média do índice IRM foi menor no grupo de apneicos. Os valores reduzidos do IRM e HF em pacientes apneicos indicam uma atenuação na modulação vagal dos mesmos. Para os pacientes da Fantasia Database, os parâmetros HF e LF foram capazes de distinguir os pacientes jovens e idosos nos dois métodos utilizados, Welch e AR, para análise do VFC. Além disso, após a remoção da influência da respiração, a razão LF/HF também apresentou significância estatística com o uso do método Welch. Dos resultados obtidos, observa-se que os pacientes idosos apresentaram LF e HF menores que os pacientes jovens. Como o parâmetro HF está associado à atividade vagal, este resultado indica que os voluntários idosos apresentaram uma atividade vagal reduzida quando comparado aos voluntários jovens, isto pode ser um efeito natural do processo de envelhecimento, visto que todos os voluntários desta base são saudáveis. Além disso, como LF pode ser uma medida da atividade simpática, estes resultados sugerem que os idosos também apresentam uma atividade simpática reduzida quando comparado aos voluntários jovens. Na análise da resposta ao impulso dos pacientes da Fantasia Database, foram considerados dois sistemas, um com a respiração como entrada e outro em que a pressão arterial atua como entrada. Para estes sistemas, pelo menos um dos parâmetros IRM, DG-HF e DG-LF apontou diferenças estatisticamente significativas nos modelos discutidos. Ademais, os valores médios dos parâmetros IRM e DG-HF foram maiores no grupo de jovens nos dois sistemas simulados para esta base de dados. Estes resultados podem ser interpretados como uma indicação de maior atividade vagal em pacientes jovens.Applying techniques to identify systems, it is possible to construct models capable of representing the cardiorespiratory system. The analysis of these models provides important information regarding the performance of the autonomic nervous system (ANS). In this work, data on respiration, blood pressure and heart rate of patients were analyzed in two databases: the Apnea-ECG Database, focused on patients with and without obstructive sleep apnea, and Fantasy Database , whose signs are distributed among groups of young and old. These signals were then used to obtain indices to characterize the functioning of the ANS. The first technique implemented to evaluate the behavior of the SNA was the analysis of the heart rate variability (HRV) from the power spectral density (DEP) of the RR interval signal (RRI) in the regions low (LF) and high (HF) frequency. However, traditional HRV analysis has a drawback: the influence of breathing on RRI. This influence of breathing is independent of the activity of the ANS, therefore, it can impair its correct evaluation. To circumvent this problem, the RRI signal was decomposed into two components, one component correlated to respiration and the other uncorrelated. The non-respiratory correlated RRI component was used for HRV analysis. In addition, we also analyzed the results for the impulse response of systems with respiration or blood pressure as input and with RRI as output (systems were constructed with the original RRI as output and also with the RRI component not correlated to breath as output). Unlike the VFC analysis by DEP, which involves the analysis of a single variable, the RRI; the impulse response applies a multivariate model that allows the estimation of the dynamic relationships that connect changes in respiration and pressure to fluctuations in RRI. In this technique, the magnitude of impulse response (MRI) and dynamic gains in the high (HF) and low (LF) frequency bands were obtained. The results of the Apnea-ECG Database obtained by the HRV analysis did not indicate a statistical difference between the study groups. However, the mean value of the HF parameter was considerably lower in apneic patients. For this database, the removal of the influence of respiration on the RRI did not significantly alter the results obtained from the HRV. For the impulse response, in the LBF model, a significant difference was observed between the groups when analyzing the MRI parameter. However, after removing the influence of respiration on RRI, MRI was able to distinguish groups in all models. This result suggests that the indices obtained after the removal of the influence of respiration are more sensitive to the detection of changes in the ANS. In addition, it was noted that the mean MRI index was lower in the apneic group. Reduced values of MRI and HF in apneic patients indicate an attenuation in the vagal modulation of the same. For patients from Fantasy Database, the HF and LF parameters were able to distinguish the young and elderly patients in the two methods used, Welch and AR, for HRV analysis. In addition, after removing the influence of respiration, the LF/HF ratio also presented statistical significance with the use of the Welch method. From the results obtained, it can be observed that patients the elderly had lower LF and HF than the younger patients. As the HF parameter is associated with vagal activity, this result indicates that the elderly volunteers have a reduced vagal activity when compared to young volunteers, this may be a natural effect of the aging process, since all of the patients are healthy. In addition, since LF may be a measure of sympathetic activity, these results suggest that the elderly also have a reduced sympathetic activity when compared to young volunteers. In the analysis of patientsímpulse response of the Fantasy Database, two systems were considered, one with breathing as input and another where the blood pressure acts as input. For these systems, at least one of the IRM, DGHF and DGLF parameters pointed out statistically significant differences in the models discussed. In addition, the mean values of the MRI and DG-HF parameters were higher in the group of youngsters in the two simulated systems for this database. These results may be interpreted as an indication of increased vagal activity in young patients