Modulação autonômica cardíaca na distrofia muscular de Duchenne durante tarefa no computador

Introdução: A Distrofia Muscular de Duchenne (DMD) é caracterizada como uma fraqueza muscular progressiva que leva à incapacidade. Devido às dificuldades funcionais enfrentadas pelos indivíduos com DMD, o uso da tecnologia assistiva é essencial para proporcionar ou promover habilidades funcionais. Na DMD, além do comprometimento musculoesquelético, uma disfunção autonômica cardíaca também tem sido relatada. Assim, visamos investigar as respostas autonômicas agudas de indivíduos com DMD durante a realização de uma tarefa no computador. Método: A variabilidade da frequência cardíaca foi avaliada através de métodos lineares e não lineares, utilizando uma cinta torácica com equipamento de monitoramento de eletrocardiograma (ECG). Assim, 45 indivíduos foram incluídos no grupo com DMD e 45 no grupo de desenvolvimento típico (controle), avaliados for 20 minutos em repouso sentado e 5 minutos com a realização de uma tarefa no computador. Resultados: Os indivíduos com DMD apresentaram menor modulação cardíaca parassimpática durante o repouso, que diminuiu ainda mais durante a tarefa no computador. Conclusão: Indivíduos com DMD exibiram respostas autonômicas cardíacas mais intensas durante a tarefa no computador

Impact of artifact correction methods on R-R interbeat signals to quantifying heart rate variability (HRV) according to linear and nonlinear methods.

In the analysis of heart rate variability (HRV) are used temporal series that contains the distances between successive heartbeats in order to assess autonomic regulation of the cardiovascular system. These series are obtained from the electrocardiogram (ECG) signal analysis, which can be affected by different types of artifacts leading to incorrect interpretations in the analysis of the HRV signals. Classic approach to deal with these artifacts implies the use of correction methods, some of them based on interpolation, substitution or statistical techniques. However, there are few studies that shows the accuracy and performance of these correction methods on real HRV signals. This study aims to determine the performance of some linear and non-linear correction methods on HRV signals with induced artefacts by quantification of its linear and nonlinear HRV parameters. As part of the methodology, ECG signals of rats measured using the technique of telemetry were used to generate real heart rate variability signals without any error. In these series were simulated missing points (beats) in different quantities in order to emulate a real experimental situation as accurately as possible. In order to compare recovering efficiency, deletion (DEL), linear interpolation (LI), cubic spline interpolation (CI), moving average window (MAW) and nonlinear predictive interpolation (NPI) were used as correction methods for the series with induced artifacts. The accuracy of each correction method was known through the results obtained after the measurement of the mean value of the series (AVNN), standard deviation (SDNN), root mean square error of the differences between successive heartbeats (RMSSD), Lomb\'s periodogram (LSP), Detrended Fluctuation Analysis (DFA), multiscale entropy (MSE) and symbolic dynamics (SD) on each HRV signal with and without artifacts. The results show that, at low levels of missing points the performance of all correction techniques are very similar with very close values for each HRV parameter. However, at higher levels of losses only the NPI method allows to obtain HRV parameters with low error values and low quantity of significant differences in comparison to the values calculated for the same signals without the presence of missing points.