Lina María Sepúlveda-Cano

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Heart rate variability (HRV) is one of the promising directions for a simple and noninvasive way for obstructive sleep apnea syndrome detection. The time-frequency representations has been proposed before to investigate the non-stationary properties of the HRV during either transient physiological or pathological episodes. Within the framework of the(More)
Photopletysmography signal has been developed for monitoring of Obstructive Sleep Apnoea, in particular, whenever an apneic episode occurs, that is reflected by decreases in the photopletysmography signal amplitude fluctuation. However, other physiological events such as artifacts and deep inspiratory gasp produce sympathetic activation, being unrelated to(More)
This paper presents a methodology for Obstructive Sleep Apnea (OSA) detection based on the HRV analysis, where as a measure of relevance PLS is used. Besides, two different combining approaches for the selection of the best set of contours are studied. Attained results can be oriented in research focused on finding alternative methods minimizing the(More)
Heart rate variability (HRV) is one of the promising directions for a simple and noninvasive way for obstructive sleep apnea syndrome detection (OSA). The interaction between the sympathetic and parasympathetic systems on the HRV recordings, gives rise to several non-stationary components added to the signal. Aiming to improve the classifier accuracy for(More)
The indirect extraction of respiratory frequency during exercise testing is very interesting and challenging. In this work we propose a method to estimate respiratory frequency during exercise testing from heart rate variability (HRV) analysis. Empirical mode decomposition is first applied to HRV signal to obtain the intrinsic mode functions (IMF). The(More)
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