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Digital Signal and Image Processing For Autonomic Nervous System Function Evaluation

dc.contributor.authorEl Yaagoubi, Mohammed
dc.date.accessioned2021-10-28T14:44:53Z
dc.date.available2021-10-28T14:44:53Z
dc.date.issued2020
dc.identifier.urihttp://hdl.handle.net/10115/18277
dc.descriptionTesis Doctoral leída en la Universidad Rey Juan Carlos de Madrid en 2020. Directores de la Tesis: Rebeca Goya Esteban y Younes Jabrane. Tutor: José Luis Rojo Álvarezes
dc.description.abstractThe autonomic nervous system regulates certain automatic body functions, such as smooth muscles, digestion, breathing, heart muscles, or certain glands. In this way, it allows the maintenance of the body's internal homeostasis. The autonomic nervous system is divided into the sympathetic nervous system and the parasympathetic nervous system, which sympathetically control the most frequent antagonistic actions through di erent neurotransmitters, among which we nd norepinephrine and adrenaline (catecholamines) at the sympathetic level, while at the parasympathetic level we nd acetylcholine. On the other hand, the enteric nervous system regulates the digestive system, as well as motor and secretory activities. These three systems manage the activity of many organs, such as cardiac activity and blood vessels, lungs, digestive tract, bladder, dilation or contraction of the pupil of the eye, among many others. The recent boom in biomedical engineering lies largely in the use of digital signal and medical image processing techniques with the aim of nding new tools and solutions in many areas. In this Thesis, two speci c problems of biomedical engineering related to the autonomic nervous system have been selected: (1) in cardiology, we address the eld of heart rate variability (HRV) and the prevention of sudden cardiac death (SCD); (2) in neurology, we study iris pigmentation and its relationship with cluster headaches (CH). With respect to the rst area, the identi cation of patients at greater risk of SCD has been extensively studied over the last few decades and several indices have been proposed based on the analysis of the electrocardiogram (ECG) stored in 1-day Holter records. Indices based on the non-linear dynamics of HRV variability have been shown to convey predictive information in terms of factors related to cardiac regulation by the autonomic nervous system, and among these, multiscale methods aim to provide more complete descriptions than measures based on individual scales. However, there is limited knowledge about the suitability of non-linear measurements to characterize cardiac dynamics in current monitoring scenarios over a period of several days. As for the second area, the di culty in diagnosing CH among the di erent types of pathological headaches leads to the need to investigate methods that help diagnosis and thus improve the administration of speci c treatment for them. The newborn human being has an indeterminate iris colour and the iris is coloured during the rst months of life. The nal color is inherited and determines the progressive pigmentation, which is culminated in the rst months of life by the activity of the pigmenting cells (melanophores). The sympathetic nervous system exerts a trophic action on the activity of the melanophores. When there is a congenital or acquired sympathetic defect in the neonatal period, there is a de cit of pigmentation in the iris on the side of the sympathetic hypofunction. The result is heterochromia, that is, the individual has one eye of each color, typically one blue eye and the other brown, with the light eye being the one that is defective in pigmentation. Heterochromia with clear color di erence is easily recognized with the naked eye. However, if the di erence is subtle, a sensitive method is required to recognize it.es
dc.language.isoenges
dc.publisherUniversidad Rey Juan Carloses
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectInformáticaes
dc.titleDigital Signal and Image Processing For Autonomic Nervous System Function Evaluationes
dc.typeinfo:eu-repo/semantics/doctoralThesises
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.subject.unesco1203.17 Informáticaes


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Attribution-NonCommercial-NoDerivatives 4.0 InternacionalExcept where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional