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GENDER DIVING BRADYCARDIA DIFFERENCES: A MACHINE LEARNING STUDY

dc.contributor.authorRey Paredes, Marta
dc.date.accessioned2023-07-21T10:00:16Z
dc.date.available2023-07-21T10:00:16Z
dc.date.issued2023-07-20
dc.identifier.urihttps://hdl.handle.net/10115/23439
dc.descriptionTrabajo Fin de Grado leído en la Universidad Rey Juan Carlos en el curso académico 2022/2023. Directores/as: Francisco Suárez Castro, Óscar Barquero Pérez
dc.description.abstractWhen we dive at full lung capacity (apnea) and put our face in the water, our autonomic nervous system is activated, making our heart beat slower. This mechanism is known as the diving reflex and serves to keep our body from consuming so much oxygen, since we cannot get it from the air underwater. This is a highly developed reflex in diving animals such as whales,and seals. This reflex occurs among terrestrial animals, such as the human species, when we put our face in water, holding our breath for a few seconds. In our species, there are and are being described differences in the functioning of the nervous system, as well as in the functioning of the heart, and differences between men and women. This project aims to investigate the gender differences in diving bradycardia and to develop a classification model to discriminate data between male and female subjects.
dc.language.isoeng
dc.publisherUniversidad Rey Juan Carlos
dc.rights
dc.rights.uri
dc.subjectDiving reflex
dc.subjectBradycardia
dc.subjectApnea
dc.subjectRR interval
dc.subjectHeart rate variability
dc.subjectMachine Learning
dc.subjectInterpretability
dc.titleGENDER DIVING BRADYCARDIA DIFFERENCES: A MACHINE LEARNING STUDY
dc.typeinfo:eu-repo/semantics/studentThesis
dc.rights.accessRightsinfo:eu-repo/semantics/embargoedAccess


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