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Monitoring vital signs at rest while using channel state information of wi-fi signals and artificial intelligence tools /

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dc.contributor.authorArmenta García, Jesús Albany
dc.contributor.codirectorIbarra Esquer, Jorge Eduardo dir.
dc.contributor.directorGonzález Navarro, Félix Fernando
dc.coverage.placeofpublicationMexicali Baja California.
dc.date.accessioned2022-07-11T22:05:52Z
dc.date.available2022-07-11T22:05:52Z
dc.date.created2022
dc.degree.deparmentUniversidad Autónoma de Baja California, Instituto de Ingeniería
dc.degree.grantorTesis de Maestría / master Thesis.
dc.degree.nameMaestría y Doctorado en Ciencias e Ingeniería
dc.description.abstractBreathing and heart rate are vital signs that might help identifying pathological conditions by its monitoring. This master’s thesis presents a system for monitoring breathing and heart rate, which combines con- ventional Channel State Information sensing approaches with Machine Learning techniques to provide a reliable monitoring. Also, a new sen- sitive subcarrier selection method, which is an important step for pro- cessing Channel State Information data, based on Hilbert Transform is presented. Along with the system’s description, this thesis provides the base theory for understanding each system’s component and the task that each component does. An exhaustive analysis was also performed and presented in order to understand Channel State Information data as well as the processing of data for vital signs monitoring. Results show that a reliable breathing rate monitoring can be achieved and raise questions about heart rate monitoring which are also answered in the same chapter.
dc.format.extent97 p. ; il.
dc.format.mimetypepdf
dc.identifier.urihttps://hdl.handle.net/20.500.12930/9032
dc.identifier.urihttps://doi.org/10.57840/uabc-45
dc.language.isospa
dc.relation.urlhttps://drive.google.com/file/d/18JPKlZalQQcSX3mgd6_S4552HBs20_4N/view?usp=sharing.
dc.rightsopenAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4
dc.subjectInteligencia artificial
dc.subjectTesis y disertaciones académicas
dc.subjectlemb
dc.subject.lccQ335 A75 2022
dc.titleMonitoring vital signs at rest while using channel state information of wi-fi signals and artificial intelligence tools /
dc.uabc.bibliographycNoteIncluye referencias bibliográficas
dc.uabc.bilbiotecaMEXICALI
dc.uabc.identifier250711
dc.uabc.numInventarioMXL123567
dc.uabc.typeMaterialTESIS
dspace.entity.typePublication
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