Análises da arritmia sinusal respiratória

Detalhes bibliográficos
Autor(a) principal: Ladeira, Guênia Mara Vieira
Data de Publicação: 2020
Tipo de documento: Tese
Idioma: por
Título da fonte: Repositório Institucional da UFU
Texto Completo: https://repositorio.ufu.br/handle/123456789/30697
http://doi.org/10.14393/ufu.te.2020.802
Resumo: Heart rate variability is essential for maintaining the homeostatic balance of the body. It is controlled by the autonomic nervous system. Human biological systems have standard basic characteristics, but varieties of construction and functioning due to genetics, age, sex, and also disease impairment. In addition, they have a complex relationship between systems, such as the nervous system and the cardiorespiratory system. Further analysis of a complex system reveals causes and consequences of its functioning, and helps to detect problems and solve them. Motivated by a better understanding of this relationship I will deepen the analysis of the systems to contribute to the research in this area. The efficiency of the autonomic regulation can be verified by means of respiratory sinus arrhythmia tests observed through electrocardiogram signals ECG and the response of the nervous system can be perceived by electroencephalogram EEG. In this work I present some approaches in the analysis of complex systems such as biological ones. The most relevant contributions of the research are prepared from the knowledge of the cardiorespiratory and nervous biological systems, and the direct relationship between them. The work was concerned with the quality of the instrumentation for biological signal collection and pre-processing for analysis. This stage generated the construction of electrocardiogram equipment. Then, ECG signals were collected from the paralympic boccia team, while the athletes performed their usual breathing exercises to improve concentration and alter heart rates. The electrocardiograms were analysed through the techniques of quantification of recurrence observing the details of the alterations during the exercises. Another approach of the research was the mathematical models of the electrocardiogram. The ECG models were studied and the Kaplan oscillator was chosen, whose model was analysed through bifurcation diagrams and improved in its results. How the athletes change the pattern of the heart and increase the concentration with the exercises. The work passed the EEG analysis stage. Several analyses were performed by linear and non-linear techniques, comparing the signals between the participant with open eyes and closed eyes. A new recurrence analysis technique in the frequency spectrum was generated in this part. The technique presented relevant results to better characterize the signals, can be used to characterize case of depression, and other diseases affecting the central nervous system. Data collection in set of ECG and EEG performing the breathing exercise were performed, the data were analysed by already established techniques and by the recurrence technique created here, we showed that there is a relationship between the heart and brain signals in performing the breathing exercises. All the stages of the work have generated articles which have been published, the first in congresses and the last in specialized journals.
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spelling Análises da arritmia sinusal respiratóriaAnalyses of respiratory sinus arrhythmiaAnálise de sistemas complexosAnálise de recorrência do espectro de frequênciaSinais elétricos do coraçãoSinais elétricos do sistema nervoso centralAnalysis of complex systemsAnalysis of recurrence of the frequency spectrumElectrical signals from the heartElectrical signals from the heartCNPQ::ENGENHARIAS::ENGENHARIA BIOMEDICACNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::MEDIDAS ELETRICAS, MAGNETICAS E ELETRONICAS INSTRUMENTACAO::INSTRUMENTACAO ELETRONICACNPQ::CIENCIAS EXATAS E DA TERRA::MATEMATICA::ANALISECNPQ::CIENCIAS EXATAS E DA TERRA::MATEMATICA::GEOMETRIA E TOPOLOGIASistema nervosoHomeostaseRespiraçãoCardiotocografiaHeart rate variability is essential for maintaining the homeostatic balance of the body. It is controlled by the autonomic nervous system. Human biological systems have standard basic characteristics, but varieties of construction and functioning due to genetics, age, sex, and also disease impairment. In addition, they have a complex relationship between systems, such as the nervous system and the cardiorespiratory system. Further analysis of a complex system reveals causes and consequences of its functioning, and helps to detect problems and solve them. Motivated by a better understanding of this relationship I will deepen the analysis of the systems to contribute to the research in this area. The efficiency of the autonomic regulation can be verified by means of respiratory sinus arrhythmia tests observed through electrocardiogram signals ECG and the response of the nervous system can be perceived by electroencephalogram EEG. In this work I present some approaches in the analysis of complex systems such as biological ones. The most relevant contributions of the research are prepared from the knowledge of the cardiorespiratory and nervous biological systems, and the direct relationship between them. The work was concerned with the quality of the instrumentation for biological signal collection and pre-processing for analysis. This stage generated the construction of electrocardiogram equipment. Then, ECG signals were collected from the paralympic boccia team, while the athletes performed their usual breathing exercises to improve concentration and alter heart rates. The electrocardiograms were analysed through the techniques of quantification of recurrence observing the details of the alterations during the exercises. Another approach of the research was the mathematical models of the electrocardiogram. The ECG models were studied and the Kaplan oscillator was chosen, whose model was analysed through bifurcation diagrams and improved in its results. How the athletes change the pattern of the heart and increase the concentration with the exercises. The work passed the EEG analysis stage. Several analyses were performed by linear and non-linear techniques, comparing the signals between the participant with open eyes and closed eyes. A new recurrence analysis technique in the frequency spectrum was generated in this part. The technique presented relevant results to better characterize the signals, can be used to characterize case of depression, and other diseases affecting the central nervous system. Data collection in set of ECG and EEG performing the breathing exercise were performed, the data were analysed by already established techniques and by the recurrence technique created here, we showed that there is a relationship between the heart and brain signals in performing the breathing exercises. All the stages of the work have generated articles which have been published, the first in congresses and the last in specialized journals.Pesquisa sem auxílio de agências de fomentoTese (Doutorado)A variabilidade da frequência cardíaca é essencial à manutenção do equilíbrio homeostáticos do corpo. Esta é controlada pelo sistema nervoso autônomo. Os sistemas biológicos humano têm características básicas padrão, mas variedades de construção e funcionamento devido à genética, à idade, ao sexo, e também comprometimentos por doenças. Além de terem relação complexa entre os sistemas, como acontece entre o sistema nervoso e o cardiorrespiratório. A análise mais aprofundada de um sistema complexo revela causas e consequências de seu funcionamento, e auxilia detectar problemas e solucioná-los. Motivada pela melhor compreensão desta relação vou aprofundar as análises dos sistemas para contribuir com as pesquisas desta área. A eficiência da regulação autonômica pode ser verificada por meio de testes de arritmia sinusal respiratória observada através dos sinais de eletrocardiograma ECG e a resposta do sistema nervoso pode ser percebida pelo eletroencefalograma EEG. Neste trabalho apresento algumas abordagens na análise de sistemas complexos como os biológicos. As contribuições mais relevantes da pesquisa são preparadas partindo do conhecimento dos sistemas biológico cardiorrespiratório e nervoso, e da relação direta entre eles. No trabalho houve a preocupação com a qualidade da instrumentação para coleta de sinais biológicos e do pré-processamento para análise. Esta etapa gerou a construção de um equipamento de eletrocardiograma. E então foram coletados sinais de ECG da equipe paralimpica de bocha, enquanto os atletas realizavam seus habituais exercícios respiratórios para melhorar a concentração e que alteram a frequências cardíacas. Os eletrocardiogramas foram analisados através das técnicas análises de quantificação de recorrência observando os detalhes das alterações durante os exercícios. Outra abordagem da pesquisa foram os modelos matemáticos do eletrocardiograma. Os modelos de ECG foram estudados e foi escolhido o oscilador de Kaplan, cujo modelo foi analisado através de diagramas de bifurcação e melhorado em seus resultados. Como os atletas alteram o padrão do coração e aumentam a concentram com os exercícios. O trabalho passou a etapa de análise do EEG. Foram realizadas diversas análises por técnicas lineares e não lineares, comparando os sinais entre o participante com olhos abertos e olhos fechados. Nesta parte foi gerada uma nova técnica de análise de recorrência no espectro de frequências. A técnica apresentou resultados relevantes para melhor caracterizar os sinais, poderá ser utilizada para caracterizar caso de depressão, e outras doenças que afetam o sistema nervoso central. Coletas de dados em conjunto de ECG e EEG realizando o exercício respiratório foram realizadas, os dados foram analisados por técnicas já consagradas e pela técnica de recorrência aqui criada, mostramos que existe uma relação entre os sinais do coração e do cérebro na execução dos exercícios respiratórios. Todas as etapas do trabalho geraram artigos que foram publicados, os primeiros em congressos e os últimos em revistas especializadas.Universidade Federal de UberlândiaBrasilPrograma de Pós-graduação em Engenharia ElétricaDestro Filho, João Batistahttp://lattes.cnpq.br/4173410222083256Tusset, Ângelo Marcelohttp://lattes.cnpq.br/1204232509410955Balthazar, José Manoelhttp://lattes.cnpq.br/9728054402919622Lopes, Luís Cláudio Oliveirahttp://lattes.cnpq.br/9971842873202479Finzi Neto, Roberto Mendeshttp://lattes.cnpq.br/3792275882221002Ladeira, Guênia Mara Vieira2020-12-18T12:35:45Z2020-12-18T12:35:45Z2020-12-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfLADEIRA, Guênia Mara Vieira. Análises da arritmia sinusal respiratória. 2020. 157 f. Tese (Doutorado em Engenharia Elétrica) - Universidade Federal de Uberlândia, Uberlândia, 2020. DOI http://doi.org/10.14393/ufu.te.2020.802https://repositorio.ufu.br/handle/123456789/30697http://doi.org/10.14393/ufu.te.2020.802porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFUinstname:Universidade Federal de Uberlândia (UFU)instacron:UFU2020-12-19T06:16:35Zoai:repositorio.ufu.br:123456789/30697Repositório InstitucionalONGhttp://repositorio.ufu.br/oai/requestdiinf@dirbi.ufu.bropendoar:2020-12-19T06:16:35Repositório Institucional da UFU - Universidade Federal de Uberlândia (UFU)false
dc.title.none.fl_str_mv Análises da arritmia sinusal respiratória
Analyses of respiratory sinus arrhythmia
title Análises da arritmia sinusal respiratória
spellingShingle Análises da arritmia sinusal respiratória
Ladeira, Guênia Mara Vieira
Análise de sistemas complexos
Análise de recorrência do espectro de frequência
Sinais elétricos do coração
Sinais elétricos do sistema nervoso central
Analysis of complex systems
Analysis of recurrence of the frequency spectrum
Electrical signals from the heart
Electrical signals from the heart
CNPQ::ENGENHARIAS::ENGENHARIA BIOMEDICA
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::MEDIDAS ELETRICAS, MAGNETICAS E ELETRONICAS INSTRUMENTACAO::INSTRUMENTACAO ELETRONICA
CNPQ::CIENCIAS EXATAS E DA TERRA::MATEMATICA::ANALISE
CNPQ::CIENCIAS EXATAS E DA TERRA::MATEMATICA::GEOMETRIA E TOPOLOGIA
Sistema nervoso
Homeostase
Respiração
Cardiotocografia
title_short Análises da arritmia sinusal respiratória
title_full Análises da arritmia sinusal respiratória
title_fullStr Análises da arritmia sinusal respiratória
title_full_unstemmed Análises da arritmia sinusal respiratória
title_sort Análises da arritmia sinusal respiratória
author Ladeira, Guênia Mara Vieira
author_facet Ladeira, Guênia Mara Vieira
author_role author
dc.contributor.none.fl_str_mv Destro Filho, João Batista
http://lattes.cnpq.br/4173410222083256
Tusset, Ângelo Marcelo
http://lattes.cnpq.br/1204232509410955
Balthazar, José Manoel
http://lattes.cnpq.br/9728054402919622
Lopes, Luís Cláudio Oliveira
http://lattes.cnpq.br/9971842873202479
Finzi Neto, Roberto Mendes
http://lattes.cnpq.br/3792275882221002
dc.contributor.author.fl_str_mv Ladeira, Guênia Mara Vieira
dc.subject.por.fl_str_mv Análise de sistemas complexos
Análise de recorrência do espectro de frequência
Sinais elétricos do coração
Sinais elétricos do sistema nervoso central
Analysis of complex systems
Analysis of recurrence of the frequency spectrum
Electrical signals from the heart
Electrical signals from the heart
CNPQ::ENGENHARIAS::ENGENHARIA BIOMEDICA
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::MEDIDAS ELETRICAS, MAGNETICAS E ELETRONICAS INSTRUMENTACAO::INSTRUMENTACAO ELETRONICA
CNPQ::CIENCIAS EXATAS E DA TERRA::MATEMATICA::ANALISE
CNPQ::CIENCIAS EXATAS E DA TERRA::MATEMATICA::GEOMETRIA E TOPOLOGIA
Sistema nervoso
Homeostase
Respiração
Cardiotocografia
topic Análise de sistemas complexos
Análise de recorrência do espectro de frequência
Sinais elétricos do coração
Sinais elétricos do sistema nervoso central
Analysis of complex systems
Analysis of recurrence of the frequency spectrum
Electrical signals from the heart
Electrical signals from the heart
CNPQ::ENGENHARIAS::ENGENHARIA BIOMEDICA
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::MEDIDAS ELETRICAS, MAGNETICAS E ELETRONICAS INSTRUMENTACAO::INSTRUMENTACAO ELETRONICA
CNPQ::CIENCIAS EXATAS E DA TERRA::MATEMATICA::ANALISE
CNPQ::CIENCIAS EXATAS E DA TERRA::MATEMATICA::GEOMETRIA E TOPOLOGIA
Sistema nervoso
Homeostase
Respiração
Cardiotocografia
description Heart rate variability is essential for maintaining the homeostatic balance of the body. It is controlled by the autonomic nervous system. Human biological systems have standard basic characteristics, but varieties of construction and functioning due to genetics, age, sex, and also disease impairment. In addition, they have a complex relationship between systems, such as the nervous system and the cardiorespiratory system. Further analysis of a complex system reveals causes and consequences of its functioning, and helps to detect problems and solve them. Motivated by a better understanding of this relationship I will deepen the analysis of the systems to contribute to the research in this area. The efficiency of the autonomic regulation can be verified by means of respiratory sinus arrhythmia tests observed through electrocardiogram signals ECG and the response of the nervous system can be perceived by electroencephalogram EEG. In this work I present some approaches in the analysis of complex systems such as biological ones. The most relevant contributions of the research are prepared from the knowledge of the cardiorespiratory and nervous biological systems, and the direct relationship between them. The work was concerned with the quality of the instrumentation for biological signal collection and pre-processing for analysis. This stage generated the construction of electrocardiogram equipment. Then, ECG signals were collected from the paralympic boccia team, while the athletes performed their usual breathing exercises to improve concentration and alter heart rates. The electrocardiograms were analysed through the techniques of quantification of recurrence observing the details of the alterations during the exercises. Another approach of the research was the mathematical models of the electrocardiogram. The ECG models were studied and the Kaplan oscillator was chosen, whose model was analysed through bifurcation diagrams and improved in its results. How the athletes change the pattern of the heart and increase the concentration with the exercises. The work passed the EEG analysis stage. Several analyses were performed by linear and non-linear techniques, comparing the signals between the participant with open eyes and closed eyes. A new recurrence analysis technique in the frequency spectrum was generated in this part. The technique presented relevant results to better characterize the signals, can be used to characterize case of depression, and other diseases affecting the central nervous system. Data collection in set of ECG and EEG performing the breathing exercise were performed, the data were analysed by already established techniques and by the recurrence technique created here, we showed that there is a relationship between the heart and brain signals in performing the breathing exercises. All the stages of the work have generated articles which have been published, the first in congresses and the last in specialized journals.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-18T12:35:45Z
2020-12-18T12:35:45Z
2020-12-09
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv LADEIRA, Guênia Mara Vieira. Análises da arritmia sinusal respiratória. 2020. 157 f. Tese (Doutorado em Engenharia Elétrica) - Universidade Federal de Uberlândia, Uberlândia, 2020. DOI http://doi.org/10.14393/ufu.te.2020.802
https://repositorio.ufu.br/handle/123456789/30697
http://doi.org/10.14393/ufu.te.2020.802
identifier_str_mv LADEIRA, Guênia Mara Vieira. Análises da arritmia sinusal respiratória. 2020. 157 f. Tese (Doutorado em Engenharia Elétrica) - Universidade Federal de Uberlândia, Uberlândia, 2020. DOI http://doi.org/10.14393/ufu.te.2020.802
url https://repositorio.ufu.br/handle/123456789/30697
http://doi.org/10.14393/ufu.te.2020.802
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Uberlândia
Brasil
Programa de Pós-graduação em Engenharia Elétrica
publisher.none.fl_str_mv Universidade Federal de Uberlândia
Brasil
Programa de Pós-graduação em Engenharia Elétrica
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFU
instname:Universidade Federal de Uberlândia (UFU)
instacron:UFU
instname_str Universidade Federal de Uberlândia (UFU)
instacron_str UFU
institution UFU
reponame_str Repositório Institucional da UFU
collection Repositório Institucional da UFU
repository.name.fl_str_mv Repositório Institucional da UFU - Universidade Federal de Uberlândia (UFU)
repository.mail.fl_str_mv diinf@dirbi.ufu.br
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