Comparação de diferentes métodos para determinar o limiar de anaerobiose de idosos saudáveis

Detalhes bibliográficos
Autor(a) principal: Pozzi, Luis Gustavo
Data de Publicação: 2006
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional da UFSCAR
Texto Completo: https://repositorio.ufscar.br/handle/ufscar/5195
Resumo: Some studies have been conducted with the objective of applying mathematical models to the data of HR, CO2 and RMS of myoelectric signal to determine a shift point on their behaviors during exercise and characterize metabolic changes which occur at the anaerobic threshold level (AT), saving time and optimizing the conventional analysis process which, by financial reasons, has become restricted to few research centers. The objective of the present study was to determine the anaerobic threshold applying two mathematical models, Heteroscedastic and Hinkley, to a set of HR, RMS and CO2 data. Methods: 9 active elderly subjects were studied (61,4 ±1,8years) during continuous physical ramp load test on cycle ergometer, with power ranging from 10 to 15 Watts/min. FC data was collected beat to beat and ventilatory variables breath to breath. After the application of mathematical models to these variables and the identification of the behavior shift points, the power levels, HR and O2 were registered, compared and co-related to those obtained by the graphic visual model. Statistic methodology: The Friedman test was used to make multiple comparisons and the Spearman co-relation test (5%) to verify the adjustment of the models to the variables. Results: no significant differences were found (p>0,05) in relation to the gold standard, between the power levels, O2 and HR during the LA shift identified by the different models. Significant correlated data were found between the HR values identified by the mathematical models applied to the HR and O2 data, between the values of O2 when identified by the HR, and between power rates only when identified by the Hinkley model applied to data of RMS of the myoeletric signal. Conclusion: in the sample study, the mathematical models appeared adequate in determining noninvasive AT. Both models adjusted better to the HR data, followed by CO2 and RMS.
id SCAR_55fd8a9b708729ffa4ade1e0876c07f4
oai_identifier_str oai:repositorio.ufscar.br:ufscar/5195
network_acronym_str SCAR
network_name_str Repositório Institucional da UFSCAR
repository_id_str 4322
spelling Pozzi, Luis GustavoCatai, Aparecida Mariahttp://genos.cnpq.br:12010/dwlattes/owa/prc_imp_cv_int?f_cod=K4793978Y6http://plsql1.cnpq.br/sigef_imp/PRC_HIST_PROC?F_COD_RH=K4700755A5d1ff9be5-8c88-4504-a087-25ab93639c242016-06-02T20:19:03Z2007-08-162016-06-02T20:19:03Z2006-02-21POZZI, Luis Gustavo. Comparison of different methods to determine the anaerobic threshold of healthy older men.. 2006. 110 f. Dissertação (Mestrado em Ciências Biológicas) - Universidade Federal de São Carlos, São Carlos, 2006.https://repositorio.ufscar.br/handle/ufscar/5195Some studies have been conducted with the objective of applying mathematical models to the data of HR, CO2 and RMS of myoelectric signal to determine a shift point on their behaviors during exercise and characterize metabolic changes which occur at the anaerobic threshold level (AT), saving time and optimizing the conventional analysis process which, by financial reasons, has become restricted to few research centers. The objective of the present study was to determine the anaerobic threshold applying two mathematical models, Heteroscedastic and Hinkley, to a set of HR, RMS and CO2 data. Methods: 9 active elderly subjects were studied (61,4 ±1,8years) during continuous physical ramp load test on cycle ergometer, with power ranging from 10 to 15 Watts/min. FC data was collected beat to beat and ventilatory variables breath to breath. After the application of mathematical models to these variables and the identification of the behavior shift points, the power levels, HR and O2 were registered, compared and co-related to those obtained by the graphic visual model. Statistic methodology: The Friedman test was used to make multiple comparisons and the Spearman co-relation test (5%) to verify the adjustment of the models to the variables. Results: no significant differences were found (p>0,05) in relation to the gold standard, between the power levels, O2 and HR during the LA shift identified by the different models. Significant correlated data were found between the HR values identified by the mathematical models applied to the HR and O2 data, between the values of O2 when identified by the HR, and between power rates only when identified by the Hinkley model applied to data of RMS of the myoeletric signal. Conclusion: in the sample study, the mathematical models appeared adequate in determining noninvasive AT. Both models adjusted better to the HR data, followed by CO2 and RMS.Alguns estudos têm sido conduzidos com o objetivo de aplicar modelos matemáticos aos dados de FC, CO2 e RMS do sinal mioelétrico para determinar um ponto de mudança nos seus comportamentos frente ao exercício e caracterizar alterações metabólicas que ocorrem no nível do limiar de anaerobiose (LA), poupando tempo e otimizando todo o processo de análise convencional, que por motivos financeiros, torna-se restrita a poucos centros de pesquisa. O objetivo do presente estudo foi determinar o limiar de anaerobiose aplicando dois modelos matemáticos, Heteroscedático e Hinkley, ao conjunto de dados de FC, RMS e CO2. Metodologia: foram estudados 9 idosos ativos (61,4±1,8 anos) durante teste de exercício físico dinâmico contínuo do tipo rampa, em cicloergômetro, com incrementos de potência variando de 10 a 15 Watts/min. Foram coletados os dados de FC batimento a batimento, eletromiografia de superfície do músculo vasto lateral e variáveis ventilatórias respiração a respiração. Após a aplicação dos modelos matemáticos e identificados os pontos de quebra de comportamento, foram registrados neste momento os valores de potência, O2 e FC, comparados e correlacionados aos obtidos pelo modelo visual gráfico. Metodologia estatística: foi utilizado o teste de Friedman para comparações múltiplas e o teste de correlação de Spearman (nível de significância de 5%). Resultados: não foram encontradas diferenças significantes, em relação ao padrão ouro, entre os valores de potência, O2 e FC no momento do LA identificado pelos diferentes modelos. Foram encontradas correlações significantes entre os valores de FC identificados pelos modelos matemáticos aplicados aos dados de FC e CO2, entre os valores de O2 quando identificados pela freqüência cardíaca e de potência somente quando identificada pelo modelo de Hinkley aplicado aos dados de RMS do sinal mioelétrico. Conclusões: no grupo estudado, os modelos matemáticos mostraramse eficientes na determinação não-invasiva do LA. Ambos os modelos ajustaramse melhor aos dados de FC, seguido pela CO2 e RMS.application/pdfporUniversidade Federal de São CarlosPrograma de Pós-Graduação em Fisioterapia - PPGFtUFSCarBRFisioterapiaLimiar de anaerobioseModelos matemáticosIdososCIENCIAS DA SAUDE::FISIOTERAPIA E TERAPIA OCUPACIONALComparação de diferentes métodos para determinar o limiar de anaerobiose de idosos saudáveisComparison of different methods to determine the anaerobic threshold of healthy older meninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis-1-14ed7731f-b898-4c69-9259-e19629ba1f59info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARORIGINALDissLGP.pdfapplication/pdf1609330https://repositorio.ufscar.br/bitstream/ufscar/5195/1/DissLGP.pdf88bd59a45015d98192652d3d68f74fe3MD51THUMBNAILDissLGP.pdf.jpgDissLGP.pdf.jpgIM Thumbnailimage/jpeg8039https://repositorio.ufscar.br/bitstream/ufscar/5195/2/DissLGP.pdf.jpg79b60fa9d18057602640aa8527e5515fMD52ufscar/51952023-09-18 18:31:06.005oai:repositorio.ufscar.br:ufscar/5195Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-09-18T18:31:06Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false
dc.title.por.fl_str_mv Comparação de diferentes métodos para determinar o limiar de anaerobiose de idosos saudáveis
dc.title.alternative.eng.fl_str_mv Comparison of different methods to determine the anaerobic threshold of healthy older men
title Comparação de diferentes métodos para determinar o limiar de anaerobiose de idosos saudáveis
spellingShingle Comparação de diferentes métodos para determinar o limiar de anaerobiose de idosos saudáveis
Pozzi, Luis Gustavo
Fisioterapia
Limiar de anaerobiose
Modelos matemáticos
Idosos
CIENCIAS DA SAUDE::FISIOTERAPIA E TERAPIA OCUPACIONAL
title_short Comparação de diferentes métodos para determinar o limiar de anaerobiose de idosos saudáveis
title_full Comparação de diferentes métodos para determinar o limiar de anaerobiose de idosos saudáveis
title_fullStr Comparação de diferentes métodos para determinar o limiar de anaerobiose de idosos saudáveis
title_full_unstemmed Comparação de diferentes métodos para determinar o limiar de anaerobiose de idosos saudáveis
title_sort Comparação de diferentes métodos para determinar o limiar de anaerobiose de idosos saudáveis
author Pozzi, Luis Gustavo
author_facet Pozzi, Luis Gustavo
author_role author
dc.contributor.authorlattes.por.fl_str_mv http://plsql1.cnpq.br/sigef_imp/PRC_HIST_PROC?F_COD_RH=K4700755A5
dc.contributor.author.fl_str_mv Pozzi, Luis Gustavo
dc.contributor.advisor1.fl_str_mv Catai, Aparecida Maria
dc.contributor.advisor1Lattes.fl_str_mv http://genos.cnpq.br:12010/dwlattes/owa/prc_imp_cv_int?f_cod=K4793978Y6
dc.contributor.authorID.fl_str_mv d1ff9be5-8c88-4504-a087-25ab93639c24
contributor_str_mv Catai, Aparecida Maria
dc.subject.por.fl_str_mv Fisioterapia
Limiar de anaerobiose
Modelos matemáticos
Idosos
topic Fisioterapia
Limiar de anaerobiose
Modelos matemáticos
Idosos
CIENCIAS DA SAUDE::FISIOTERAPIA E TERAPIA OCUPACIONAL
dc.subject.cnpq.fl_str_mv CIENCIAS DA SAUDE::FISIOTERAPIA E TERAPIA OCUPACIONAL
description Some studies have been conducted with the objective of applying mathematical models to the data of HR, CO2 and RMS of myoelectric signal to determine a shift point on their behaviors during exercise and characterize metabolic changes which occur at the anaerobic threshold level (AT), saving time and optimizing the conventional analysis process which, by financial reasons, has become restricted to few research centers. The objective of the present study was to determine the anaerobic threshold applying two mathematical models, Heteroscedastic and Hinkley, to a set of HR, RMS and CO2 data. Methods: 9 active elderly subjects were studied (61,4 ±1,8years) during continuous physical ramp load test on cycle ergometer, with power ranging from 10 to 15 Watts/min. FC data was collected beat to beat and ventilatory variables breath to breath. After the application of mathematical models to these variables and the identification of the behavior shift points, the power levels, HR and O2 were registered, compared and co-related to those obtained by the graphic visual model. Statistic methodology: The Friedman test was used to make multiple comparisons and the Spearman co-relation test (5%) to verify the adjustment of the models to the variables. Results: no significant differences were found (p>0,05) in relation to the gold standard, between the power levels, O2 and HR during the LA shift identified by the different models. Significant correlated data were found between the HR values identified by the mathematical models applied to the HR and O2 data, between the values of O2 when identified by the HR, and between power rates only when identified by the Hinkley model applied to data of RMS of the myoeletric signal. Conclusion: in the sample study, the mathematical models appeared adequate in determining noninvasive AT. Both models adjusted better to the HR data, followed by CO2 and RMS.
publishDate 2006
dc.date.issued.fl_str_mv 2006-02-21
dc.date.available.fl_str_mv 2007-08-16
2016-06-02T20:19:03Z
dc.date.accessioned.fl_str_mv 2016-06-02T20:19:03Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv POZZI, Luis Gustavo. Comparison of different methods to determine the anaerobic threshold of healthy older men.. 2006. 110 f. Dissertação (Mestrado em Ciências Biológicas) - Universidade Federal de São Carlos, São Carlos, 2006.
dc.identifier.uri.fl_str_mv https://repositorio.ufscar.br/handle/ufscar/5195
identifier_str_mv POZZI, Luis Gustavo. Comparison of different methods to determine the anaerobic threshold of healthy older men.. 2006. 110 f. Dissertação (Mestrado em Ciências Biológicas) - Universidade Federal de São Carlos, São Carlos, 2006.
url https://repositorio.ufscar.br/handle/ufscar/5195
dc.language.iso.fl_str_mv por
language por
dc.relation.confidence.fl_str_mv -1
-1
dc.relation.authority.fl_str_mv 4ed7731f-b898-4c69-9259-e19629ba1f59
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 São Carlos
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Fisioterapia - PPGFt
dc.publisher.initials.fl_str_mv UFSCar
dc.publisher.country.fl_str_mv BR
publisher.none.fl_str_mv Universidade Federal de São Carlos
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFSCAR
instname:Universidade Federal de São Carlos (UFSCAR)
instacron:UFSCAR
instname_str Universidade Federal de São Carlos (UFSCAR)
instacron_str UFSCAR
institution UFSCAR
reponame_str Repositório Institucional da UFSCAR
collection Repositório Institucional da UFSCAR
bitstream.url.fl_str_mv https://repositorio.ufscar.br/bitstream/ufscar/5195/1/DissLGP.pdf
https://repositorio.ufscar.br/bitstream/ufscar/5195/2/DissLGP.pdf.jpg
bitstream.checksum.fl_str_mv 88bd59a45015d98192652d3d68f74fe3
79b60fa9d18057602640aa8527e5515f
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)
repository.mail.fl_str_mv
_version_ 1802136282635173888