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

• Ano de defesa: 2006
• Autor(a) principal: Pozzi, Luis Gustavo
• Orientador(a): Catai, Aparecida Maria
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Fisioterapia - PPGFt
• País: BR
• Palavras-chave em Português: Fisioterapia; Limiar de anaerobiose; Modelos matemáticos; Idosos
• Área do conhecimento CNPq: CIENCIAS DA SAUDE::FISIOTERAPIA E TERAPIA OCUPACIONAL
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/5195

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.