Correlação entre nível de atividade física por acelerometria e custo energético da caminhada de indivíduos pós-acidente vascular cerebral crônico

• Ano de defesa: 2018
• Autor(a) principal: Ribeiro, Jean Alex Matos
• Orientador(a): Russo, Thiago Luiz de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Fisioterapia - PPGFt
• Palavras-chave em Português: Metabolismo energético; Consumo de oxigênio; Caminhada; Sensores inerciais; Acelerômetro; Monitor de atividade; Tecnologia vestível; Exercício; Reabilitação; Acidente vascular cerebral
• Palavras-chave em Inglês: Energy metabolism; Oxygen consumption; Walking; Inercial sensors; Accelerometer; Activity monitor; Wearable technology; Exercise; Rehabilitation; Stroke
• Área do conhecimento CNPq: CIENCIAS DA SAUDE::FISIOTERAPIA E TERAPIA OCUPACIONAL
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/10435

Introduction: Individuals after stroke expend more energy during walking and this contributes to an increasingly inactive lifestyle, increasing the risk of developing a new cerebrovascular and/or cardiac events. The Compendium of Physical Activities may overestimate or underestimate energy expenditure in people following stroke. Thus, more accessible methods to estimate energy costs in this population are important to prescribe physical activity and exercise. Objective: To evaluate whether there is a correlation between StepWatch™ Activity Monitor (SAM) and the energy cost of walking in participants after chronic stroke. Methods: This study is a correlational, cross-sectional pilot study. Twenty participants following stroke were analyzed. All procedures were carried out in two days. On the first day, the performance on the six-minute walk test (6MWT) was measured, and then the SAM was placed on the participant’s non-paretic ankle. Metabolic variables were collected using a portable metabolic system (Oxycon Mobile®) during walking in the 6MWT. Nine days later, the participants returned and the SAM was removed. The energy cost of walking was calculated by dividing peak oxygen consumption by the distance in meters achieved in the 6MWT. Spearman’s rank correlation coefficient was used to evaluate whether there is a correlation among variables of interest and the magnitude of the correlation was based on Munro’s classification. All analyses were carried out with the SPSS 20.0 software with a significance level of 5%. Results: The energy cost of walking correlated with the number of steps (r¬s = - 0.666, p = 0.001), percentages of time in inactivity (r¬s = 0.503, p = 0.024), low cadence (r¬s = 0.782, p < 0.001), medium cadence (r¬s = - 0.632, p = 0.003) and high cadence (r¬s = - 0.673, p = 0.001) and the percentages of steps taken at low cadence (r¬s = 0.707, p < 0.001) and high cadence (r¬s = - 0.620, p = 0.004). Conclusion: SAM seems to be a good activity monitor to infer the energy cost of walking in people following chronic stroke, and should be considered to help clinicians to prescribe exercise for the prevention and treatment of cardiovascular diseases after stroke.