Development of a protocol for determining and classifying of the physical workload in forestry activities

• Autor(a) principal: Stanley Schettino
• Data de Publicação: 2019
• Outros Autores: Luciano José Minette, Carolina Freitas Schettino, José Dionisio de Paula Junior
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UFMG
• Texto Completo: http://hdl.handle.net/1843/47461
• topic: Ergonomics; Forestry; Heart rate; Worker's health; Ergonomia; Serviços de saúde ocupacional; Variabilidade do batimento cardíaco; Índice de massa corporal

In field conditions, forest work can be extremelyheavy under the view point of physical effort. In order to classify the physical workload, the aerobic capacity, expressed in maximumoxygen consumption (VO2max), when associated with other factorssuch as age, gender and body mass of workers during the performance of their activities, can provide accurate answers aboutthe physical workload of these workers. Thus, this study aimed at thedevelopment of equations for VO2max determination from maximumheart rates of work, body mass and gender of the workers, besides the proposition of a protocol to classify the physical workload fordifferent forestry activities from VO2max. Based on the nomogram proposed by Per-Olof Astrand, taking as a basis the body mass andheart rate variables, all the combinatory possibilities for thedetermination of VO2max were explored, generating 319 and 383combinations for the female and male genders, respectively. Nonlinear regression models were adjusted by adopting the valuesfound for VO2max as dependent variable and body mass and heart rateas independent variables. The model chosen for VO2 max estimationwas adjusted to the data with great precision, considering the resultsof the regression statistical analysis, demonstrating that the adjustedequations present a high predictive power to estimate the VO2max inforest workers, being applicable for the physical workloaddetermination. Moreover, the protocol proposed for classification of physical workload has practicality and efficiency, and its use is viablein field conditions, showing consistent results, which improvesworking conditions in situations where workers are confronted withrealities that disrupt and surpass their capacities.