Breathing plays a key role in human health, especially in terms of fatigue and energy. Oxygen maximum consumption is important for lung. Lung functional performance is characterized by: its ventilator capacity, to bring air (thus O2) into alveoli, and its capacity to transfer O2 and CO2 into and from the pulmonary capillary bed. Hence, the O 2 and CO2 diffusion coefficients as well as the O 2 consumption rate and the CO2 production rate represent the lung performance indices. Both gases have a relevant importance in human body energy expenditure; one of the best instrumentation used for this purpose is ergospirometer. It allows to know the oxygen maximum consumption or the aerobic maximum power VO2, that is the maximum amount of energy (moles of ATP) produced by different substances (carbohydrates, lipids and proteins) per unit of time. This research proposes a signal processing approach for improving the quality of data recovered from the ergospirometric sessions. The ergospirometric is used to evaluate the efficiency of walking for two main reasons: rehabilitation and cough impact on a patient before a surgery. Cough can be an index of muscular and lung problems on human body. Before a surgery, it could be necessary to discriminate some pathologies in presence of cough. The results offered by the research are characterized by a good accuracy and they help clinicians in knowing précised values of oxygen maximum consumption, hence, human body expenditure. A Cosmed K4b2, as ergospirometer, is used in this research.
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