Oxygen Uptake Estimation In Humans During Exercise Using A Hammerstein Model

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dc.contributor.author Wang Lu en_US
dc.contributor.author Celler Branko en_US
dc.contributor.author Su Steven en_US
dc.contributor.author Savkin Andrey en_US
dc.date.accessioned 2009-12-21T03:52:54Z
dc.date.available 2009-12-21T03:52:54Z
dc.date.issued 2007 en_US
dc.identifier 2006014367 en_US
dc.identifier.citation Su Steven et al. 2007, 'Oxygen Uptake Estimation In Humans During Exercise Using A Hammerstein Model', Springer, vol. 35, no. 11, pp. 1898-1906. en_US
dc.identifier.issn 0090-6964 en_US
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/5803
dc.description.abstract This paper aims to establish a block-structured model to predict oxygen uptake in humans during moderate treadmill exercises. To model the steady state relationship between oxygen uptake (oxygen consumption) and walking speed, six healthy male subjects walked on a motor driven treadmill with constant speed from 2 to 7 kilometer/hour. The averaged oxygen uptake at steady state (V O2) was measured by a mixing chamber based gas analysis and ventilation measurement system (AEI Moxus Metabolic Cart). Based on these reliable date, a nonlinear steady state relationship was successfully established using Support Vector Regression methods. In order to capture the dynamics of oxygen uptake, the treadmill velocity was modulated using a Pseudo Random Binary Signal (PRBS) input. Breath by breath analysis of all subjects was performed. An ARX model was developed to accurately reproduce the measured oxygen uptake dynamics within the aerobic range. Finally, a Hammerstein model was developed, which may be useful for implementing a control system for the regulation of oxygen uptake during treadmill exercises. en_US
dc.publisher Springer en_US
dc.relation.isbasedon http://dx.doi.org/10.1007/s10439-007-9362-2 en_US
dc.title Oxygen Uptake Estimation In Humans During Exercise Using A Hammerstein Model en_US
dc.parent Annals Of Biomedical Engineering en_US
dc.journal.volume 35 en_US
dc.journal.number 11 en_US
dc.publocation New York, NY, USA en_US
dc.identifier.startpage 1898 en_US
dc.identifier.endpage 1906 en_US
dc.cauo.name Engineering en_US


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