An equation for prediction of energy expenditure of walking and running.

Walt, W. H. Van Der; Wyndham, C. H.

doi:10.1152/jappl.1973.34.5.559

Cited by 127 publications

(43 citation statements)

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“…RMR was determined by a weighted average of the organ basal metabolic rates (22) as well as the energy costs for gluconeogenesis, lipogenesis, and turnover of protein, triacylglycerol, and glycogen (9,20). TEF was determined by macronutrient composition, and content of the diet (29), and PAE depended on the amount of daily physical activity and was proportional to the body weight (61).…”

Section: Methodsmentioning

confidence: 99%

Computational model of in vivo human energy metabolism during semistarvation and refeeding

Hall

2006

American Journal of Physiology-Endocrinology and Metabolism

115

148

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Changes in body weight and composition are the result of complex interactions among metabolic fluxes contributing to macronutrient balances. To better understand these interactions, a mathematical model was constructed that used the measured dietary macronutrient intake during semistarvation and refeeding as model inputs and computed whole body energy expenditure, de novo lipogenesis, and gluconeogenesis as well as turnover and oxidation of carbohydrate, fat, and protein. Published in vivo human data provided the basis for the model components that were integrated by fitting a few unknown parameters to the classic Minnesota human starvation experiment. The model simulated the measured body weight and fat mass changes during semistarvation and refeeding and predicted the unmeasured metabolic fluxes underlying the body composition changes. The resting metabolic rate matched the experimental measurements and required a model of adaptive thermogenesis. Refeeding caused an elevation of de novo lipogenesis that, along with increased fat intake, resulted in a rapid repletion and overshoot of body fat. By continuing the computer simulation with the prestarvation diet and physical activity, the original body weight and composition were eventually restored, but body fat mass was predicted to take more than one additional year to return to within 5% of its original value. The model was validated by simulating a recently published short-term caloric restriction experiment without changing the model parameters. The predicted changes in body weight, fat mass, resting metabolic rate, and nitrogen balance matched the experimental measurements, thereby providing support for the validity of the model.

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Section: Methodsmentioning

confidence: 99%

Computational model of in vivo human energy metabolism during semistarvation and refeeding

Hall

2006

American Journal of Physiology-Endocrinology and Metabolism

115

148

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“…1992), although sorne authors have suggested that this relationship might be quadratic (Daniels. et al, 1977;Fellingham et al, 1978;Van der Walt & Wyndham, 1973). Nevill et al.…”

Section: Running Velocity and Vozmentioning

confidence: 99%

Effect of intense interval workouts on running economy using three recovery durations

Zavorsky

Montgomery

Pearsall

1998

European Journal of Applied Physiology

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This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, sorne thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer.The quality of tbis reproduction is dependent upon tbe quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction.In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will he noted. Also, if unauthorized copyright material had ta he' removed, a note will indieate the deletion.Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand corner and continuing from left ta right in equai sections with smaII overlaps. Each original is aIso photographed in one exposure and is included in reduced form at the back of the book.Photographs included in the original manuscript have been reprodueed xerographically in tlûs eopy. Higher quality 6" x 9" black and white photographie prints are available for any photographs or illustrations appearing in this copy for an additional charge. Contact lTh1I directly to order. The author bas granted a nonexclusive licence allowing the National Library of Canada to reproduce, loan, distribute or sell copies of this thesis in microform, paper or electronic formats. DMIThe author retains ownership of the copyright in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author' s penmSSlon.L'auteur a accordé une licence non exclusive permettant à la Bibliothèque nationale du Canada de reproduire, prêter, distribuer ou vendre des copies de cette thèse sous la forme de microfiche/film, de reproduction sur papier ou sur format électronique.L'auteur conserve la propriété du droit d'auteur qui protège cette thèse.Ni la thèse ni des extraits substantiels de celle-ci ne doivent être imprimés ou autrement reproduits sans son autorisation. 0-612-29521-4Canad~ ABSTRACTThe purposes of this study were to determine if (1) RE is adversely affected by intense interval bouts of 10 x 400-m, and (2) if there is an interaction effect between RE and recovery duration during the workouts. Twelve highly trained male runners (VO:!max = 72.5 ± 4.3 ml-kg-'min-' ) performed 3 interval workouts of 10 x 400-m with a minimum of 4 days between runs. Recovery between repetitions was randomly assigned at 60, 120or 180 s. The velocity for each 4oo-m run was determined from a treadmill V0 2max test.The average running velocity was 357.9 ± 9.0 mmin-I .

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“…For the prediction of steady state oxygen uptake, Franklin 18 proposed a linear static model to approximately estimate oxygen consumption in a given range of walking speed. Papers 12,44,47 provided simple static nonlinear (polynomial) models.…”

Section: Introductionmentioning

confidence: 99%

Oxygen Uptake Estimation in Humans During Exercise Using a Hammerstein Model

Wang

Celler

et al. 2007

Ann Biomed Eng

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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 km/h. The averaged oxygen uptake at steady state (VO 2 ) 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.

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An equation for prediction of energy expenditure of walking and running.

Cited by 127 publications

References 0 publications

Computational model of in vivo human energy metabolism during semistarvation and refeeding

Computational model of in vivo human energy metabolism during semistarvation and refeeding

Effect of intense interval workouts on running economy using three recovery durations

Oxygen Uptake Estimation in Humans During Exercise Using a Hammerstein Model

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