| Title |
A simulation of cross-country skiing on varying terrain by using a mathematical power balance model
|
|---|---|
| Published in |
Open Access Journal of Sports Medicine, May 2013
|
| DOI | 10.2147/oajsm.s39843 |
| Pubmed ID | |
| Authors |
John F Moxnes, Øyvind Sandbakk, Kjell Hausken |
| Abstract |
The current study simulated cross-country skiing on varying terrain by using a power balance model. By applying the hypothetical inductive deductive method, we compared the simulated position along the track with actual skiing on snow, and calculated the theoretical effect of friction and air drag on skiing performance. As input values in the model, air drag and friction were estimated from the literature, whereas the model included relationships between heart rate, metabolic rate, and work rate based on the treadmill roller-ski testing of an elite cross-country skier. We verified this procedure by testing four models of metabolic rate against experimental data on the treadmill. The experimental data corresponded well with the simulations, with the best fit when work rate was increased on uphill and decreased on downhill terrain. The simulations predicted that skiing time increases by 3%-4% when either friction or air drag increases by 10%. In conclusion, the power balance model was found to be a useful tool for predicting how various factors influence racing performance in cross-country skiing. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Lecturer > Senior Lecturer | 1 | 10% |
| Student > Doctoral Student | 1 | 10% |
| Student > Master | 1 | 10% |
| Researcher | 1 | 10% |
| Professor > Associate Professor | 1 | 10% |
| Other | 0 | 0% |
| Unknown | 5 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Sports and Recreations | 3 | 30% |
| Biochemistry, Genetics and Molecular Biology | 1 | 10% |
| Social Sciences | 1 | 10% |
| Unknown | 5 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 February 2014.
All research outputs
#20,656,820
of 25,374,647 outputs
Outputs from Open Access Journal of Sports Medicine
#225
of 260 outputs
Outputs of similar age
#155,402
of 204,330 outputs
Outputs of similar age from Open Access Journal of Sports Medicine
#7
of 9 outputs
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