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* The Garmin [[Connect IQ]] platform should allow for alternative models of power, given pace input from an accurate Footpod and the barometer of the watch.
=How Do They Work?=
So far, only RunScribe has been transparent about the model they use for running power, which is available as an online calculator at [https://runscribe.com/power/RunScribe.com]. Your power output is going to be closely related to your [[Running Economy]], and there's quite a bit known about [[The Science of Running Economy]]. The three most important inputs to the model are:
* '''Weight.''' A key input to any estimate of running power is your body weight, and generally running effort varies linearly with your weight. This is pretty easy to estimate, or running power systems ask you to enter your weight. I typically enter my approximate body weight and then don't modify it, but you could weigh yourself before each run in your running gear to compensate for additional closing and the like. Of course, it's hard to adjust for hydration changes; in other summer my body weight can vary by 5Lb/2.5Kg over the course of a long run. None of the running power systems evaluate the weight on your feet, which we know can dramatically influence [[Running Economy]].
* '''Pace'''. For running, effort varies linearly with your pace across a broad range. Accurately measuring your pace is one of the critical problems in estimating power. Some systems will rely on GPS, but [[GPS Accuracy]] is so poor that the systems tend to be deeply flawed. A better approach is a Footpod, and systems like [[Stryd]] don't need calibration to produce high accuracy.
One of the primary benefits of training is likely to be improving running economy, so that you can run faster for the same oxygen consumption. Running economy varies significantly between different runners, which means that running power output would vary for a given oxygen consumption between runners. If a running power meter was actually measuring oxygen consumption, then this would be a way of measuring running economy, but that's an equally flawed idea.
==Comparisons Between Running Power and V̇O2max==
Below is a graph from the book "The Secret Of Running", which compares power output and V̇O<sub>2.</sub> It's claiming that this shows "the stride data I just as good as the V̇O<sub>2</sub>." However, this only shows that the [[Stryd]] estimate of power varies linearly with pace, which given pace is a primary input to power estimate should come as no surprise. It also shows that oxygen consumption is also linear with pace, something that is well known. However, the power estimate for a given oxygen consumption varies dramatically. You can see for 40 ml/Kg/min, the estimate varies from 2.5 w/Kg to 4.0 w/Kg, a nearly 40% variation. See [https://hetgeheimvanhardlopen.nl/wp-content/uploads/2016/11/3-The-running-economy-of-14-test-runners.pdfhetgeheimvanhardlopen.nl] for more details.
[[File:StrydVo2.png|center|thumb|300px|Data from "The Secret Of Running" book.]]
Stryd have released their own evaluation at [https://storage.googleapis.com/stryd_static_assets/stryd-metric-validation.pdfStryd Metric Validation]. Their data shows "Stryd power is 96% correlated with metabolic energy expenditure", but the study was on 13 runners and the correlation is only a subset of 9 of them.
[[File:StrydVO2-2.jpg|center|thumb|300px|Data from an evaluation performed by [[Stryd]].]]
=Differences Between Running and Cycling Power Meters=
* It's quite easy to measure cycling power by measuring the force applied (torque) and the rotation it's applied through. This makes cycling power meters reasonably accurate and not outrageously expensive (compared with say, a metabolic cart that a lab would use to measure oxygen consumption). By comparison, running power is impractical to directly measure and requires a mathematical model with various assumptions that use indirect inputs. This makes running power meters an estimate of power output rather than a true meter. If cycling power meters worked like this, they'd be a wind speed meter that would guess how that influence power output.
* Because running is vastly less efficient than cycling, knowing power output is less important. If a cyclist knows their power output, they have a very good estimate of their exercise intensity. This is because most of a cyclist's effort is delivered as usable power. Even if it were practical to measure running power, it would be of relatively less value due to the influence of [[Running Economy]]. This means that a runner is far more interested in their energy expenditure than of their power output.
=Running and Cycling Watts=
Garmin claim that for a given oxygen consumption, the Watts of running output should be higher than watts of cycling<ref name="urlGarmin FAQ"/>. Thankfully, Garmin list the scientific research they use to support their claim, allowing for their conclusions to be verified.
* Claim: ''Metabolic efficiency of positive work for running at 2.75 m/s is 39%, and at 3.25 m/s is 41%''<ref name="FarrisSawicki2011"/>.
** This study uses optical measurement of joint dynamics along with ground reaction forces to calculate the total mechanical power, and compared this with the oxygen consumed. The focus of this study is to estimate how much power is being generated at each joint, rather than overall efficiency. This study ignores any elastic properties of a runner, and assumes that none of the landing forces are used to subsequently generate positive forces. It's debatable whether this is a reasonable assumption given the limited focus of this study, there is plenty of evidence to the contrary<ref name="FukunagaKubo2001"/><ref name="IshikawaPakaslahti2007"/>, with one study claiming "''In walking or running the negative work performed in the eccentric phase was completely stored as elastic energy''"<ref name="HofVan Zandwijk2002"/>.
* Claim: ''In running, efficiency increases steadily with speed from ~45% at 2.77 m/s to ~60% at 5.55 m/s''<ref name="CavagnaLegramandi2008"/>.
** I'm not sure how Garmin came to this conclusion given this research study, but I may have missed something. I could find no mention of measuring oxygen consumption or metabolic work. The published paper does have graphs on page 416 that show the total mechanical work, along with the internal work (used to move your limbs forward into position) and the external work (used to propel the body forward.) It looks to me like Garmin may have used the ratio between the external mechanical work and the total mechanical work to define "efficiency." This is a totally different to the previous study which is looking at the ratio of total energy to mechanical energy, whereas this study is looking at a subdivision of the mechanical energy.
** This study does raise the interesting question of what should be counted as "running power." Should the power going into your arm swing be considered part of running power or just wasted energy? Likewise, the power used to move your leg forward in the swing phase could be considered wasted energy or running power.
* Claim: "''A review paper on cycling efficiencies indicates efficiency for cycling is between 20 to 25% for power between 200-300 W''"<ref name="JoynerCoyle2008"/>.
** The paper says 18.5 to 23.5% at 300W, but this paper actually references another study<ref name="CoyleSidossis1992"/> that shows cycling gross efficiency of between 18.3 and 22.6%. So the numbers are little different, but close enough.
* Claim: "''Some researchers study delta efficiency, or apparent efficiency, which is the ratio of an increment in external mechanical power output to the increase in metabolic power required to produce it''."
** Sub-claim "delta efficiency for running is 45.5%, cycling is 25.7%"<ref name="BijkerDe Groot2001"/>.
*** This study actually only considers the mechanical cost of moving uphill, using a simple calculation of mass, gravity, velocity, and the angle of incline. So this isn't the delta efficiency of running, so much as the efficiency of moving the body upwards along an incline.
** Sub-claim "delta efficiency for running is 45.5%, cycling is 25.7%"<ref name="K.Groot2002"/>.
*** This is a similar study by the same researchers, using the same simplistic measure of efficiency.
** Sub-claim "delta efficiency for running is 53.8%, cycling is 25.1%"<ref name="AsmussenBonde-Petersen1974"/>.
*** This study is comparing the changes in efficiency between running and cycling when there is a force pulling the subject backwards. For runners and they used a rope going over a pulley and attached to a weight. From what I can tell, the delta efficiency only looks at the work performed from the distance covered and the force of the weight.
* Claim: "''The table below shows external power experienced at the road and does not include internal power required for repositioning the limbs''"<ref name="CavagnaKaneko1977"/><ref name="WilliamsCavanagh1983"/><ref name="CavagnaMantovani1997"/>
** Garmin is correct in saying these studies only look at the external power, not the internal power, but more importantly they ignore the elastic properties of the human body.
None of this research appears to be relevant to real-world running, or helpful in calculating appropriate running power.
=References=
<references>
<ref name="CavagnaMantovani1997">G. A. Cavagna, M. Mantovani, P. A. Willems, G. Musch, The resonant step frequency in human running, Pflgers Archiv European Journal of Physiology, volume 434, issue 6, 1997, pages 678–684, ISSN [http://www.worldcat.org/issn/0031-6768 0031-6768], doi [http://dx.doi.org/10.1007/s004240050451 10.1007/s004240050451]</ref>
<ref name="WilliamsCavanagh1983">Keith R. Williams, Peter R. Cavanagh, A model for the calculation of mechanical power during distance running, Journal of Biomechanics, volume 16, issue 2, 1983, pages 115–128, ISSN [http://www.worldcat.org/issn/00219290 00219290], doi [http://dx.doi.org/10.1016/0021-9290(83)90035-0 10.1016/0021-9290(83)90035-0]</ref>
<ref name="CavagnaKaneko1977">G. A. Cavagna, M. Kaneko, Mechanical work and efficiency in level walking and running, The Journal of Physiology, volume 268, issue 2, 1977, pages 467–481, ISSN [http://www.worldcat.org/issn/00223751 00223751], doi [http://dx.doi.org/10.1113/jphysiol.1977.sp011866 10.1113/jphysiol.1977.sp011866]</ref>
<ref name="AsmussenBonde-Petersen1974">Erling Asmussen, Flemming Bonde-Petersen, Apparent Efficiency and Storage of Elastic Energy in Human Muscles during Exercise, Acta Physiologica Scandinavica, volume 92, issue 4, 1974, pages 537–545, ISSN [http://www.worldcat.org/issn/00016772 00016772], doi [http://dx.doi.org/10.1111/j.1748-1716.1974.tb05776.x 10.1111/j.1748-1716.1974.tb05776.x]</ref>
<ref name="K.Groot2002">Bijker K., G. de Groot, Hollander A., Differences in leg muscle activity during running and cycling in humans, European Journal of Applied Physiology, volume 87, issue 6, 2002, pages 556–561, ISSN [http://www.worldcat.org/issn/1439-6319 1439-6319], doi [http://dx.doi.org/10.1007/s00421-002-0663-8 10.1007/s00421-002-0663-8]</ref>
<ref name="BijkerDe Groot2001">Kirsten E. Bijker, Gert De Groot, A. Peter Hollander, Delta efficiencies of running and cycling, Medicine & Science in Sports & Exercise, volume 33, issue 9, 2001, pages 1546–1551, ISSN [http://www.worldcat.org/issn/0195-9131 0195-9131], doi [http://dx.doi.org/10.1097/00005768-200109000-00019 10.1097/00005768-200109000-00019]</ref>
<ref name="CoyleSidossis1992">Edward F. Coyle, Labros S. Sidossis, Jeffrey F. Horowitz, John D. Beltz, Cycling efficiency is related to the percentage of Type I muscle fibers, Medicine & Science in Sports & Exercise, volume 24, issue 7, 1992, pages 782???788, ISSN [http://www.worldcat.org/issn/0195-9131 0195-9131], doi [http://dx.doi.org/10.1249/00005768-199207000-00008 10.1249/00005768-199207000-00008]</ref>
<ref name="JoynerCoyle2008">Michael J. Joyner, Edward F. Coyle, Endurance exercise performance: the physiology of champions, The Journal of Physiology, volume 586, issue 1, 2008, pages 35–44, ISSN [http://www.worldcat.org/issn/00223751 00223751], doi [http://dx.doi.org/10.1113/jphysiol.2007.143834 10.1113/jphysiol.2007.143834]</ref>
<ref name="CavagnaLegramandi2008">G.A Cavagna, M.A Legramandi, L.A Peyre-Tartaruga, Old men running: mechanical work and elastic bounce, Proceedings of the Royal Society B: Biological Sciences, volume 275, issue 1633, 2008, pages 411–418, ISSN [http://www.worldcat.org/issn/0962-8452 0962-8452], doi [http://dx.doi.org/10.1098/rspb.2007.1288 10.1098/rspb.2007.1288]</ref>
<ref name="HofVan Zandwijk2002">A. L. Hof, J. P. Van Zandwijk, M. F. Bobbert, Mechanics of human triceps surae muscle in walking, running and jumping, Acta Physiologica Scandinavica, volume 174, issue 1, 2002, pages 17–30, ISSN [http://www.worldcat.org/issn/0001-6772 0001-6772], doi [http://dx.doi.org/10.1046/j.1365-201x.2002.00917.x 10.1046/j.1365-201x.2002.00917.x]</ref>
<ref name="IshikawaPakaslahti2007">M. Ishikawa, J. Pakaslahti, P.V. Komi, Medial gastrocnemius muscle behavior during human running and walking, Gait & Posture, volume 25, issue 3, 2007, pages 380–384, ISSN [http://www.worldcat.org/issn/09666362 09666362], doi [http://dx.doi.org/10.1016/j.gaitpost.2006.05.002 10.1016/j.gaitpost.2006.05.002]</ref>
<ref name="FukunagaKubo2001">T. Fukunaga, K. Kubo, Y. Kawakami, S. Fukashiro, H. Kanehisa, C. N. Maganaris, In vivo behaviour of human muscle tendon during walking, Proceedings of the Royal Society B: Biological Sciences, volume 268, issue 1464, 2001, pages 229–233, ISSN [http://www.worldcat.org/issn/0962-8452 0962-8452], doi [http://dx.doi.org/10.1098/rspb.2000.1361 10.1098/rspb.2000.1361]</ref>
<ref name="urlGarmin FAQ">https://support.garmin.com/faqSearch/en-US/faq/content/vAzl2ne5dV6diuc2XbYZA6, Garmin Running Power Higher Compared to Cycling Power, Accessed on 2017-12-30</ref>
<ref name="FarrisSawicki2011">D. J. Farris, G. S. Sawicki, The mechanics and energetics of human walking and running: a joint level perspective, Journal of The Royal Society Interface, volume 9, issue 66, 2011, pages 110–118, ISSN [http://www.worldcat.org/issn/1742-5689 1742-5689], doi [http://dx.doi.org/10.1098/rsif.2011.0182 10.1098/rsif.2011.0182]</ref>
</references>
