Evacuate the area - the last words you want to hear at an airport?

Mega stress at Check-in at Heathrow Terminal 3. Got to x-ray machines and my bags were stopped. First one staff member was called to the computer display and then within 10 mins 6 security staff were gathered around it. I was then ask for a list of all the items in the bag. Eventually it transpired it was a metal cup and contents that had been identified as a BOMB.

Cambridge - King's Parade

Many consider Cambridge as being a beautiful unspoilt small town with old buildings unsullied by the worst ravages of commercial excess. It is a view that I find myself expressing as I casually talk to people around the country. It is a viewpoint based upon what I see as I travel to and from work everyday not one from old photos or Disney-like recollections from visits long ago. Here is a photo that I took about two years ago of a portion of Downing Street just a few hundred metres from where I work. The view can hardly have changed in a hundred years. There are no satellite dishes, aerials, advertising posters or even graffiti - no plastic, no bollards, no sleeping policemen or helpful signs telling you something that you don't need to know. This is the view of Cambridge that is all too easy to lodge in one's consciousness - it is after all a view that is repeated in hundreds of locations around Cambridge. But, look more closely and there are signs of progress. There are lines on the road, there is tarmac and electric lights too and the stone work is mostly rather too clean. But, these are details that we filter out rather easily they are such an obvious part of normal life that they no longer warrant any attention.
There is something very privileged about cycling past King's College Chapel early on a Saturday morning when the students are still tucked-up in bed and tourists are breakfasting in their hotels. King's Parade is tidy, devoid of litter with green neat grass and clean stone buildings. From the vantage point of a twenty-first century cyclist, off to do a parkrun on a weekend, it looks splendid and well preserved - a town and University unchanged. A town very similar to that captured in this picture from June 1940 taken by my wife's uncle (Donald Smith) of his sister and mother walking down King's Parade. Of course war-time Britain was not entirely representative of the mid-twentieth century - there was much happening that made towns and villages look and feel much older and quieter than they had been only a few years before. In many old photos wartime austerity throws the scenery back decades or centuries to a simpler less clustered time.

On seeing the photo it stuck me that the scene must look almost unchanged today and I set out on a Friday afternoon to try and stand exactly where Don had and take a photo of the scene 70 years later. The 1940 photo was taken somewhere near midday as the shadows are pointing north and by the look of the length of the shadows, if the photo was taken in June, it must have been very early June. So, my photo late afternoon in October, 2012 was going to look slightly different. But, I didn't expect it to look quite so different.

 I have left the photo in colour and I have not cropped it to match the 1940 photo. It was taken from one of the entrances to the Cambridge Chop House looking towards Senate House. Looking at it, I think Don was a bit taller than I am or he was standing on something to get a better view of the buildings behind. The streets were no busier on the day I took my photo but the view is not as good. I need to retake the photo with the sun from behind as in Don's version. The tree is obviously much larger now and obscures the western frontage of Senate House and the street hoardings, advertising boards and outside tables clutter the view. The old lamposts in Don's photo hardly intruded on the scene, but the modern poles in my photo dominate. The car with its highly reflective paintwork demands attention - a very different effect from the matt sheen of the 1940s model reflecting off the elegant wheel arch. The hi-vis jacket of a workman presents an equal visual distraction as do the chrome reflections from the chairs. In Don's photo the reflection from the window  folds the image back on to its self framing the composition. In mine the reflections are hardly visible against the well illuminated interior. The change seems to be embodied by a rather gaudy 'look at me' mentality a presumption that more is better - more visibility and more shine. Perhaps this is the result of improved manufacturing and reduced costs making shine and attractiveness easier to obtain in individual items. Or, maybe it is the result of competition for visibility and custom such that mere functionality is no longer sufficient. Either way, from an aesthetic view it is hard to sustain the argument that individual advances in technology, communication, planning and commerce have been able to maintain let alone improve one of Cambridge's iconic views. But, maybe it doesn't really matter since these things only become apparent when faced with a direct comparison between old and new. To the hundreds of tourists who wander up and down King's Parade each day it is still a 'chocolate box' view.

The relationship between speed and heart rate on a run

Miles per gallon - or an equivalent?

We are all use to heart beats per minute, but it is not necessarily the best measure to use when looking at running data. In this post I will explain how speed and heart rate are related and why heart beats per km is a much better measure to use.

Bulk download of activityIds and GPX from Garmin Connect

[Updated 4pm 30/06/2012]
OK, problem solved. There was a flag that enables the untitled activities to be shown. I have added in a few more search terms including date, distance (with an accuracy) and location with accuracy. The locations are pulled from a long/lat table on a separate sheet. I have begun to populate it with the locations of the parkruns. The latest version 5 is available here.
I would also like to that David Jacobson for his help with getting this up and running. David has a blog here which lists some more sophisticated software for looking at Garmin datasets in other ways.

[Updated 1:23am 30/06/2012]
I can't correct the failure to display other people non-named activities - it is a problem with the whole Garmin Connect system....but, I have a better searching facility on this sheet. It now implements distance, location and date searches. I have entered a few parkrun locations to test it.

[Updated 12:41pm 28/06/2012]
My previous version ignored activities without a name. I hope I have corrected that problem....

The Garmin Connect website is useful, but often rather slow and limited in terms of data manipulation. To overcome some of these problems I have written a short Excel VBA script that pulls down all of the activity IDs and GPS files for any user (not just your own). The Excel file is here. Save the file somewhere sensible (don't open it from the link) and when you open it, enable macros. You need to enter your own Garmin Connect detail (username and password) and the user you want to download for. Then click the extract button.

The code is all visible, but not documented - anyone with a small amount of VBA experience should be able to tweak it for their own needs.

1. Athletic track test of barefoot versus Hyperspeed

Comparison of physiological effort of running barefoot compared to Asics Hyperspeed

Summary

We examined physiological effort, using heart beats per km as an index, for two subjects (aged 14 & 45) running shod (~200g per shoe) and barefoot around an outdoor synthetic athletics track at ~4:30 min per km. Both runners showed a progressive rise in physiological effort during the first four shod runs. On running barefoot (for the first time) both runners showed a progressive decline in physiological effort which ceased on returning to the shod condition. The changes in physiological effort were ~2% and consistent with previous efficiency gains associated with lighter running shoes. However, no significance testing was performed, and this is just a preliminary study so conclusions must be limited. Nevertheless, it seems very unlikely that running barefoot is less efficient than shod on a synthetic athletics track.

Introduction

The idea we set-out to test is whether running barefoot or in lightweight running shoes results in the lowest amount of physiological effort. Whilst there have been many studies of barefoot running, almost all have been done on treadmills. Treadmills tend to be rather elastic and do not necessarily replicate the surface encountered in outdoor running. There has been a study of barefoot running on an indoor track - however, we have attempted here to get a little bit closer to normal, 'real-world' running.
The test surface was an outdoor athletics track (Cambridge University Athletics Track) which has a typical synthetic surface. The surface was selected as both participants (my son and I) had not engaged in barefoot running (except a few years ago on a beach...) and therefore required a consistent, mildly abrasive surface free of stones and other hazards.
The test was conducted at constant (but not controlled) pace wearing Garmin 305 GPS/heart rate monitors with which we assessed physiological effort. It is relatively well known that heart rate rises and falls as 'physiological effort' changes during running. As you run faster heart rate rises due to the greater supply of blood required by your muscles - equally as you slow down heart rate falls as your muscles demand less blood. Thus, during a run heart rate is a good indicator of changes in physiological effort (work being done). Of course there are other reasons why heart rate may change - dehydration and thermoregulation are good examples - but, such challenges tend to occur gradually. Thus, heart rate during an exercise session - once in steady-state - is a good indicator of physiological effort. By doing repeat measurements of speed and heart rate we have calculated the number of heart beats per km associated with barefoot and shod running.

Methods

We arrived at the athletics track around 7pm on an overcast day. The track was empty and free from distractions. We selected lane 8 (~450m) for our test, staying as close as possibly to the inner side of the lane. We had two subjects (Max, aged 14 and I, aged 45) and decided on a two lap (~900m) measurement for each test with an additional 100m flying-start. We used an alternating protocol to avoid distracting each other and influencing pace. Max first ran two laps, then on his last 100 m I joined in and started my two laps. On my last 100m Max joined in an started his next two laps - and so on. Thus, we ensured a constant rest between laps with minimal distractions. We decided upon four sets of two laps each in our normal running shoes, followed by three sets of two laps each barefoot and then another three sets of two laps back in the running shoes again. This produced 10 sets of data. Max and I ran mainly by feel, selecting a pace that was comfortable and sustainable. We did not attempt to match each others pace (except for the 100m flying start), or changes of pace during the sets. Average heart rate and time were collected from the watches and heart beats per km were calculated.

Results

Table 1 shows the data from all ten sets. Max and I ran at very similar speeds, between 4:39 and 4:31 per km, with a progressive speed increase between sets. Max's heart rate was also, on average, 38 beats per minute higher than mine - unsurprising given our age and training differences. I recently ran a 3:07 marathon and Max does no consistent running except for the occasional parkrun (5K). 

Runner	Set	Test	Time	Pace	HR	beats per km
Max	1	Shod	04:11	04:39	155	720
Max	2	Shod	04:10	04:38	164	759
Max	3	Shod	04:04	04:32	167	756
Max	4	Shod	04:07	04:34	171	781
Max	5	Barefoot	04:06	04:33	171	778
Max	6	Barefoot	04:07	04:34	169	772
Max	7	Barefoot	04:06	04:34	168	766
Max	8	Shod	04:02	04:29	169	758
Max	9	Shod	04:02	04:29	169	758
Max	10	Shod	04:04	04:31	169	764
Christof	1	Shod	04:10	04:38	123	567
Christof	2	Shod	04:12	04:40	127	592
Christof	3	Shod	04:11	04:39	128	595
Christof	4	Shod	04:09	04:36	132	608
Christof	5	Barefoot	04:08	04:36	133	611
Christof	6	Barefoot	04:07	04:34	131	599
Christof	7	Barefoot	04:05	04:32	131	595
Christof	8	Shod	04:06	04:33	129	586
Christof	9	Shod	04:05	04:32	130	589
Christof	10	Shod	04:05	04:32	130	589

Table 1. Data from each subject for the ten tests (in sequence: 4 shod, 3 barefoot, 3 shod).

In Figure 1 I have plotted the pace for each lap, and the gradual increase in speed is obvious. It is interesting to note that both Max and I gradually increased the speed by a similar amount without discussion or prior agreement - although, my pacing was generally more consistent than Max's. The barefoot condition (open symbols) was not associated with any obvious change in pacing. 

Figure 1. Plot of pace for each test (open symbols show the barefoot tests). Note the arbitrary y-axis limits selected to allow the progressive increase in pace to be seen. 

In Figure 2 the relative heart rate (relative to the average across all ten tests for each subject) is shown plotted. Both Max and I had very similar relative heart rate changes with an initial rise in heart rate over the first four tests, followed by a plateau or slight decline in heart rate during the barefoot running which was maintained on returning back to running shoes. However, the pace fluctuations may confound a simple heart rate analysis.

Figure 2. Plot of heart rate (relative to the average for each subject over the 10 tests). Again, arbitrary y-axis ranges were chosen. Open symbols show the barefoot tests. 

 A simple way method of correcting for pace variations is to calculate heart beats per km. These data are shown in Table 1. Max had a mean value of 761 heart beats per km, whilst mine was 593 heart beats per km. To allow a better comparison of Max and my data I have plotted the heart beats per km relative to these averages (Figure 3). This form of normalization removes the offsets and allows changes in physiological effort to be compared between different people.

Figure 3. Relative heart beats per km plotted against test number. The relative heart beats per km was calculated as the heart beats per km divided by the subject's average heart beat per km over the ten tests. This form of correction allows relative changes in efficiency to be seen without the offset due to differences in heart rate between individuals.

Both Max and I showed a progressive rise in the number of heart beats per km for the initial 4 tests. This type of initial rise is always seen during a warm-up period. The following three runs barefoot (open symbols) was associated with a modest decline in heart beats per km which appeared to reverse on returning to the shod condition.

Discussion

The initial four runs produced a progressive rise in heart beats per km (physiological effort) typical of these types of test. Interestingly the first run barefoot produced similar values as the previous shod run, and the two subsequent barefoot runs produced lower physiological efforts. This, ~2% decline during the barefoot tests, is consistent with barefoot running being more efficient and is a similar degree of efficiency gain previously seen with a reduction in running shoe weight. On returning to the running shoes for the final three tests, the progressive decline in effort seen during barefoot running appeared to reverse (although only partially) producing a very modest increase. The similarity between Max and my traces is striking despite having done the runs separately and without a prior pacing plan. The changes in the data between the shod and barefoot conditions are not sufficiently striking to be confident that other time dependent phenomena (including the pace variations) are not confounding the results. The relatively low physiological effort on the last three shod runs was unexpected and may be due to the slight rise in pace. Tentatively, it would appear that barefoot running is associated with lower physiological effort (perhaps 2%) when compared to lightweight running shoes (400g per pair), but another test with better controls is required!

Shoe weight and running speed - the scientific literature

Shoe weight and running speed - the scientific literature

Whilst I have done a few tests of my own on the effect of different running shoes on physiological effort associated with running, I thought it might be interesting to draw together the literature on the subject.

There have been quite a few studies, but many of them are inaccessible to the general public because they were published in Scientific Journals that are not open access. Where possible I have tried to get hold of these articles and I have explained what the authors did and what they concluded. This is very much my opinion of the research - you may well have a different view point (please feel free to comment). For my starting point I used an article by Greg Crowther, published in Northwest Runner back in 2001.

The early years

The first relevant article I can find seems to be Hettinger & Muller (1953). They published an article on the effect of shoe weight on the energy consumption during walking and carrying (sorry for my poor translation). I have managed to access it, but it does stretch my German to its limit. They investigated a range of conditions (in 265 trials) from barefoot, plimsolls (UK terminology), half shoes, normal laced shoes, ski-shoes, riding boots, military boots and a variety of other test shoes. I only mention them since it is the most complete test list of shoes I have come across - very Germanic! Whilst there is much good data to consider - most of it is hard to connect with more modern studies. However, the conclusion that; when walking and carrying a weight of 30 kg, energy consumption increases more rapidly in shoes than barefoot seems interesting. The next relevant study was by Catlin & Dressendorfer (1979) where the authors, apparently, looked at the effect of shoe weight on the energy cost of running. Since I am unable to get hold of the article and PubMed does not have an abstract for it I am limited to recounting what Jones et al. (1986) state about it. The study looked at marathon runners, on a treadmill wearing lightweight racing flats (520g total weight). They recorded a 0.9% increase in energy cost for each 100g increase in shoe weight (per pair).

Myers & Steudel (1985) reported the results of four people running at a stately 10.3 km per hour (5:50 min per km) on a treadmill (paced using a metronome) with weights (3.6 kg in total in canvas belts filled with lead shot) attached to them in four locations - waist, upper thigh, upper shank and ankle. They made measurements of oxygen consumption at steady-state (after 8-15 mins of running). The authors also modelled the physical work required to accelerate the additional weights using a few simple equations. They found that 3.6 kg around the waist had the smallest effect causing a 3.7% increase in energy (oxygen) consumption. Moving the weights (split equally across the limbs) caused a greater increase in energy consumption with the size of the increase related to how close the weights were to the foot. Thus, the ankle weights produced a 24.3% increase in energy consumption compared to running without the added weights and 20.7% compared to running with the weights around the waist. Thus, they demonstrated that weight around the feet has a much bigger effect (on the flat and on a treadmill) than weight on the waist. Interestingly they state the kinetic energy changes of the legs account for about a third of the energy used when running. They also noted that this kinetic energy component increases with the square of the running speed whilst the mechanical energy in moving the trunk rises linearly resulting in high energy costs for limb movements at higher speeds.

In the same year (Martin, 1985) the results of weight loading (thighs or feet) of 15 men running at 12 km per hour (5 min per km) was published. I only have access to the abstract, so I can make little comment other than to report what was summarized within it. The increase in oxygen consumption was 7.2% per kg of load (on the foot) which, when extrapolated to 3.6 kg, produces a value of ~26% and is in agreement with Myers & Steudel (1985). They also go on to state that the energy increase can be attributed to the additional weight rather than a change in gait.
Jones et al. (1986) looked at the energy cost of women walking and running in athletics shoes (514g) and leather military boots (1,370g)! They report an 8.3% increase in energy cost associated with the weight increase of 857g giving rise to the memorable number of 1.0% increase in energy cost per 100g increase in footwear weight.

Miller & Stamford (1987) went a little bit further, investigating men and women, ankle and arm weights during both walking and running! Again the experiments were on a treadmill but, at a range of speeds. The maximum running speed was halfway between Martin (1985) and Myers & Steudel (1985) at 7 mph (11.2 km per hour). The bottom line is that men and women had the same energy consumption and it rose by 8% per kg on the ankle (i.e. similar to Martin's study). Weights on the hand produced a greater increase (13%) in oxygen consumption - but, subjects ran with a 90 degree bend in the elbow with arms swinging with each step. Interestingly they also report that the increase in oxygen consumption rose linearly with weight added to the ankle all the way up to 4.5 kg.

Barefoot - the ultimate weight reduction

Warburton  (2001) published a brief review of barefoot running. In it he states that Laboratory studies show a 4% reduction in energy cost when running barefoot. But he also states; "Competitive running performance should therefore improve by a similar amount, but there has been no published research comparing the effect of barefoot and shod running on simulated or real competitive running performance." This short coming may have been solved by Buchholz (2007). He wrote a Masters Thesis on performance differences between bare foot and shod running, however, an electronic copy is not available. Divert et al. (2008) attempted to compare barefoot with shod running in order to test whether shoe weight or a change in foot strike was responsible for the differences in oxygen consumption reported. They used 12 subjects running at 13 km per hour on a treadmill with a range of shoe and additional weights. They found that additional mass increased oxygen consumption and that efficiency was reduced when wearing shoes.  They hypothesized that the damping effect of shoes reduced the storage of elastic energy lowering the efficiency of running in shoes.

Hanson et al. (2011) compared the cost of running barefoot and shod both on the treadmill and overground using both men and women at 70% of VO₂max (10.7 km per hour). They found that shoes increased oxygen consumption and heart rate on both the treadmill and overground. Interestingly, the effects were more pronounced overground where using shoes increased oxygen consumption by 5.7% compared to on a treadmill where shoes increased oxygen consumption by 2%. An electronic copy is available at the time of writing, and care needs to be taken with reading it. Fig. 1, for instance, appears to show no significant oxygen uptake differences between the groups - which is compatible with their data since the SEM will be dominated by the variation between subjects rather than the different test conditions. It is hard to see why this figure is included and the statistically significant data (i.e. mean relative change in oxygen uptake for each condition) is not plotted - hey ho! But, there are studies which report the opposite. Jack Daniels, who worked for Nike in the early 1980s, states that as shoe weight is reduced there is a point at which further weight reductions began to increase the cost of running. This may well be the same observation reported by Franz et al. (2012). Again this is a treadmill comparison of barefoot versus shod. However, in this case running (12 km per hour) in shoes produced a lower oxygen uptake and the authors concluded that running barefoot offers no metabolic advantage over lightweight cushioned shoes. The paper got a lot of publicity across the web, but without being able to see it I cannot comment further.

Is strike type important?

To finish off I want to just bring a recent article to your attention, whilst it is not directly related to shoe weight it does impact on shoe type. Perl et al. (2012) looked at running economy in minimal shoes versus standard running shoes using a range of foot strike patterns. Again I am hampered by not being able to access the paper, but here is the gist of what they report in the abstract. First, they controlled for shoe mass (I don't know how) and they found that regardless of whether you forefoot or rearfoot strike minimal shoes require less energy (2.4% less for forefoot, 3.3% less for rearfoot). That is an effect of the shoe type not weight. Again, like Divert et al. (2008) they suggest that shoe cushioning may get in the way of the more efficient elastic recoil in your musculature.

Conclusion

It is clear that adding weight to your feet will cause a rise in oxygen consumption. Treadmill data suggests about 1% for each 100g of total shoe weight. There is only one study of oxygen consumption that used a hard surface (an indoor track) and that was by Hanson et al (2011). However, they only tested one shoe type against barefoot running, and the shoe weight does not seem to be given. Others (e.g.  Buchholz, 2007) must have run tests on the effect of shoe weight overground, however, they are hard to get hold of - perhaps because they are done as student projects and without laboratory control are considered unsuitable for publication in the scientific literature.

It is also clear that the physics dictates that increasing the mass at the end of a lever system must result in an increased energy input. The counter argument is that some of the weight, in a shoe, improves efficiency by altering the gait or foot-strike or improves race performance by allowing the runner to get to the finish line without injury. Minimal running shoes may also present a benefit beyond weight reduction in allowing the musculature to return more elastic energy. However, barefoot running tests have produced mixed results. There are suggestions that this may depend upon gait or foot-strike, experience, adaptations etc. However, I think it is probably fair to say that there is not yet enough evidence to be at all sure.

Finally, there is the BIG question as to whether a reduction in energy consumption leads to better race performance. Certainly extrapolating from mathematical models like Rapoport's (which is a good read) then one would conclude that it can. But, races are about more than simple energetics......

References

Buchholz MP Performance differences between the conditions of running with the foot bare and running with the foot shod (2007) Thesis (MS) Springfield College Listing

Catlin MJ, Dressendorfer RH (1979) Effect of shoe weight on the energy-cost of running Medicine and Science in Sports and Exercise 11, 80.

Divert C, Mornieux G, Freychat P, Baly L, Mayer F, Belli A (2008) Barefoot-shod running differences:shoe or mass effect? Int J Sports Med, 29, 512-518. PubMed

Franz JR, Wierzbinski CM, Kram R (2012) Metabolic cost of running barefoot versus shod: is lighter better? Med Sci Sports Exerc Mar 2 [Epub ahead of print] PubMed

Hanson NJ, Berg K, Deka P, Meendering JR, Ryan C (2011) Oxygen cost of running barefoot vs. running shod. Int J Sports Med PubMed Full Text

Hettinger T, Muller EA (1953) Der Einfluss der Schuhgewichtes auf den Energieumsatz beim Gehen und Lastentragen. Arbeitsphysiologie 15, 33-40. Full Text
Jones BH, Knapik JJ, Daniels WL, Toner MM (1986) The energy cost of women walking and running in shoes and boots. Ergonomics 29, 439-443. Full Text
Martin PE (1985) Mechanical and physiological responses to lower extremity loading during running. Med Sci Sports Exerc 17, 427-433. PubMed 

Miller JF, Stamford BA (1987) Intensity and energy cost of weighted walking vs. running for men and women. J Appl Physiol 62, 1497-1501. PubMed Full Text

Myers MJ, Steudel K (1985) Effect of limb mass and its distribution on the energetic cost of running. J Exp Biol. 116, 363-373. PubMed Full Text

Perl DP, Daoud AI, Lieberman DE (2012) Effects of footware and strike type on running economy. Med Sci Sports Exerc [Epub ahead of print] PubMed
Warburton M (2001) Barefoot running. Sportscience 5. sportsci.org/jour/0103/mw.htm

A quantification of the reduction in effort when running in lighter shoes - another test

Difference in running speed, at equal physiological effort, in lighter and heavier shoes

In a previous blog I reported a comparison of 'physiological effort' of running at the same speed in two different running shoes. I compared the ProGrid Ride (740g total weight for the pair) with the Hyperspeed (425g total weight for the pair) both UK size 9. I conducted the test on a flat tarmac track (2km at 4:50 mins per km) alternating between shoes. The result was that when using the Hyperspeeds I had roughly 1.8% fewer heart beats per km than when using the ProGrid Rides. I then went on to suggest that this might extrapolate to a 1.8% faster speed for the same heart rate.

I posted a link to the results on RunningAHEAD and JRMichler suggested a better test. He said; " The next logical experiment would be to run 1.8% faster with the lighter shoes and compare average heart rates. "

It is indeed a good idea. The last test was fixed speed, on this one I set out to run at a speed that I predicted would produce equal heart rates with both shoes. I started with the ProGrids and ran a warm-up 2km along the route (here is the run). I then set-off at 4:30 min per km pace for the first test run which I abandoned just over halfway when I turned at the wrong pole......I walked back.

The next two runs in the ProGrids were done (1 & 2) in 9:03min and 9:02min for the 2km - roughly 2s slower than I had planned. I then attempted to run ~2% faster in the Hyperspeeds. The first run was in 08:51min and the second in 08:49min (2.14% faster than in the ProGrids).

In Figure 1 I have plotted the speed (in km per hour) and the heart rates for each run.

Figure 1. Speed and heart rate data for six runs (in sequence) on a 2km flat tarmac path in two different running shoes. The first run was done at an average of 137 beats per minute (as reported by Garmin Training Center) whilst the next four runs were all done at 138 beats per minute. On the final run my heart rate was 1 beat per minute higher. I have set the y-axis ranges to allow the difference in heights of the individual bars to be judged. I am not attempting to imply either a large or a small effect - it is ~2%.

I shall restrict my analysis to the middle four runs for a couple of reasons. First, the middle Hyperspeed runs are bracketed ProGrid runs making for a symmetrical arrangement. Second, all of those runs resulted in the same heart rate (138 beats per min). The average speed for the middle two ProGrids was 13.30 km per hour and for the Hyperspeeds it was 13.58 km per hour. Thus, I ran in the Hyperspeeds 2.14% faster than in the ProGrids but (to integer accuracy) the heart rate was identical. Thus, it would appear the lower heart beats per km using the Hyperspeeds in my previous test does translate to a faster speed (~2%) at the same heart rate.

For interest I have included in Figure 2 an analysis of heart beats per km for the same data set.

Figure 2. Heart beats per km for the same runs as shown in Figure 1. This form of analysis normalizes for speed and heart rate producing a value of heart beats per km that is fairly insensitive (although not completely) to speed. It shows that the Hyperspeeds require fewer heart beats to be taken per km run. The y-axis minimum is the value that I predict I would need to run a world record marathon.

This is consistent with the idea that losing 150g from each foot results in either a lower physiological effort for the same speed, or higher speeds for the same heart rate (the choice is yours!).