Supersapiens – Glucose monitoring for sportspeople
More: Supersapiens Detailed Review
A thought for you: As endurance sportspeople, we need sources of energy and oxygen to burn it. Surely we should look more at Muscle Oxygen and Blood Glucose? Yet we spend all our analytical time looking at power data, velocity and heart rate data.
NB Technically it’s NOT blood glucose
I’m performing some sports & lifestyle tests with SuperSapiens over the next few weeks. During the first week, I’m trying to get a handle on what’s happening to my body and how glucose responds to food, exercise and life in general. Next week I’ll do some more involved sports tests; I have some in mind but please feel free to mention any you might consider interesting in the comments section.
More Info: supersapiens.com
What Is The Scope of Supersapiens?
The sensor is AirTag-sized with a filament sticking out of it that painlessly and continuously is in your skin. It’s held in place by a simple adhesive and cover. My sensor lasts two weeks then, AFAIK, you throw it away and buy another.
The sensor only talks to the Supersapiens smartphone app by Bluetooth and can cache its data for 8 hours until you next open the app.
The Supersapiens app looks good and has live data, charts and all sorts of goodness that, no doubt, I will delve into over the next few weeks. You can tag the continuous chart of glucose with events like EATING or RUNNING and it is possible to automatically import workouts from Apple Health but NOT from other sports data platforms like Strava, Garmin Connect or Wahoo Fitness.
There seem to be limitations to outgoing data connectivity too. Meaning the bottom line for live data is that you must carry your phone with you in order for a newish Garmin Watch (not Edge) to get the data via your iPhone. I can’t see any other way to get data out other than to record it as a developer field via the CIQ app and I’ve not even tested that yet. Just to confirm that there are no permissions to export from Supersapiens to Apple Health, so you can’t get data out that way either.
That said Wahoo is one of many investors in Supersapiens and the company has received significant funding. You can be absolutely certain that Supersapiens is going to evolve significantly in its openness in the coming months.
My Tests So Far
I tried a Gel Test and a Running On Empty Test
Running-On-Empty Test
Last night I had yoghurt/fruit (carbs) and not much else for an evening meal. This morning I had 4 slices of brown toast (carbs) and a less-than-liberal splattering of jam (carbs) at 08:30. Coffee too…obviously.
Four and a half hours later, I went for a two-and-a-half-hour ride to the Surrey Hills starting at 1 PM. I just took water as it’s hot. Plus I had an emergency gel in case I bonked. I’m going to have carbs in my liver, my muscles, and maybe something still being digested in my gut from the morning and the previous day.
The plan was to exhaust my carbs and simulate phenomena of blurred vision and disorientation that I sometimes get. I have previously thought that was due to running out of carbs but there could be a dehydration effect too. Anyway, this test should shed some light on the cause.
During the workout, I was continuously under/over LT1 (aerobic threshold) for most of the time and in my comfort zone. As I was a bit bored, I threw in two very hard efforts (Z4/Z5) each under 7 minutes and they were both close to PBs on the Strava segments in question. Looking at the 3rd image, above, this shows my W’ (red line) and how the ride ate into my anaerobic reserves so actually maybe the ride was harder than I thought although I think my FTP is set a bit too low which makes the W’ drop bigger than it probably was.
I did NOT replicate the dizziness feeling. However, I perhaps felt the onset of it as I arrived home. I’m not sure.
The first Supersapiens chart, above, was interesting. You can see my levels fell below a predetermined minimum just over halfway through the ride and that was soon after the second hard hill effort. And the 67% GPZ reflects the amount of time spent below the line ie when I was in a non-optimally fuelled zone.
In the following post-workout chart, you can see there are some very strange things happening, this is the effect of me returning to a normal equilibrium and the minimal refuelling effect of coffee and cake at the Flying Cloud Cafe (any cyclist returning to London from Surrey should avoid Kingston Bridge and stop there #beautiful location)
The Gel Test
I thought this was interesting.
3 hours prior to the ‘Gel Test’, a coffee +cake marked the end of a 2+ hour workout. So I assume my blood sugar levels are ‘normal’ at the start of the test.
I decided to take a sports gel and see what happened. I was interested to see how long it took to get into my bloodstream. Take a look.
The chart is hard to annotate so I created some events on it to highlight points on the curve at certain times of the day.
- I took the gel at exactly 7PM, the start of the first vertical blue line. And then not much happens for a short while.
- The second blue vertical bar starts at 7:30 pm. So you can very clearly see that the gel is already working its magic and the mini-peak is about 20 minutes after taking the gel
- The true peak effect is at about 7:50 ie nearly an hour after ingestion
- The effect seems to end at 8:15pm.
Obviously, if I was doing anything other than sitting down or had a full stomach, the energy-usage impact on the glucose curve would be very different.
But the point is that “Gels start to work on me after 20 minutes”
There you go. I’ve learnt something already, I previously assumed it was 30 minutes.
dfa 1 derived endurance run
A dfa 1 analysis of my HRV determines my LT1 to be MUCH lower than would be predicted based on zones derived from threshold tests at LT2. I am not alone in this and I know several people who find the same.
Running at a dfa 1 derived LT1 should obviously be fat burning. As the following chart shows, that may well be the case. Next to try the same test at my z2/z3 boundary as determined by upper threshold tests and see what happens…
Take Out
This is very interesting stuff and definitely gives personal insights we never had before. Previously we just had to trust the advice we were given…now we can test for ourselves.
I already ‘get’ the basics of glucose but I’m not sure how much I need to improve my understanding to see if I am the sort of person that will benefit from a deeper understanding. I suspect there will be a steep learning curve.
Indeed I’m not sure if the benefits of Supersapiens usage will be realised whilst exercising or if, as I suspect, the benefits will arise from better management of your lifestyle outside of exercise.
I’m also going to have to dig around to see how best to integrate the data with the other sports data I have.
More Info: supersapiens.com
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My wife has diabetes Type I and has used the Libre sensor for 3 years. It was a life changer as not much need of poking her fingers with needles 5-7 times per day …… I was discussing about your article with her as we have “learned” thru experience a lot about the sensor and how it works …. Two observations that might be useful for your tests:
1. We have noticed that a new sensor provides a stable reading only after the first 12-24 hrs (we know this because we compare it with a blood sample) and the disclaimer on the sensor mentions that this “could” happen. So when you use a new sensor, you might find some erratic behavior at the beginning (i.e. weird readings which in her case are “low” sugar readings compared with blood sample). Same happens the las 12-24 hrs before the sensor dies (14th day )…. Her doctor can check her readings online and normally he disregards the first and last day.
2. Sensor tends to “lag” 12-18 minutes in regards to blood readings. Blood is an “instant” reading of your sugar in it. The sensor uses a different reading (some subcutaneous liquid) which tend to have that lag. I guess this is also mentioned in the literature coming with the sensor and we know it is for sure, at least in her case, because from time to time takes blood samples to compare….
So you might want to consider those tips in your analysis …..
Above comments come from the “diabetic” world. Supersapiens has a different approach. It uses the same Abbot sensor but the software is geared to sport performance (proper nutrition plan for optimal performance). Nonetheless is the same sensor, hence should experience same “issues”. The good news for the diabetic world is that is a great push to bring this technology to a wider market, This should help in improving technology and cost. We spend around USD 2,500 per year only in sensors … Expensive but worth it . A life changer . In our country, health insurance pays for traditional “blood strips” but the cost now is some similar, that there are strong discussions to include Abbot to be covered by insurance.
If the sensor lags 12-18′ regarding blood readings, won’t this make it not viable for real time race nutrition? So one needs to figure everything out in training, checking different intensities, gels reaction times, etc, and only then be able to apply it in a race scenario?
I was hoping this could signal me *during* a marathon/ultra when to go for an extra gel or something “TAKE IT NOW you are going to need in 20m!”. 😛
interstitial fluid in the MUSCLE is perhaps what is being used to fuel your work.
So it could be argued that Supersapiens *IS* measuring the correct thing. ie the lag to your muscle and the lag to supersapiens is similar.
#itscomplicated by other factors too.
the lag from ingestion to a reading showing in supersapiens is obviously the athlete’s problem (swilling glucose in your mouth might speed up absorption)
#itscomplicated
I would follow the same logic. First, the guys behind Supersapiens know for sure about the “lag” between blood and interstitial fluid. Second, as you mentioned, that said fluid is at the muscle, where it matters for this purpose and third, the app must have some sort of algorithm
that takes this into consideration ….
From what I’ve read in the Supersapiens site, they claim “real time glucose visibility “, si that either means is because it reads from the glucose present in your interstitial fluid in your muscles (and that would matters more for sports rather than in your bloodstream) and/or the app has an algorithm that “corrects” that. Again, my comments come knowing in how the Libre Sensor works for diabetes monitoring purposing , where you use an ad-hoc reader or app and comparing in it with blood sample you have that difference. For diabetes blood matters … for sports, maybe is this interstitial fluid in muscles …..
Anyway I think this can be a great tool specially if you are an endurance athlete. Many lear by “feel” in how to fuel properly. This can be a tool that add data and numbers to that “feel” ….