Can We Go Overboard with Metrics?

Interesting piece in “the i”, UK online tabloid, today and as it mentions Quantified Self in the text thought other like to read it.

What say you?

1 Like

I could pinpoint the day in my menstrual cycle when woe betide any fool get in my way.

That’s fun lol

Overall, I think this is nonsense. Anyone with a habit of hyper fixation will fixate, whether it be on data or something else. She even admits to it further down the article by mentioning her unhealthy fixation on her sleep data.

Today, it’s commonplace to track daily habits such as blood sugars, sleep, steps and stress levels.

This line irritates me. Tracking blood sugar is necessary for those with diabetes; it’s not some frivolous habit.

The part that resonates is what I am taking as the underlying question: What does a normal person do with all this data?

Individuals with this data can begin to understand their personal baselines. Then, they can understand how other variables influence them and use that data as they see fit.

On the accuracy of devices, nothing is perfect. I’ve received inaccurate readings from trained physicians in healthcare settings. We all have. Did we notice? No, because we didn’t have the data in a consumable format. Now we do. And so now it’s labeled inaccurate?

Call me suspicious, but this reads like an article meant to sow doubt in self-quantification and reduce attention on your health data, which never sits well with me.

Thank you for sharing this! What did you think about the article?


Hi, Hi. I’ve not been here for well over a year because I wasn’t sure how to quantify what interests me. I don’t know where the article is but it sounds like someone is sincerely fixed on fixating with no desire to sow distrust. I won’t insert here my own project but I will see if I can learn why you’re here. You take good good care.

That is the fundamental question for QS of course. Collecting data for the sake of collecting data is pointless.

Indeed. I have recently had false readings from my Apple Watch for its “Stand Hours” metric. Seems that raising one’s arm is enough for it to interpret the movement as a “stand”. Also had the opposite happen of standing up and moving within an hour does not get recorded. To be honest this is not a metric that I measure but it is useful for keeping me to the good health and safety practice of not sitting down for too long during the day.

You may be right but it comes across as an obessive compulsion habit that she wants now to kick.

THought provoking. Especially that point of collecting data for the sake of collecting data. My data export from Apple Health is now close to 200Mb of XML. Finding the appropriate way of displaying and analysing it is takin time. Currently looking at R and the tidyverse for that.

Similar situation for me. What in that mess of pottage known as health data is useful for day-to-day analysis and what might be useful in the future.

Simply follow the link in my original post.

If you know how to convert it to Python, Jupyter can be a helpful tool for data visualization and analysis.

There are several different pathways to analysing such data be that python with Jupyter notebooks, R with R Studio and tidyverse, ggplot2 plus other libraries. Also a bunch of Perl libraries too. Very much a case of whatever takes your fancy. For me, right now, R with R Studio is my choice as I learn to become au fait with R for some more public work; playing with my own data is a good exercise for that.

1 Like

There are several different pathways to analysing such data be that python with Jupyter notebooks, R with R Studio and tidyverse, ggplot2 plus other libraries. Also a bunch of Perl libraries too. Very much a case of whatever takes your fancy. For me, right now, R with R Studio is my choice as I learn to become au fait with R for some more public work; playing with my own data is a good exercise for that.

It seems that i’ve gone through that path and finally i came to mostly using python :slight_smile:
R / Python / Jupiter all just tools with almost everything you need to do a good analysis.

But knowing how to use tools is a 10% of skills you need to do an analysis if you have data collected. The main thing is to choose most suitable method to answer your question, know it limitations and make sure you can verify that it worked as it should. This requires fundamental knowledge in probability theory and statistical inference and from my experience “analysis” coming from QS geeks usually done without understanding what they are doing just because they dont have time to learn how to do it right. These days you can correlate something within your data in just 1 minute - the fastest way to get a false conclusions :slight_smile:

Anyway there are some progress in QS field we get more wearables, they becoming more accurate, we get easier access to our data (a lot of web apis and raw data export), it is more easier to preprocess it (with packages like neurokit or mne) and we have a lot of analytical easily accessible and open-source tools (R / Py). But despite this progress the lack of knowledge on how to analyse data in correct way still persists and i dont see progress here.

I’ve spent ~2-3 years learning data science (statistical and bayesian inference) as my hobby (few hours every week reading books and doing workshops in R/Python and also implementing them in my work) and still i see it is often really hard to extract a “insights” from data.

Something else to consider about the data we might consider collecting.

The proposition that using a glucose monitor by a someone who is not diabetic may cause harmful changes in diet and behaviour needs to be considered.

Here is a rationale for using a CGM without showing (not yet) signs of insuline resistance.

In any case, it is a good idea to be conscious of the own motivation to use such a device.

Exercise could cause harmful changes in your body. Maybe you should be a couch potatoe to stay safe, On the other hand you may die early by sitting on the couch,

Seriously, every longevity expert I know recommends monitoring glucose to avoid spikes and live longer. I have a watch that monitors glucose 24/7. Much easier to use than my former Dexcom G7 FDA prescription device, noninvasive and almost as accurate. Even my doc who is very lean and fit monitors his glucose for longevity reasons, not to mention exercising, functional medicine diet, and monitoring sleep every night.

Could you reveal the brand and model of this CGM watch?


What watch can read blood glucose?

Here’s one for the low low price of US$39. Care is recommended before basing decisions on these readings. :laughing:

1 Like

I also have a $30 watch that gives pretty accurate glucose readings but the one I like best is about $80 and is faster, more accurate, and looks better. Fitaos VKE400 Smart Tracker Health and Fitness Watch with ECG

You have people you can refer to to help interpret the results of your glucose monitoring. The point that the author of that piece was making is that doing such interpretation without reference to someone who knows what they talking about can cause serious problems.

As to exercise causing harm — tell me about it! I twisted my knee while taking my daily exercise in local woods. Six months later I am only now able to walk for more than 10 minutes at a time. Had a steriod injection back in early January and multiple ice-packs/paracetamol/NSAID gel sessions every day from November until a month ago. In consultation with the physio at my GP surgery I have a rehabilitation plan that will see me walking through those woods again … but not until November/December by which time I will be using Norwegian Walking Poles to provide better workouts and support.

Thank you and @Agaricus for the links. I contacted both manufacturers since there is no available evidence that smartwatches can accurately monitor blood sugar. I wonder how they get away with advertising that without public proof of its accuracy.

The FDA cleared the first wearable for CBGM only last month. It’s not a watch and the sensor must be replaced bimonthly it says. Very curious. I’ve had to stop my older family members from relying on smartwatches that claim they can measure blood pressure (they cannot). I hope this isn’t an ongoing trend :confused:

1 Like

Apple has a patent on this which was one of the drivers behind my purchase of an Apple Watch. However as they have yet to deliver on the patent in a Watch I also purchased a Withings blood pressure monitor wihch has a network link to my iPhone. (Tried using non-networked devices but I made too many transctription errors copying the results over to the Apple Health app.) If Apple does eventually have a Watch that collects FDA approved blood pressure readings then I will upgrade.

1 Like

That’s great news! Well, as great as it could be for a big powerhouse like Apple to be taking that on.

The last time I researched it, Blumio patented the method of taking BP using radar in a wearable (acquired by CardieX). There hasn’t been any news of a public product release that I’m aware of, though.

My link was definitely meant to be sarcastic. The boldness of somebody offering a $30 glucose sensing watch is sort of impressive, in a roguish way, but the actual output will be nonsense.