How science works, explained with smartbands

https://www.youtube.com/watch?v=csSzD0KAcpw

How do you know if you really slept well last night?

Perhaps this sounds familiar. Yesterday you went to bed early. You turned off your phone, avoided coffee after six, even skipped that episode of your favorite show. And yet, this morning you woke up tired. What happened? Did you really sleep well? And how could you observe it if… you were asleep?

This apparently trivial question hides one of the deepest problems in science: how can we objectively know something when the very act of knowing interferes with what we want to know?

The goal of science (and why it's not as obvious as it seems)

Most people—and even many scientists—don't understand or stop to really think about what makes a science, science. I'm not talking about discovering new things or inventing useful technologies. I'm talking about a more fundamental goal: building objective descriptions of reality.

This means symbolically representing a world that exists independently of what you or I think or feel. A world we can partially influence, yes, but one we don't fully control. It's in this rigorous construction process that scientific truths are forged.

But here we run into a problem.

Kant's chewing gum: observing is interfering

The philosopher Immanuel Kant realized centuries ago: observing the world is simultaneously interfering with it. If knowing were a direct relationship between a Subject (you) and an Object (the world), how can we be sure we perceive things as they really are? To what extent does our way of looking condition or distort what we want to know?

Put another way: how do we know that a rose is truly red and not simply the result of our perception?

It's like trying to peel chewing gum stuck to one hand… using the other hand. There seems to be no way to get rid of the damn gum.

The solution: scientific instruments

To circumvent this problem, science developed under the protection of a brilliant strategy: using instruments. A physicist's scale, a chemist's pipette, a biologist's microscope… they are material operators that transform some phenomena into others, neutralizing the particular subject who observes. Thanks to them, we aim to measure precisely without our biases, prejudices, or physical limitations interfering (as much).

But still, a legitimate question remains: to what extent does that device truly measure what it claims to measure?

My insomnia and the smartband: can I trust it?

A few years ago I had insomnia. It became a really serious problem, and being a scientist, I tried to approach it scientifically. I decided to buy a smartband to monitor it. The idea was simple: if I could measure how much and how I slept, maybe I could associate my routines (exercise, dinner, screens…) with sleeping better or worse.

But the doubt soon arose: how could I trust what the smartband was saying? Sometimes the results didn't seem very consistent. Other times they contradicted my feelings upon waking. Had I slept well or badly? Who was right: me or the device?

How these things measure sleep

Smartbands and smartwatches don't measure sleep directly. They don't have an electroencephalogram like those in a sleep lab. Instead, they combine several indirect sensors, for example:

• Accelerometer and gyroscope: detect whether you're moving or staying still.

• Optical photoplethysmography (PPG): measures your heart rate and its variability. A low and stable rate usually indicates deep sleep; a more erratic one, light sleep or REM.

• Blood oxygen: drops can signal apneas or transitions between phases.

• Skin temperature: usually drops at the beginning of sleep and rises in REM or upon waking.

• Estimated respiration: derived from other sensors, helps identify deep sleep vs REM.

  
  

With all this, advanced algorithms (often with artificial intelligence) estimate how much time you spent in each phase of sleep: awake, light, deep, REM.

Sounds good. Moreover, each device can use a different combination of sensors and algorithms. And this is where the insight comes in.

The trick: using two smartbands at once

If one smartband tells me one thing, how do I know it's not biased by its particular technology? The answer is simple: I use two different smartbands at the same time.

And by "different" I don't just mean different brands, but that they use different technological systems for their measurements. One might prioritize PPG and another the accelerometer. One might have a temperature sensor and another might not.

If both give me consistent readings—for example, both say I slept 7 hours with 2 hours of deep sleep—then I can trust them. If they don't match, then I can't trust either one.

Aha!

Material synthetic identity: the key to scientific truth

And here comes the profound generalization of this idea, from the hand of Spanish philosopher Gustavo Bueno, who called it material synthetic identity. The idea is brilliant: if two (or more) independent operational procedures converge on the same result, then that result must express a necessary scientific truth.

It's the confluence of independent methods that allows us to segregate scientific truth from the biases of each particular method. Without that confluence, we'd be left with the suspicion that the result is conditioned by the procedure followed.

In fact, our own body already implicitly applies this principle: we have two eyes, two ears. Try covering one eye and trying to put the cap on a pen at different distances. You'll see that it's easy to miss. Each eye gives us a biased estimate of distance. It's the contrast between both versions that allows our brain to calculate distance precisely.

Conclusion: science is more fascinating than it seems

Measuring sleep with two smartbands may seem like an anecdotal detail. But in reality it's a perfect example of how science works: building truths through the convergence of independent procedures, neutralizing biases and overcoming the limitations of each particular instrument.

The foundations of science go much further, of course. If you liked this topic and want to delve deeper, I recommend chapter 9 of my book Everything I Can Imagine: The Algorithm of Understanding (Part II) [which you can read here], where I develop the foundations of science in much more detail and explain its importance for our daily lives.

Because in the end, understanding how we know the world isn't just abstract philosophy. It's something that affects us every time we look at our smartband data, read a scientific paper, or simply try to understand what's real and what isn't.

And that, in 2026, matters more than ever.