How do smartwatches track body signals?

20 Tem 23:39

Well, to start with, the most common thing in smartwatches and fitness trackers is the use of **optical sensors (PPG) for heart rate measurement**. These green or red LEDs emit light that reflects off the blood, and a photodetector captures changes in light absorption based on heartbeats. It's the same technology used in wrist blood pressure monitors, but with filtering algorithms to avoid motion artifacts. As for **sleep analysis**, most devices combine data from the accelerometer (movement) with heart rate variability (HRV). When HRV is low and movement drops drastically, the algorithm concludes you're in REM or deep sleep. That said, motion sensors (like those in Mi Band) are less accurate than the ECG in an Apple Watch or Whoop strap, which use electrodes directly on the skin. For **stress tracking**, some devices (like Garmin) use resting heart rate variability (HRV) along with breathing. Low HRV often correlates with higher stress, and that's where the magic of *machine learning* comes in: manufacturers train their algorithms with datasets from thousands of users to refine readings. That explains why the same watch might give you a 7/10 stress level one day and a 4/10 the next, even in similar situations. If you're after accuracy, forget about cheap Chinese brands and go for ones like **Apple, Garmin, or Whoop**, which use higher-end sensors (like oximeters, and even real ECG in some cases) and have R&D teams to validate data. Though, mind you, even they aren’t flawless: PPG readings can be affected by dark skin, hair, or even sweat. I skip sleep metrics in the summer because my Garmin Series 7 goes haywire in the heat.