How AI Calculates Your Sleep Score and What It Actually Means

Every morning, your wearable presents you with a number. Maybe it's 85, maybe it's 72. But what does that score actually represent? Understanding how AI calculates your sleep score can help you make better decisions about your rest.

The Building Blocks of Sleep Scores

Modern sleep tracking uses multiple data points to estimate sleep quality. The primary inputs include movement patterns, heart rate, and heart rate variability (HRV). Some devices also track skin temperature and blood oxygen levels.

Sleep Staging: Deep, Light, and REM

AI algorithms attempt to classify your sleep into stages based on physiological signals. Deep sleep shows lower heart rates and minimal movement. REM sleep exhibits irregular heart rate patterns similar to wakefulness but with near-complete stillness. Light sleep falls somewhere in between.

Why Your Score Varies Night to Night

Several factors influence your nightly score: alcohol consumption, late meals, stress levels, exercise timing, and room temperature. The AI weighs these against your personal baseline, which is why the same sleep duration can produce different scores.

What to Focus On

Rather than obsessing over a single number, look for trends. Consistent scores matter more than perfect nights. Pay attention to what habits correlate with better scores for your body specifically.