Why Sleep and Strain Scores Offer False Precision
Easter argues that consumer wearables can substantially mismeasure steps and become even less trustworthy when compressing sleep or workout strain into a score. Wrist heart-rate noise, broad assumptions, and large individual differences make a universal number look more authoritative than the underlying data warrants.
- Step estimates can be materially inaccurate and tend to overestimate
- Wrist heart-rate readings contain significant noise
- Sleep algorithms rely on assumptions that may not hold for an individual
- A poor score can override how rested a person actually feels
- Sleep needs and preferred conditions differ between people
“wearables that score something like sleep or give you like a strain count or something like that for your workouts those are I mean they're…”
“by trying to like put this all in a single number for everyone it just it doesn't make any damn sense”