The Poorly-Quantified Self
I wear a fitness tracker on my wrist to measure my daily steps and heart rate during workouts. At home, I have a smart scale that syncs measurements of my weight and body fat percentage in the same app where I track my movements.
Recently, I’ve become frustrated by chronic errors within my “quantified self” setup. These errors may be systemic or user-generated, I’m not 100% sure. When I update unrelated settings, the “calories burned” estimate for my workout jumps around. At home, the body fat % on my scale is over 8% higher than the number captured by my personal trainer using calipers.
This led me to wonder: how on earth can I be sure my quantified self is being quantified correctly?
The majority of the fitness tracking industry is predicated on blind trust. Sure, news outlets like Wirecutter use third-party tools to test the accuracy of these devices, but they typically only evaluate the earliest lifetime of a product.
People constantly ask about the value and impact of the quantified self, but I’ve yet to see a real evaluation of the implications inaccurate data can have. For many people, these numbers provide a barometer of success/failure in diet plans and exercise routines.
Turns out, it becomes much harder to gaining meaningful insight from the “quantified self” when you lose confidence in the numbers themselves.
What’s your experience with fitness trackers and health-adjacent IoT devices?