The itch
Levine's NEAT (Non-Exercise Activity Thermogenesis) research stopped us mid-scroll: habitual fidgeters can burn around 350 kcal more per day than sedentary people — not through any structured exercise, just unconscious leg motion. The frustrating part was having no way to know which category you fall into on any given day, or even which hour. So we built BinBot.
How the detection works
The core is a 100Hz CoreMotion capture pipeline run through a 3–9Hz IIR bandpass filter. Human fidget motion tends to live in that frequency window. Walking sits lower — around 0.5–2Hz — and ambient vibration from cars or trains is irregular enough to mostly fall outside the band. A five-layer rhythm classifier runs on top of that to further reduce false positives.
Three motion modes are identified and tracked separately: vibrate, jump, and spin. All counts write to HealthKit. Apple Watch is supported for independent logging, and there is a home screen widget plus Live Activity for quick at-a-glance counts throughout the day.
What it actually feels like to use
You pocket your phone in the morning and forget about it. By evening you have a number. The first day it is meaningless without context — fidgeting varies too much between people for a universal baseline to exist. But after a week you start seeing your own pattern. After a month subtler things emerge: certain environments or task types produce more motion, sometimes tracking loosely against how focused or restless you felt.
The honest part
Walking and car vibrations do occasionally trigger false counts. Watch-to-iPhone sync is one-directional for now — the biggest rough edge we plan to address. BinBot is better framed as a trend instrument than a precise measurement tool. The relative changes day to day are more meaningful than any single absolute count.
Free, ad-supported. If you want to put a number on how much you actually fidget:
https://apps.apple.com/jp/app/id6760091302
SOCIAL SHARE CARD GENERATOR