How AI Nail Biting Detection Works

Stop Biting uses MediaPipe and WebAssembly to detect nail biting in real time — entirely on your device. Setup takes under two minutes.

Why awareness is the bottleneck

Most nail biters catch fewer than half of their daily biting episodes through self-monitoring alone. The habit is automatic — it runs below the threshold of conscious awareness. Habit Reversal Training (the gold-standard treatment) identifies awareness training as its most critical component. Stop Biting automates that component: it catches the episodes you don't notice.

Getting started

  1. Open the app. Visit stopbiting.today in Chrome, Edge, or Firefox — or download the macOS/Windows desktop app.
  2. Grant camera access. Allow the app to use your webcam. The video is processed locally — nothing is ever transmitted.
  3. Position your webcam. Make sure your face and hands are visible in the camera view. The AI tracks hand-to-mouth movements.
  4. Work normally. The app runs in the background. When it detects nail biting, an audible alarm fires immediately.
  5. Perform your competing response. When the alarm fires, press both palms flat on your desk for 60 seconds — the physical incompatibility breaks the habit chain.

Technical specifications

  • Detection model: Google MediaPipe Hand Landmarker (21 landmarks)
  • Processing: WebAssembly — sandboxed, on-device, no network access
  • Alarm latency: under 1 second from detection to alarm
  • Incident logging: timestamped log stored locally — never transmitted

Common questions

What happens to my camera data?

Nothing. The video feed is processed frame-by-frame by the MediaPipe WASM binary running locally. No frames, no thumbnails, no data of any kind is sent to any server — you can verify this by watching your network traffic while the app runs.

Does it work on Mac, Windows, and Linux?

The web app works on any device with a modern browser and webcam — Mac, Windows, Linux, and Chromebook. Native desktop apps are available for macOS and Windows for system-tray background running.

Will it false-alarm when I'm eating or touching my face?

The detection model distinguishes sustained hand-to-mouth proximity from brief touches, and sensitivity can be adjusted in settings.

Learn more