# FaceOff: Detecting Face Touching with a Wrist-Worn Accelerometer

arXiv: https://arxiv.org/abs/2008.01769 · HTML: https://mlsanity.com/paper/2008.01769/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Aug 2020.

## Built on by (most cited first, 2 of 2)

- [Transfer: Cross Modality Knowledge Transfer using Adversarial Networks -- A Study on Gesture Recognition](https://mlsanity.com/paper/2306.15114/) (2023)
- [FaceTouch: Detecting hand-to-face touch with supervised contrastive learning to assist in tracing infectious disease](https://mlsanity.com/paper/2308.12840/) (2023)

## Abstract (arXiv)

According to the CDC, one key step of preventing oneself from contracting coronavirus (COVID-19) is to avoid touching eyes, nose, and mouth with unwashed hands. However, touching one's face is a frequent and spontaneous behavior---one study observed subjects touching their faces on average 23 times per hour. Creative solutions have emerged amongst some recent commercial and hobbyists' projects, yet most either are closed-source or lack validation in performance. We develop FaceOff---a sensing technique using a commodity wrist-worn accelerometer to detect face-touching behavior based on the specific motion pattern of raising one's hand towards the face. We report a survey (N=20) that elicits different ways people touch their faces, an algorithm that temporally ensembles data-driven models to recognize when a face touching behavior occurs and results from a preliminary user testing (N=3 for a total of about 90 minutes).