A Scalable Solution for Signaling Face Touches to Reduce the Spread of Surface-based Pathogens
Name
3448121.pdf
Description
Published version
Size
3.6 MB
Format
Adobe PDF
Checksum (MD5)
a08704d4394dd82bd39585da3fd70db9
Author(s)
Rojas, Camilo
Poulsen, Niels
Van Tuyl, Mileva
Vargas, Daniel
Cohen, Zipporah
Paradiso, Joe
Maes, Pattie
Esvelt, Kevin
Adib, Fadel
Date Issued
2021
Journal
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Publisher
Association for Computing Machinery (ACM)
Citation
Rojas, Camilo, Poulsen, Niels, Van Tuyl, Mileva, Vargas, Daniel, Cohen, Zipporah et al. 2021. "A Scalable Solution for Signaling Face Touches to Reduce the Spread of Surface-based Pathogens." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 5 (1).
Version
Final published version
Abstract
Hand-to-Face transmission has been estimated to be a minority, yet non-negligible, vector of COVID-19 transmission and a major vector for multiple other pathogens. At the same time, as it cannot be effectively addressed with mainstream protection measures, such as wearing masks or tracing contacts, it remains largely untackled. To help address this issue, we have developed Saving Face - an app that alerts users when they are about to touch their faces, by analyzing the distortion patterns in the ultrasound signal emitted by their earphones. The system only relies on pre-existing hardware (a smartphone with generic earphones), which allows it to be rapidly scalable to billions of smartphone users worldwide. This paper describes the design, implementation and evaluation of the system, as well as the results of a user study testing the solution's accuracy, robustness, and user experience during various day-to-day activities (93.7% Sensitivity and 91.5% Precision, N=10). While this paper focuses on the system's application to detecting hand-to-face gestures, the technique can also be applicable to other types of gestures and gesture-based applications.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3448121
