Open AccessDevelopment and Evaluation of Bluetooth Low-Energy Device for Electronic Encounter Metrics
Author(s) -
Kathryn E. Keenan,
José Aumentado,
Harold Simmons Booth,
Kimberly A. Briggman,
Mikail Kraft,
Michele N. Martin,
René Peralta,
Angela Robinson,
Lynden K. Shalm,
M. Stephens,
Emily Townsend,
Sae Woo Nam
Publication year - 2022
Publication title -
journal of research of the national institute of standards and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.202
H-Index - 59
eISSN - 2165-7254
pISSN - 1044-677X
DOI - 10.6028/jres.126.043
Subject(s) - bluetooth low energy , computer science , bluetooth , contact tracing , mobile device , wearable computer , wearable technology , covid-19 , tracing , proxy (statistics) , real time computing , human–computer interaction , computer security , embedded system , wireless , telecommunications , infectious disease (medical specialty) , disease , medicine , pathology , machine learning , operating system
The coronavirus disease 2019 (COVID-19) pandemic led to the need for tracking of physical contacts and potential exposure to disease. Traditional contact tracing can be augmented by electronic tools called “electronic contact tracing” or “exposure notification.”. Some methods were built to work with smartphones; however, smartphones are not prevalent in some high-contact areas (e.g., schools and nursing homes). We present the design and initial testing of low-cost, highly privacy preserving wearable exposure notification devices. Several devices were constructed based on existing hardware and operated independently of a smartphone. The method (devices and analyses) was not able to reliably use the received signal strength indicator (RSSI) as a proxy for distance between pairs of devices; the accuracy of RSSI as a proxy for distance decreased dramatically outside of the idealized conditions. However, even an imperfect device could be useful for research on how people use and move through spaces. With some improvement, these devices could be used to understand disease spread and human or animal interaction in indoor environments.