UbiBreathe: A Ubiquitous non-Invasive WiFi-based Breathing Estimator

TL;DR

UbiBreathe is a novel WiFi-based system that non-invasively estimates breathing rates and detects apnea using signal strength changes, enabling ubiquitous respiratory monitoring with high accuracy in various environments.

Contribution

The paper introduces UbiBreathe, a system leveraging WiFi RSS patterns for non-invasive respiratory monitoring, handling noise and movement challenges, with high accuracy in diverse scenarios.

Findings

Estimates breathing rates with less than 1 bpm error.

Detects apnea with over 96% accuracy.

Operates effectively in various environmental conditions.

Abstract

Monitoring breathing rates and patterns helps in the diagnosis and potential avoidance of various health problems. Current solutions for respiratory monitoring, however, are usually invasive and/or limited to medical facilities. In this paper, we propose a novel respiratory monitoring system, UbiBreathe, based on ubiquitous off-the-shelf WiFi-enabled devices. Our experiments show that the received signal strength (RSS) at a WiFi-enabled device held on a person's chest is affected by the breathing process. This effect extends to scenarios when the person is situated on the line-of-sight (LOS) between the access point and the device, even without holding it. UbiBreathe leverages these changes in the WiFi RSS patterns to enable ubiquitous non-invasive respiratory rate estimation, as well as apnea detection. We propose the full architecture and design for UbiBreathe, incorporating various modules that help reliably extract the hidden breathing signal from a noisy WiFi RSS. The system handles various challenges such as noise elimination, interfering humans, sudden user movements, as well as detecting abnormal breathing situations. Our implementation of UbiBreathe using off-the-shelf devices in a wide range of environmental conditions shows that it can estimate different breathing rates with less than 1 breaths per minute (bpm) error. In addition, UbiBreathe can detect apnea with more than 96% accuracy in both the device-on-chest and hands-free scenarios. This highlights its suitability for a new class of anywhere respiratory monitoring.