# Respiratory Anomaly Detection using Reflected Infrared Light-wave Signals

arXiv: https://arxiv.org/abs/2311.01367 · HTML: https://mlsanity.com/paper/2311.01367/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 41 references that are in the map.
- First posted on arXiv 2 Nov 2023.

## Builds on (most cited first, 3 of 3)

- [DistancePPG: Robust non-contact vital signs monitoring using a camera](https://mlsanity.com/paper/1502.08040/) (2015)
- [WiFi-based Real-time Breathing and Heart Rate Monitoring during Sleep](https://mlsanity.com/paper/1908.05108/) (2019)
- [Non-contact Vital Signs Monitoring through Visible Light Sensing](https://mlsanity.com/paper/1807.05408/) (2018)

## Abstract (arXiv)

In this study, we present a non-contact respiratory anomaly detection method using incoherent light-wave signals reflected from the chest of a mechanical robot that can breathe like human beings. In comparison to existing radar and camera-based sensing systems for vitals monitoring, this technology uses only a low-cost ubiquitous infrared light source and sensor. This light-wave sensing system recognizes different breathing anomalies from the variations of light intensity reflected from the chest of the robot within a 0.5m-1.5m range with an average classification accuracy of up to 96.6% using machine learning.