Machine Learning for Respiratory Detection Via UWB Radar Sensor
- Resource Type
- Conference
- Authors
- Elhadad, Anwar; Sullivan, Timothy; Wshah, Safwan; Xia, Tian
- Source
- 2020 IEEE International Symposium on Circuits and Systems (ISCAS) Circuits and Systems (ISCAS), 2020 IEEE International Symposium on. :1-5 Oct, 2020
- Subject
- Components, Circuits, Devices and Systems
Shape
Reflection
Radar antennas
Aluminum
Machine learning
Ultra wideband radar
UWB radar
respiratory measurement
machine learning
- Language
- ISSN
- 2158-1525
This paper focuses on detecting the respiratory of a person by utilizing a doppler radar to monitor the chest movement during respiration. Specifically, machine learning approach in conjunction with the radar sensor is utilized to capture the radar reflection pulse signal and its movement patterns. By analyzing the evolution of the reflected pulse while breathing, the respiratory rate can be accurately measured. In addition, the change of respiration ratio and respiration patterns can be characterized.