Non-contact acquisition of respiration and heart rates using Doppler radar with time domain peak-detection algorithm
- 1 July 2017
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
- Vol. 2017 (1557170X), 2847-2850
- https://doi.org/10.1109/embc.2017.8037450
Abstract
The non-contact measurement of the respiration rate (RR) and heart rate (HR) using a Doppler radar has attracted more attention in the field of home healthcare monitoring, due to the extremely low burden on patients, unconsciousness and unconstraint. Most of the previous studies have performed the frequency-domain analysis of radar signals to detect the respiration and heartbeat frequency. However, these procedures required long period time (approximately 30 s) windows to obtain a high-resolution spectrum. In this study, we propose a time-domain peak detection algorithm for the fast acquisition of the RR and HR within a breathing cycle (approximately 5 s), including inhalation and exhalation. Signal pre-processing using an analog band-pass filter (BPF) that extracts respiration and heartbeat signals was performed. Thereafter, the HR and RR were calculated using a peak position detection method, which was carried out via LABVIEW. To evaluate the measurement accuracy, we measured the HR and RR of seven subjects in the laboratory. As a reference of HR and RR, the persons wore contact sensors i.e., an electrocardiograph (ECG) and a respiration band. The time domain peak-detection algorithm, based on the Doppler radar, exhibited a significant correlation coefficient of HR of 0.92 and a correlation coefficient of RR of 0.99, between the ECG and respiration band, respectively.Keywords
This publication has 5 references indexed in Scilit:
- Special Issues No.3 : Measurement Technique for ErgonomicsThe Japanese Journal of Ergonomics, 2016
- A Self-Calibrating Radar Sensor System for Measuring Vital SignsIEEE Transactions on Biomedical Circuits and Systems, 2015
- An infectious disease/fever screening radar system which stratifies higher-risk patients within ten seconds using a neural network and the fuzzy grouping methodJournal of Infection, 2014
- Range Correlation and$ I/ Q$Performance Benefits in Single-Chip Silicon Doppler Radars for Noncontact Cardiopulmonary MonitoringIEEE Transactions on Microwave Theory and Techniques, 2004
- Proposal of the Evaluation Method of the Heart Rate Variability using the Frequency Information of the ElectrocardiogramIEEJ Transactions on Electronics, Information and Systems, 1999