Non-contact acquisition of respiration and heart rates using Doppler radar with time domain peak-detection algorithm

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.

[1]  Jenshan Lin,et al.  Range correlation and I/Q performance benefits in single-chip silicon Doppler radars for noncontact cardiopulmonary monitoring , 2004, IEEE Transactions on Microwave Theory and Techniques.

[2]  Ohtsuki Tomoaki,et al.  Heartbeat Detection with Doppler Radar Based on Estimation of Average R-R Interval Using Viterbi Algorithm , 2016 .

[3]  Guanghao Sun,et al.  Design an easy-to-use infection screening system for non-contact monitoring of vital-signs to prevent the spread of pandemic diseases , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  Tomoaki Ohtsuki,et al.  Heartbeat detection with Doppler radar based on estimation of average R-R interval using Viterbi algorithm , 2016, 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[5]  Kiyoko Yokoyama,et al.  Proposal of the Evaluation Method of the Heart Rate Variability using the Frequency Information of the Electrocardiogram , 1999 .

[6]  Guanghao Sun,et al.  An infectious disease/fever screening radar system which stratifies higher-risk patients within ten seconds using a neural network and the fuzzy grouping method , 2014, Journal of Infection.

[7]  Majid Sarrafzadeh,et al.  A Self-Calibrating Radar Sensor System for Measuring Vital Signs , 2016, IEEE Transactions on Biomedical Circuits and Systems.

[8]  中川 千鶴 特集③人間工学のための計測手法:第4部:生体電気現象その他の計測と解析(5)-自律神経系指標の計測と解析- , 2016 .