Harmonic Multiple Loop Detection (HMLD) Algorithm for Not-Contact Vital Sign Monitoring Based on Ultra-Wideband (UWB) Radar

Yi Zhang,Zihang Qi,Hua Zhu,Rui Qi,Xiuping Li

doi:10.1109/access.2020.2976104

Yi Zhang, Zihang Qi + Show 3 more

Open Access

https://doi.org/10.1109/access.2020.2976104

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Abstract

In this paper, the harmonic multiple loop detection (HMLD) algorithm for heart rate (HR) and respiration rate (RR) estimation with impulse radio ultrawideband (IR-UWB) radar is introduced. The algorithm includes two parts: one is the harmonic multiple discriminant principle and the other is the cyclic spectrum updating process. The harmonic multiple discriminant principle is used to detect whether the peak point in the fundamental frequency band is the true vital sign signal. The cyclic spectrum updating process can remove the error peak point according to the results obtained from the part one. In this algorithm, threshold setting is not needed and the estimation error caused by the erroneous threshold can be reduced. Only the fundamental and second harmonic frequencies are needed for HR and RR estimation, so the algorithm has strong environmental robustness and low requirement of radar hardwares. Compared with other algorithms, HMLD algorithm provides reasonable average error rates (4.95% and 5.06%) compared to real data from the oximeter in RR and HR detection. The real-time vital signs detection experiment shows that HMLD algorithm can not only detect the vital signs rate and record the historical curve in real time, but also detect the location information, which proves the validity of HMLD algorithm in real-time vital signs detection.

Highlights

Vital sign detection is an essential part of the medical, health care and military field
The red circle is the error point rejected by the loop mechanism
The multiple error calculated from the pending fundamental frequency is 0.0527

Summary

Introduction

Vital sign detection is an essential part of the medical, health care and military field. By measuring respiratory rate (RR) and heart rate (HR), medical staff can diagnose clinical disease for patients and monitor disease through vital signs [1]–[5]. The current common method of detecting vital signs is to contact the human body to obtain vital signs information, such as pulse-oximetry and electrocardiogram (ECG). For those who are not suitable for skin contact, such as burn patients or newborns, contact vital sign detection. In the case of long-term monitoring, contact vital sign detection equipment is inconvenient and uncomfortable. It is necessary to study the non-contact vital sign detection method

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