Contactless radar-based vital sign monitoring
The breathing rate and the heart rate are critical physiological parameters. They play a crucial role in the early detection of conditions that affect the well-being of a patient. By continuously monitoring these vital signs, it is possible to detect drowsiness, sleep apnea, or even depression.
Conventional monitoring devices, always connected by cables, are inappropriate or even useless in many situations. Besides mobility restrictions and stress, they can cause discomfort, epidermal damage, and even lead to pressure necrosis. Therefore, these conventional cabled devices are not an option for long-term monitoring.
In this context, the contactless monitoring of vital signs using radar devices has several advantages. Radar signals can penetrate through different materials and are not affected by skin pigmentation or external light conditions. Additionally, these devices preserve privacy, they can be low-cost and they transmit no more power than a mobile phone.
Despite recent advances, accurate contactless vital sign monitoring is still challenging in practical scenarios. The radar sees the breathing and heartbeat movements through phase modulations in its received signal. The challenge stems from the fact that when we breathe or when the heart beats, the tiny induced motion of the chest surface can be smaller than one millimeter. This means that these vital signs can be easily lost in the background noise, or even masked by random body movements.
The goal of this research is to propose innovative radar signal processing solutions in order to enable contactless vital sign monitoring in practical scenarios.
Relevant publications
- Beltrão, G., Stutz, R., Hornberger, F., Martins, W. A., Tatarinov, D., Alaee-Kerahroodi, M., … & Zemlin, M. Contactless radar-based breathing monitoring of premature infants in the neonatal intensive care unit. Scientific Reports, 12(1), 1-15 (2022).
Clinical setup. (a) Conventional monitoring of premature neonate: connection by cables to the central monitoring unit (heart rate, oxygen saturation, respiration), and an additional peripheral venous catheter. (b) NICU room view. Both radar and the reference cabled device were controlled from the external computer. (c) Close top view. The radar was attached to a low-vibration tripod, 45 cm away from the infant. (d) Close side view with twins sharing the same bed.
Abstract: Vital signs monitoring systems are essential in the care of hospitalized neonates. Due to the immaturity of their organs and immune system, premature infants require continuous monitoring of their vital parameters, and sensors need to be directly attached to their fragile skin. Besides mobility restrictions and stress, these sensors often cause skin irritation and may lead to pressure necrosis. In this work, we show that a contactless radar-based approach is viable for breathing monitoring in the Neonatal Intensive Care Unit (NICU). For the first time, different scenarios common to the NICU daily routine are investigated, and the challenges of monitoring in a real clinical setup are addressed through different contributions in the signal processing framework. Rather than just discarding measurements under strong interference, we present a novel random body movement mitigation technique based on the time-frequency decomposition of the recovered signal. In addition, we propose a simple and accurate frequency estimator which explores the harmonic structure of the breathing signal. As a result, the proposed radar-based solution is able to provide reliable breathing frequency estimation, which is close to the reference cabled device values most of the time. Our findings shed light on the strengths and limitations of this technology and lay the foundation for future studies toward a completely contactless solution for vital signs monitoring.
- Beltrão G., Alaee-Kerahroodi, M., Schroeder, U., Tatarinov D. and Bhavani Shankar M. R. Nonlinear Least Squares Estimation for Breathing Monitoring Using FMCW Radars. Presented at the 2021 European Radar Conference (EURAD) (2021)
Setup for the measurements.
Abstract: In this paper we propose a novel framework for breathing monitoring, based on a simple Nonlinear Least Squares (NLS) estimation, which explores the harmonic structure of the breathing displacement signal. The first part of the study was performed using a controlled target which could be programmed for executing breathing-like movements, thus emulating the chest-wall displacement over time. Finally, the proposed approach was evaluated with real human data, and the results have shown robust and accurate estimation, outperforming previous methods over different scenarios.
- Beltrão G., Alaee-Kerahroodi, M., Schroeder, U. and Bhavani Shankar M. R. Joint Waveform/Receiver Design for Vital-Sign Detection in Signal-Dependent Interference. IEEE Radar Conference (RadarConf20), 2020, pp. 1-6 (2020).
Abstract: This paper presents the joint design of discrete slow-time radar waveform and receive filter, with the aim of enhancing the Signal to Interference and Noise Ratio (SINR) in phase coded radar systems for vital-sign monitoring. Towards this, we consider maximizing the SINR at the input of the vital-sign estimation block, when transmitting hardware efficient Mary Phase Shift Keying (MPSK) sequences. This multi-variable and non-convex optimization problem is efficiently solved based on a Minimum Variance Distortionless Response (MVDR) filter, with the Coordinate Descent (CD) approach for the sequence optimization, and the obtained results have shown attractive interference suppression capabilities, even for the simple binary case.
Some more stuff
Below is a video with some vital sign measurements at the SnT radar lab.
About me
I am a signal processing researcher with experience in radar systems. I received my MSc degree in Electrical Engineering, from the University of Campinas (UNICAMP) in 2012. I have BSc degrees in Telecommunications Technology (2006) and Electrical Engineering (2009) from the University of Campinas (UNICAMP) and University Salvador (UNIFACS), respectively. In 2011, I started working as a radar signal processing engineer, initially within the Radar Division of Bradar – Embraer Defense and Security, and, in 2016, I joined the Special Radar Projects Group of the Brazilian Army Technology Center. Since 2019, I’ve been working as a Doctoral Researcher at the Interdisciplinary Centre for Security, Reliability, and Trust (SnT), at the University of Luxembourg, where I’m pursuing a Ph.D. degree in the area of radar signal processing. My research interests include radar signal processing, waveform design, and vital sign monitoring with radars.
Hello, I’m Rosie Zhou. I had some doubts while studying your paper. Am I fortunate enough to be able to get your matlab code for further research? You can contact me by 15073536708@163.com this email address. I would be very happy to hear from you.