Signal Processing Contributions to Contactless Monitoring of Vital Signs Using Radars

Doctoral thesis (2023)

Vital signs are a group of biological indicators that show the status of the body’s life-sustaining functions. They provide an objective measurement of the essential physiological functions of a living ... [more ▼]

Vital signs are a group of biological indicators that show the status of the body’s life-sustaining functions. They provide an objective measurement of the essential physiological functions of a living organism, and their assessment is the critical first step for any clinical evaluation. Monitoring vital sign information provides valuable insight into the patient's condition, including how they are responding to medical treatment and, more importantly, whether the patient is deteriorating. However, conventional contact-based devices are inappropriate for long-term continuous monitoring. Besides mobility restrictions and stress, they can cause discomfort, and epidermal damage, and even lead to pressure necrosis. On the other hand, 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, can be low-cost, and transmit no more power than a mobile phone. Despite recent advances, accurate contactless vital sign monitoring is still challenging in practical scenarios. The challenge stems from the fact that when we breathe, or when the heart beats, the tiny induced motion of the chest wall surface can be smaller than one millimeter. This means that the vital sign information can be easily lost in the background noise, or even masked by additional body movements from the monitored subject. This thesis aims to propose innovative signal processing solutions to enable the contactless monitoring of vital signs in practical scenarios. Its main contributions are threefold: a new algorithm for recovering the chest wall movements from radar signals; a novel random body movement and interference mitigation technique; and a simple, yet robust and accurate, adaptive estimation framework. These contributions were tested under different operational conditions and scenarios, spanning ideal simulation settings, real data collected while imitating common working conditions in an office environment, and a complete validation with premature babies in a critical care environment. The proposed algorithms were able to precisely recover the chest wall motion, effectively reducing the interfering effects of random body movements, and allowing clear identification of different breathing patterns. This capability is the first step toward frequency estimation and early non-invasive diagnosis of cardiorespiratory problems. In addition, most of the time, the adaptive estimation framework provided breathing and heart rate estimates within the predefined error intervals, being capable of tracking the reference values in different scenarios. Our findings shed light on the strengths and limitations of this technology and lay the foundation for future studies toward a complete contactless solution for vital signs monitoring. [less ▲]

Statistical Performance Analysis of Radar-Based Vital-Sign Processing Techniques

Scientific Conference (2022)

Radar-based vital-sign monitoring provides several advantages over standard methodologies. Despite the huge amount of recent work, the preference for particular technique(s) is in debt, due to lack of a ... [more ▼]

Radar-based vital-sign monitoring provides several advantages over standard methodologies. Despite the huge amount of recent work, the preference for particular technique(s) is in debt, due to lack of a formal comparison between them. In addition, collection of real data is a time-consuming process and therefore most of the proposed solutions are only evaluated under very limited scenarios. In this paper we present a simulation framework and a selection of results which allow easy performance comparison between radar-based vital-sign processing techniques. The proposed simulation tool scans over multiple breathing and heartbeat frequencies, and the combined effects along the entire signal processing chain can be analyzed, for different combinations of scenarios and techniques. The results have shown specific limitations for each method, thus indicating a need for proper selection based on operating conditions. In addition, while breathing estimation performance is only limited by noise, heartbeat estimation is limited by the presence of breathing harmonics and, despite promising results at specific breathing/heartbeat frequencies, the presented methods fail to fully mitigate this type of interference in all scenarios. [less ▲]

Adaptive Nonlinear Least Squares Framework for Contactless Vital Sign Monitoring

in IEEE Transactions on Microwave Theory and Techniques (2022)

Subpulse Processing for Unambiguous Doppler Estimation in Pulse-Doppler Noise Radars

in IEEE Transactions on Aerospace and Electronic Systems (2021)

Sidelobe Performance Analysis of Noise Waveforms Considering the Doppler Mismatch

in Proceedings of the 21st International Radar Symposium (IRS), Warsaw, Poland, 2020 (2020)

Waveform design and optimization algorithms generally assume a zero-Doppler ideal case to reach an optimum or satisfactory solution in terms of the matched filter output. Therefore, its performance is ... [more ▼]

Waveform design and optimization algorithms generally assume a zero-Doppler ideal case to reach an optimum or satisfactory solution in terms of the matched filter output. Therefore, its performance is usually characterized only in terms of the resultant waveforms autocorrelation function, neglecting the practical situation in which the received signal is modulated by the target’s Doppler shift. Within this context, this work investigates the Doppler mismatch effects in the Integrated Sidelobe Level (ISL) performance of previously designed/optimized noise waveforms. The analysis has shown that, despite much better results for steady targets, the increasing Doppler mismatch reduces the ISL performance of optimized waveforms, until similar levels achieved when no optimization is performed. To address that, a subpulse Doppler processing approach is also considered, and the results have shown that, besides increasing the Doppler tolerance, it has also increased the optimized waveform robustness to the Doppler mismatch, reducing the resultant ISL loss and thus extending its applicability. [less ▲]