Radar Based Breathing Monitor — Biomedical Instrumentation & Clinical Sensing

Abstract — Radar Based Breathing Monitor

Modern microwave Doppler radar-based physiological sensing is playing an important role in healthcare applications and during the last decade, there has been a significant advancement in this non-contact respiration sensing technology. The advantages of contactless, unobtrusive respiration monitoring have drawn interest in various medical applications such as sleep apnea, sudden infant death syndromes (SIDS), remote respiratory monitoring of burn victims, and COVID patients. This paper provides a perspective on recent advances in biomedical and healthcare applications of Doppler radar that can detect the tiny movement of the chest surfaces to extract heartbeat and respiration and its associated different vital signs parameters (tidal volume, heart rate variability (HRV), and so on) of the human subject. Additionally, it also highlights the challenges, and opportunities of this remote physiological sensing technology and several future research directions will be laid out to deploy this sensor technology in our day-to-day life.

Sensor Interfacing & Analog Front-End Conditioning

There is a growing need for continuous monitoring of the vital signs of humans for assessing their health status ( Massaroni et al., 2019 ). Two different types of modalities such as contact sensors (finger pulse, chest belt) and non-contact sensors (Radar and Camera) are used for monitoring different vital signs such as breathing rate and heart rate ( Massaroni et al., 2020 ). Contactless remote sensing of vital signs is gaining more attention than contact sensors as it is unobtrusive and users need not intentionally engage themselves with the system ( Molinaro et al., 2022 ). Non-Contact and unobtrusive monitoring of human cardiopulmonary activity is one of the promising solutions for remote respiratory monitoring of COVID patients, sleep apnea diagnosis, post-surgery monitoring, in-home elderly people fall detection, and life signs detection under debris for post-disaster search and rescue applications ( Broic-Lubecke et al., 2012 ; Li et al., 2013 ; Islam et al., 2021 ; Li et al., 2021 ).

Bio-Signal Waveform Analysis & Simulation Findings

One of the potential advantages of this technology is that without attaching any sensor to the body it could facilitate the health monitoring of lonely elderly patients in home settings, enable sleep monitoring of patients without any expensive sleep Among the non-contact sensing modalities, Radar seems more promising than a camera as it is privacy-invasive and no imaging technology is required for vital signs sensing ( Li et al., 2021 ). Table 1 illustrates the comparison between the Radar and Camera for vital signs monitoring. For vital signs extraction using the camera is mostly performed from the intensity of the light and the phase information of the reflected echoes of the Radar can also extract vital signs. Radar is mostly employed for military and defense applications such as detecting aircraft and ships but last few decades it has been modified for biomedical applications ( Islam, 2020 ). Commercially available radar system such as 2.4 GHz–24 GHz Frequency modulated continuous wave (FMCW) RADAR is available in the market and can be used for vital signs monitoring ( Islam et al., 2022a ). Doppler radar remote respiration sensing technology has shown potential in several applications and demonstrated proof of concept in numerous disease assessments such as obstructive sleep apnea (OSA), Sudden Infant Death Syndrome (SIDS), and COVID-19 as well ( Li et al., 2013 ; Islam et al., 2021 ). The efficacy of this remote respiration sensing technology has also been proven during the COVID-19 pandemic time as it can track the status of breathing remotely without attaching any sensor to the body ( Islam et al., 2021 ).

Scope & Clinical Applications

• Real-time multi-parameter vital signs telemetry (ECG, Heart Rate, SpO2, Temperature, Respiration)
• Low-noise Analog Front-End (AFE) conditioning with active Driven Right Leg (DRL) 50 Hz cancellation
• Digital signal processing in MATLAB: Pan-Tompkins QRS detection, FIR/IIR notch, and Continuous Wavelet Transforms
• Finite element tissue bio-electromagnetics and orthopedic mechanical simulations in COMSOL & ANSYS
• Complete Arduino firmware .INO sketches, circuit schematics, and university dissertation reports