A Review on Biomedical MIMO Radars for Vital Sign Detection and Human Localization

Respiration and Heart Rate Monitoring in Smart Homes: An Angular-Free Approach with an FMCW Radar

This paper proposes a new approach for wide angle monitoring of vital signs in smart home applications. The person is tracked using an indoor radar. Upon detecting the person to be static, the radar automatically focuses its beam on that location, and subsequently breathing and heart rates are extracted from the reflected signals using continuous wavelet transform (CWT) analysis. In this way, leveraging the radar's on-chip processor enables real-time monitoring of vital signs across varying angles. In our experiment, we employ a commercial multi-input multi-output (MIMO) millimeter-wave FMCW radar to monitor vital signs within a range of 1.15 to 2.3 m and an angular span of -44.8 to +44.8 deg. In the Bland-Altman plot, the measured results indicate the average difference of -1.5 and 0.06 beats per minute (BPM) relative to the reference for heart rate and breathing rate, respectively.

Incorporation of Digital Modulation into Vital Sign Detection and Gesture Recognition Using Multimode Radar Systems

The incorporation of digital modulation into radar systems poses various challenges in the field of radar design, but it also offers a potential solution to the shrinking availability of low-noise operating environments as the number of radar applications increases. Additionally, digital systems have reached a point where available components and technology can support higher speeds than ever before. These advancements present new avenues for radar design, in which digitally controlled phase-modulated continuous wave (PMCW) radar systems can look to support multiple collocated radar systems with low radar-radar interference. This paper proposes a reconfigurable PMCW radar for use in vital sign detection and gesture recognition while utilizing digital carrier modulation and compares the radar responses of various modulation schemes. Binary sequences are used to introduce phase modulation to the carrier wave by use of a field programable gate array (FPGA), allowing for flexibility in the modulation speed and binary sequence. Experimental results from the radar demonstrate the differences between CW and PMCW modes when measuring the respiration rate of a human subject and in gesture detection.

Analysis of Signal Processing Methods to Reject the DC Offset Contribution of Static Reflectors in FMCW Radar-Based Vital Signs Monitoring

Frequency-modulated continuous wave (FMCW) radars are currently being investigated for remote vital signs monitoring (measure of respiration and heart rates) as an innovative wireless solution for healthcare and ambient assisted living. However, static reflectors (furniture, objects, stationary body parts, etc.) within the range or range angular bin where the subject is present contribute in the Doppler signal to a direct current (DC) offset. The latter is added to the person's information, containing also a useful DC component, causing signal distortion and hence reducing the accuracy in measuring the vital sign parameters. Removing the sole contribution of the unwanted DC offset is fundamental to perform proper phase demodulation, so that accurate vital signs monitoring can be achieved. In this work, we analyzed different DC offset calibration methods to determine which one achieves the highest accuracy in measuring the physiological parameters as the transmitting frequency varies. More precisely, by using two FMCW radars, operating below 10 GHz and at millimeter wave (mmWave), we applied four DC offset calibration methods to the baseband radar signals originated by the cardiopulmonary activities. We experimentally determined the accuracy of the methods by measuring the respiration and the heart rates of different subjects in an office setting. It was found that the linear demodulation outperforms the other methods if operating below 10 GHz while the geometric fitting provides the best results at mmWave.

Frequency Error Compensation of Unsynchronized Bistatic CW- MIMO Radar for Multiple Human-Body Localization

This article presents and experimentally evaluates a frequency error elimination technique suitable for unsynchronized bistatic Multiple-Input Multiple-Output (MIMO) radar for human-body detection. First, a mathematical expression of human-body localization using bistatic MIMO radar is presented. Then the direct path is used to eliminate the phase error created by the frequency difference between the transmitter and receiver. A new Doppler-shifted component of the MIMO channel without phase error is derived, and the locations of the multiple targets are calculated by the 2-dimensional MUltiple SIgnal Classification (MUSIC) method. Next, the results of simulations that examine frequency error versus power ratios are discussed to illustrate the effectiveness of the proposed method. An experiment is carried out in an indoor multipath-rich environment. To emulate the unsynchronized condition, the transmitter and receiver use independent Signal Generators (SGs). One to six targets are tested. The experiments demonstrate that our unsynchronized radar system can identify the locations of multiple targets with high accuracy.

Effects of Receiver Beamforming for Vital Sign Measurements Using FMCW Radar at Various Distances and Angles

Short-range millimeter wave radar sensors provide a reliable, continuous and non-contact solution for vital sign extraction. Off-The-Shelf (OTS) radars often have a directional antenna (beam) pattern. The transmitted wave has a conical main lobe, and power of the received target echoes deteriorate as we move away from the center point of the lobe. While measuring vital signs, the human subject is often located at the center of the antenna lobe. Since beamforming can increase signal quality at the side (azimuth) angles, this paper aims to provide an experimental comparison of vital sign extraction with and without beamforming. The experimental confirmation that beamforming can decrease the error in the vital sign extraction through radar has so far not been performed by researchers. A simple, yet effective receiver beamformer was designed and a concurrent measurement with and without beamforming was made for the comparative analysis. Measurements were made at three different distances and five different arrival angles, and the preliminary results suggest that as the observation angle increases, the effectiveness of beamforming increases. At an extreme angle of 40 degrees, the beamforming showed above 20% improvement in heart rate estimation. Heart rate measurement error was reduced significantly in comparison with the breathing rate.

Accurate Heart Rate and Respiration Rate Detection Based on a Higher-Order Harmonics Peak Selection Method Using Radar Non-Contact Sensors

Vital signs such as heart rate and respiration rate are among the most important physiological signals for health monitoring and medical applications. Impulse radio (IR) ultra-wideband (UWB) radar becomes one of the essential sensors in non-contact vital signs detection. The heart pulse wave is easily corrupted by noise and respiration activity since the heartbeat signal has less power compared with the breathing signal and its harmonics. In this paper, a signal processing technique for a UWB radar system was developed to detect the heart rate and respiration rate. There are four main stages of signal processing: (1) clutter removal to reduce the static random noise from the environment; (2) independent component analysis (ICA) to do dimension reduction and remove noise; (3) using low-pass and high-pass filters to eliminate the out of band noise; (4) modified covariance method for spectrum estimation. Furthermore, higher harmonics of heart rate were used to estimate heart rate and minimize respiration interference. The experiments in this article contain different scenarios including bed angle, body position, as well as interference from the visitor near the bed and away from the bed. The results were compared with the ECG sensor and respiration belt. The average mean absolute error (MAE) of heart rate results is 1.32 for the proposed algorithm.

Contactless Simultaneous Breathing and Heart Rate Detections in Physical Activity Using IR-UWB Radars

Vital signs monitoring in physical activity (PA) is of great significance in daily healthcare. Impulse Radio Ultra-WideBand (IR-UWB) radar provides a contactless vital signs detection approach with advantages in range resolution and penetration. Several researches have verified the feasibility of IR-UWB radar monitoring when the target keeps still. However, various body movements are induced by PA, which lead to severe signal distortion and interfere vital signs extraction. To address this challenge, a novel joint chest-abdomen cardiopulmonary signal estimation approach is proposed to detect breath and heartbeat simultaneously using IR-UWB radars. The movements of target chest and abdomen are detected by two IR-UWB radars, respectively. Considering the signal overlapping of vital signs and body motion artifacts, Empirical Wavelet Transform (EWT) is applied on received radar signals to remove clutter and mitigate movement interference. Moreover, improved EWT with frequency segmentation refinement is applied on each radar to decompose vital signals of target chest and abdomen to vital sign-related sub-signals, respectively. After that, based on the thoracoabdominal movement correlation, cross-correlation functions are calculated among chest and abdomen sub-signals to estimate breath and heartbeat. The experiments are conducted under three kinds of PA situations and two general body movements, the results of which indicate the effectiveness and superiority of the proposed approach.

Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar

Radar-based non-contact vital signs monitoring has great value in through-wall detection applications. This paper presents the theoretical and experimental study of through-wall respiration and heartbeat pattern extraction from multiple subjects. To detect the vital signs of multiple subjects, we employ a low-frequency ultra-wideband (UWB) multiple-input multiple-output (MIMO) imaging radar and derive the relationship between radar images and vibrations caused by human cardiopulmonary movements. The derivation indicates that MIMO radar imaging with the stepped-frequency continuous-wave (SFCW) improves the signal-to-noise ratio (SNR) critically by the factor of radar channel number times frequency number compared with continuous-wave (CW) Doppler radars. We also apply the three-dimensional (3-D) higher-order cumulant (HOC) to locate multiple subjects and extract the phase sequence of the radar images as the vital signs signal. To monitor the cardiopulmonary activities, we further exploit the VMD algorithm with a proposed grouping criterion to adaptively separate the respiration and heartbeat patterns. A series of experiments have validated the localization and detection of multiple subjects behind a wall. The VMD algorithm is suitable for separating the weaker heartbeat pattern from the stronger respiration pattern by the grouping criterion. Moreover, the continuous monitoring of heart rate (HR) by the MIMO radar in real scenarios shows a strong consistency with the reference electrocardiogram (ECG).

Embedded heating, ventilation, and air-conditioning control systems: From traditional technologies toward radar advanced sensing

This paper comprehensively reviews the state of the art of Heating, Ventilation, and Air-Conditioning (HVAC) control sensing. The topic has broad impacts on society, by affecting energy consumption, Earth's climate, and the environmental health. Great effort was taken by researchers to study and test new technologies and methodologies for improving HVAC energy efficiency, but this large amount of works is often fragmentary, and a complete and recent review paper does not yet exist. This paper aims at filling this gap by clarifying the key points of HVAC sensing, the main technologies, and their pros and cons. The advancement in this sector is fueled by the premium performance of the embedded systems exploited as sensors and their beneficial features. The state of the art of the available solutions has been summarized with the purpose of fueling and better organizing the research effort on this hot topic. Particular attention has been paid to investigate not only the performance and reliability of the current systems but also the advanced features that can be provided by the newly evolved and complex technologies, e.g., the radar technology that has been identified as the emerging one in this field.

Car2Car Communication Using a Modulated Backscatter and Automotive FMCW Radar

This work proposes the use of a modulated tag for direct communication between two vehicles using as a carrier the wave emitted by an FMCW radar installed in the vehicle for advanced driver assistance. The system allows for real-time signals detection and classification, such as stop signal, turn signals and emergency lights, adding redundancy to computer video sensors and without incorporating additional communication systems. A proof-of-concept tag has been designed at the microwave frequency of 24 GHz, consisting of an amplifier connected between receiving and transmitting antennas. The modulation is performed by switching the power supply of the amplifier. The tag is installed on the rear of the car and it answers when it is illuminated by the radar by modulating the backscattered field. The information is encoded in the modulation switching rate used. Simulated and experimental results are given showing the feasibility of the proposed solution.

Utilization of Micro-Doppler Radar to Classify Gait Patterns of Young and Elderly Adults: An Approach Using a Long Short-Term Memory Network

To develop a daily monitoring system for early detection of fall risk of elderly people during walking, this study presents a highly accurate micro-Doppler radar (MDR)-based gait classification method for the young and elderly adults. Our method utilizes a time-series of velocity corresponding to leg motion during walking extracted from the MDR spectrogram (time-velocity distribution) in an experimental study involving 300 participants. The extracted time-series was inputted to a long short-term memory recurrent neural network to classify the gaits of young and elderly participant groups. We achieved a classification accuracy of 94.9%, which is significantly higher than that of a previously presented velocity-parameter-based classification method.

Recent Development of Non-Contact Multi-Target Vital Sign Detection and Location Tracking Based on Metamaterial Leaky Wave Antennas

Microwave radar sensors have been developed for non-contact monitoring of the health condition and location of targets, which will cause minimal discomfort and eliminate sanitation issues, especially in a pandemic situation. To this end, several radar sensor architectures and algorithms have been proposed to detect multiple targets at different locations. Traditionally, beamforming techniques incorporating phase shifters or mechanical rotors are utilized, which is relatively complex and costly. On the other hand, metamaterial (MTM) leaky wave antennas (LWAs) have a unique property of launching waves of different spectral components in different directions. This feature can be utilized to detect multiple targets at different locations to obtain their healthcare and location information accurately, without complex structure and high cost. To this end, this paper reviews the recent development of MTM LWA-based radar sensor architectures for vital sign detection and location tracking. The experimental results demonstrate the effectiveness of MTM vital sign radar compared with different radar sensor architectures.

Radar Recorded Child Vital Sign Public Dataset and Deep Learning-Based Age Group Classification Framework for Vehicular Application

The ongoing intense development of short-range radar systems and their improved capability of measuring small movements make these systems reliable solutions for the extraction of human vital signs in a contactless fashion. The continuous contactless monitoring of vital signs can be considered in a wide range of applications, such as remote healthcare solutions and context-aware smart sensor development. Currently, the provision of radar-recorded datasets of human vital signs is still an open issue. In this paper, we present a new frequency-modulated continuous wave (FMCW) radar-recorded vital sign dataset for 50 children aged less than 13 years. A clinically approved vital sign monitoring sensor was also deployed as a reference, and data from both sensors were time-synchronized. With the presented dataset, a new child age-group classification system based on GoogLeNet is proposed to develop a child safety sensor for smart vehicles. The radar-recorded vital signs of children are divided into several age groups, and the GoogLeNet framework is trained to predict the age of unknown human test subjects.

High-Resolution and Large-Detection-Range Virtual Antenna Array for Automotive Radar Applications

Collision avoidance and autonomous control of vehicles have become essential needs for providing a high-quality and safe life. This paper introduces a new generic scheme for a virtual antenna array (VAA) and its application in a train collision-avoidance system (TCAS). The proposed TCAS shall have the capability of identifying the range and angle of an object in front of a moving train and provide the required alerts. Thereby, a new virtual array distribution for both the transmitting and the receiving antenna arrays is introduced to get a long-range object detection and high-resolution multi-input multi-output (MIMO) system. This can be accomplished because the VAA radiation pattern is the multiplication of the radiation patterns for both the transmitting and receiving antenna arrays, which is different than each one of them alone. In this work, the VAA is utilized in radar systems in which the radar range depends on the multiplication of the gain of the transmitting and receiving antennas. So, we introduce a new scheme for the general design of VAA-based radars. A prototype for the antenna system was fixed on a of Texas Instruments platform for the cascading radar. One of the main problems of the VAA is the loss of radiated power in undesired directions, which affects the maximum detection range in beamforming systems and degrades the diversity gain in MIMO applications. These issues have been solved by the introduction of the practical implementation of a proposed high-gain, low side lobe level VAA system for automotive radar that is based on the integration of four AWR1243 RF chips operating in a frequency range of 76 GHz to 81 GHz. It was implemented using low-power 45 nm (TI) RFCMOS technology. The measured gain of the realized VAA was 47.2 dBi, which was 1.815 times higher than that of the Texas instrumentation linear frequency modulated continuous wave (TI’ LFMCW) radar, which was 26 dBi. The proposed VAA saved 45% of the required implementation area compared to the TI’ LFMCW antenna array. The VAA system was fabricated and tested in an anechoic chamber, and it was found that the simulated and measured patterns of the proposed VAA were highly matched in terms of half-power beamwidth and side lobe level.

Multi-Monostatic Interferometric Radar for Bridge Monitoring

In recent years, interferometric radar has been extensively used as a sensor for static and dynamic monitoring of bridges. Generally speaking, a radar can only detect displacement components along the view direction. As the movement of a real bridge or of a large structure can be rather complex, this limitation can be a significant drawback in engineering practice. In order to overcome this limitation, in this article, a multi-monostatic radar for retrieving the displacement vector is proposed. It is basically a multiple input, multiple output (MIMO) interferometric radar, equipped with a transponder that consists of a pair of antennae, with relative amplifiers, connected to the radar with a radiofrequency (RF) cable. This arrangement allows for the simultaneous detection of two independent displacement components. The radar was successfully tested both in a controlled environment and in the field on a real bridge crossing the Arno river in Florence, Italy.

Common-Mode Noise Reduction in Noncontact Biopotential Acquisition Circuit Based on Imbalance Cancellation of Electrode-Body Impedance

Biopotential sensing technology with electrodes has a great future in medical treatment and human—machine interface, whereas comfort and longevity are two significant problems during usage. Noncontact electrode is a promising alternative to achieve more comfortable and long term biopotential signal recordings than contact electrode. However, it could pick up a significantly higher level of common-mode (CM) noise, which is hardly solved with passive filtering. The impedance imbalance at the electrode-body interface is a limiting factor of this problem, which reduces the common mode rejection ratio (CMRR) of the amplifier. In this work, we firstly present two novel CM noise reduction circuit designs. The circuit designs are based on electrode-body impedance imbalance cancellation. We perform circuit analysis and circuit simulations to explain the principles of the two circuits, both of which showed effectiveness in CM noise rejection. Secondly, we proposed a practical approach to detect and monitor the electrode-body impedance imbalance change. Compared with the conventional approach, it has certain advantages in interference immunity, and good linearity for capacitance. Lastly, we show experimental evaluation results on one of the designs we proposed. The results indicated the validity and feasibility of the approach.