Remote Human Vital Sign Monitoring Using Multiple-Input Multiple-Output Radar at Millimeter-Wave Frequencies

Non-contact respiration rate (RR) and heart rate (HR) monitoring using millimeter-wave (mmWave) radars has gained lots of attention for medical, civilian, and military applications. These mmWave radars are small, light, and portable which can be deployed to various places. To increase the accuracy of RR and HR detection, distributed multi-input multi-output (MIMO) radar can be used to acquire non-redundant information of vital sign signals from different perspectives because each MIMO channel has different fields of view with respect to the subject under test (SUT). This dissertation investigates the use of a Frequency Modulated Continuous Wave (FMCW) radar operating at 77-81 GHz for this application. Vital sign signal is first reconstructed with Arctangent Demodulation (AD) method using phase change’s information collected by the radar due to chest wall displacement from respiration and heartbeat activities. Since the heartbeat signals can be corrupted and concealed by the third/fourth harmonics of the respiratory signals as well as random body motion (RBM) from the SUT, we have developed an automatic Heartbeat Template (HBT) extraction method based on Constellation Diagrams of the received signals. The extraction method will automatically spot and extract signals’ portions that carry good amount of heartbeat signals which are not corrupted by the RBM. The extracted HBT is then used as an adapted wavelet for Continuous Wavelet Transform (CWT) to reduce interferences from respiratory harmonics and RBM, as well as magnify the heartbeat signals. As the nature of RBM is unpredictable, the extracted HBT may not completely cancel the interferences from RBM. Therefore, to provide better HR detection’s accuracy, we have also developed a spectral-based HR selection method to gather frequency spectra of heartbeat signals from different MIMO channels. Based on this gathered spectral information, we can determine an accurate HR even if the heartbeat signals are significantly concealed by the RBM. To further improve the detection’s accuracy of RR and HR, two deep learning (DL) frameworks are also investigated. First, a Convolutional Neural Network (CNN) has been proposed to optimally select clean MIMO channels and eliminate MIMO channels with low SNR of heartbeat signals. After that, a Multi-layer Perceptron (MLP) neural network (NN) is utilized to reconstruct the heartbeat signals that will be used to assess and select the final HR with high confidence

Noncontact monitoring of heartbeat and movements during sleep using a pair of millimeter-wave ultra-wideband radar systems

We experimentally evaluate the performance of a noncontact system that measures the heartbeat of a sleeping person. The proposed system comprises a pair of radar systems installed at two different positions. We use millimeter-wave ultra-wideband multiple-input multiple-output array radar systems and evaluate the performance attained in measuring the heart inter-beat interval and body movement. The importance of using two radar systems instead of one is demonstrated in this paper. We conduct three types of experiments; the first and second experiments are radar measurements of three participants lying on a bed with and without body movement, while the third experiment is the radar measurement of a participant actually sleeping overnight. The experiments demonstrate that the performance of the radar-based vital measurement strongly depends on the orientation of the person under test. They also show that the proposed system detects 70% of rolling-over movements made overnight

Novel Methods for Weak Physiological Parameters Monitoring.

M.S. Thesis. University of Hawaiʻi at Mānoa 2017

Non-Contact Vital Sign Detection Using mm-Wave Radar

Vital Sign detection using radars has been a rising technology in the fields of healthcare, security, and military purposes. Typically, radars used for these tasks operate at lower frequencies due to their low cost and and the ability to detect behind obstacles, such as walls or undre debris. However, this leads to an overall large system as the lower the frequency of operation, the larger the size of the antennas. The system size increases when multiple antennas are used for subject localization. But, with the development of millimeter- wave radars and Antenna-on-Package (AoP) solutions, a more compact and portable radar is possible. In this thesis, a commercial, compact, and portable millimeter wave radar operating at 60 GHz is used to detect the vital signs of subjects. With the use of direction of arrival, beamforming, and frequency tracking, the millimeter wave radar is able to accurately detect the heart rate and respiration rate of subjects with high accuracy. Experiments are performed involving detection with varying distances, detection through drywall, and for a single or even multiple subjects

Microstrip antenna design with improved fabrication tolerance for remote vital signs monitoring and WLAN/WPAN applications at mm-wave and THz frequencies

A novel approach is introduced to design microstrip patch antennas (MPAs) with improved fabrication tolerance for highly demanded Millimetre-wave (mm-wave) (30-300GHz) and Terahertz (THz) (0.3-3THz) frequency applications. The presented MP A designing method overcomes the challenges which exist with the fabrication and implementation of the conventional MP A designs at mm-wave and THz frequencies. The following research contributions have been added to the state-ofthe- art work: (i) designing of improved size MPAs at 60GHz, 1 OOGHz, 635GHz and 835GHz to prove the designing concept, (ii) detail measurements and analysis of Remote Vital Signs Monitoring (RVSM) with various sizes of the proposed MPA arrays at 60GHz for high detection accuracy and sensitivity, (iii) designing and tes~ing of MP As for 60GHz wireless local and personal area networks (WLAN/WP AN) in point-to-pint, point-to-multipoint and dual-band applications, (iv) implementation and testing of particular Partially Reflective Surface, Dielectric Lens and Defected Ground Structures on the proposed MP A designs with novel configurations at 60GHz for bandwidth and gain enhancement, and (v~ a comprehensive experimental study on the performance of large array designs with the proposed MP A elements for mm-wave applications. The mentioned research work is explained in the coming chapters in details. Moreover, all mentioned work has already been published

Vital Sign Monitoring in Dynamic Environment via mmWave Radar and Camera Fusion

Contact-free vital sign monitoring, which uses wireless signals for recognizing human vital signs (i.e, breath and heartbeat), is an attractive solution to health and security. However, the subject's body movement and the change in actual environments can result in inaccurate frequency estimation of heartbeat and respiratory. In this paper, we propose a robust mmWave radar and camera fusion system for monitoring vital signs, which can perform consistently well in dynamic scenarios, e.g., when some people move around the subject to be tracked, or a subject waves his/her arms and marches on the spot. Three major processing modules are developed in the system, to enable robust sensing. Firstly, we utilize a camera to assist a mmWave radar to accurately localize the subjects of interest. Secondly, we exploit the calculated subject position to form transmitting and receiving beamformers, which can improve the reflected power from the targets and weaken the impact of dynamic interference. Thirdly, we propose a weighted multi-channel Variational Mode Decomposition (WMC-VMD) algorithm to separate the weak vital sign signals from the dynamic ones due to subject's body movement. Experimental results show that, the 90${^{th}}$ percentile errors in respiration rate (RR) and heartbeat rate (HR) are less than 0.5 RPM (respirations per minute) and 6 BPM (beats per minute), respectively