Multiple Person Localization Based on Their Vital Sign Detection Using UWB Sensor

In the past period, great efforts have been made to develop methods for through an obstacle detection of human vital signs such as breathing or heart beating. For that purpose, ultra-wideband (UWB) radars operating in the frequency band DC-5 GHz can be used as a proper tool. The basic principle of respiratory motion detection consists in the identification of radar signal components possessing a significant power in the frequency band 0.2–0.7 Hz (frequency band of human respiratory rate) corresponding to a constant bistatic range between the target and radar. To tackle the task of detecting respiratory motion, a variety of methods have been developed. However, the problem of person localization based on his or her respiratory motion detection has not been studied deeply. In order to fill this gap, an approach for multiple person localization based on the detection of their respiratory motion will be introduced in this chapter

Matrix pencil method for vital sign detection from signals acquired by microwave sensors

Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an efficient method with good frequency resolution, is applied to back-reflected microwave signals to extract vital signs. It is shown that decomposing of the signal to its damping exponentials fulfilled by MPM gives the opportunity to separate signals, e.g., breathing and heartbeat, with high precision. A publicly online dataset (GUARDIAN), obtained by a continuous wave microwave sensor, is applied to evaluate the performance of MPM. Two methods of bandpass filtering (BPF) and variational mode decomposition (VMD) are also implemented. In addition to the GUARDIAN dataset, these methods are also applied to signals acquired by an ultra-wideband (UWB) sensor. It is concluded that when the vital sign is sufficiently strong and pure, all methods, e.g., MPM, VMD, and BPF, are appropriate for vital sign monitoring. However, in noisy cases, MPM has better performance. Therefore, for non-contact microwave vital sign monitoring, which is usually subject to noisy situations, MPM is a powerful method

M-sequence-based ultra-wideband sensor network for vitality monitoring of elders at home

Abstract: The western societies are increasingly faced with the challenges of enabling a self-determined and safe life for a growing number of elderly people. Remote monitoring of vitality is an important tool for health risk mitigation but many of the current methods either deliver only infrequent information or require conscious cooperation of the senior. The authors propose an ultrawideband (UWB) radio sensor network based on M-sequence technology specifically designed for the vitality monitoring of persons living alone. It uses the frequency band in the range from 6 to 8.5 GHz (electronic communications committee (ECC)-band), and provides precise localisation, captures breathing motion during rests, can be used for fall detection and allows the extraction of gait features. The sensor network can be installed in common living spaces. It operates continuously in the background without any user interaction. Vitality monitoring by radar sensors is based on motion detection and tracking. This poses some challenges to radar devices because of the harsh multi-path conditions in apartments. This study discusses these challenges, illustrates how to meet them and gives examples for vitality features which can be extracted from UWB-radar data

Differential ultra-wideband microwave imaging: principle application challenges

Wideband microwave imaging is of interest wherever optical opaque scenarios need to be analyzed, as these waves can penetrate biological tissues, many building materials, or industrial materials. One of the challenges of microwave imaging is the computation of the image from the measurement data because of the need to solve extensive inverse scattering problems due to the sometimes complicated wave propagation. The inversion problem simplifies if only spatially limited objects—point objects, in the simplest case—with temporally variable scattering properties are of interest. Differential imaging uses this time variance by observing the scenario under test over a certain time interval. Such problems exist in medical diagnostics, in the search for surviving earthquake victims, monitoring of the vitality of persons, detection of wood pests, control of industrial processes, and much more. This paper gives an overview of imaging methods for point-like targets and discusses the impact of target variations onto the radar data. Because the target variations are very weak in many applications, a major issue of differential imaging concerns the suppression of random effects by appropriate data processing and concepts of radar hardware. The paper introduces related methods and approaches, and some applications illustrate their performance

Analysis of Ultra Wide Band (UWB) Technology for an Indoor Geolocation and Physiological Monitoring System

The goal of this research is to analyze the utility of UWB for indoor geolocation and to evaluate a prototype system, which will send information detailing a person’s position and physiological status to a command center. In a real world environment, geolocation and physiological status information needs to be sent to a command and control center that may be located several miles away from the operational environment. This research analyzes and characterizes the UWB signal in the various operational environments associated with indoor geolocation. Additionally, typical usage scenarios for the interaction between UWB and other devices are also tested and evaluated

Vital Signs Monitoring Based On UWB Radar

Contactless detection of human vital sign using radar sensors appears to be a promising technology which integrates communication, biomedicine, computer science etc. The radar-based vital sign detection has been actively investigated in the past decade. Due to the advantages such as wide bandwidth, high resolution, small and portable size etc., ultra-wideband (UWB) radar has received a great deal of attention in the health care field. In this thesis, an X4 series UWB radar developed by Xethru Company is adopted to detect human breathing signals through the radar echo reflected by the chest wall movement caused by breath and heartbeat. The emphasis is placed on the estimation of breathing and heart rate based on several signal processing algorithms. Firstly, the research trend of vital sign detection using radar technology is reviewed, based on which the advantages of contactless detection and UWB radar-based technology are highlighted. Then theoretical basis and core algorithms of radar signals detection are presented. Meanwhile, the detection system based on Xethru UWB radar is introduced. Next, several preprocessing methods including SVD-based clutter and noise removal algorithms, the largest variance-based target detection method, and the autocorrelation-based breathing-like signal identification method are investigated, to extract the significant component containing the vital signs from the received raw radar echo signal. Then the thesis investigates four time-frequency analysis algorithms (fast Fourier transform + band-pass filter (FFT+BPF), empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and variational mode decomposition (VMD) and compare their performances in estimating breathing rate (BR) and heart rate (HR) in different application scenarios. A python-based vital signs detection system is designed to implement the above-mentioned preprocessing and BR and HR estimation algorithms, based on which a large number of single target experiments are undertaken to evaluate the four estimation algorithms. Specifically, the single target experiments are divided into simple setup and challenging setup. In the simple setup, testees face to radar and keep normal breathing in an almost stationary posture, while in the challenging setup, the testee is allowed to do more actions, such as site sitting, changing the breathing frequency, deep hold the breathing. It is shown that the FFT+BPF algorithm gives the highest accuracy and the fastest calculation speed under the simple setup, while in a challenging setup, the VMD algorithm has the highest accuracy and the widest applicability. Finally, double targets breathing signal detection at different distances to the radar are undertaken, aiming to observe whether the breathing signals of two targets will interfere with each other. We found that when two objects are not located at the same distance to the radar, the object closer to the radar will not affect the breath detection of the object far from the radar. When the two targets are located at the same distance, the 'Shading effect' appears in the two breathing signals and only VMD algorithm can separate the breathing signals of the targets

Doppler radar-based non-contact health monitoring for obstructive sleep apnea diagnosis: A comprehensive review

Today’s rapid growth of elderly populations and aging problems coupled with the prevalence of obstructive sleep apnea (OSA) and other health related issues have affected many aspects of society. This has led to high demands for a more robust healthcare monitoring, diagnosing and treatments facilities. In particular to Sleep Medicine, sleep has a key role to play in both physical and mental health. The quality and duration of sleep have a direct and significant impact on people’s learning, memory, metabolism, weight, safety, mood, cardio-vascular health, diseases, and immune system function. The gold-standard for OSA diagnosis is the overnight sleep monitoring system using polysomnography (PSG). However, despite the quality and reliability of the PSG system, it is not well suited for long-term continuous usage due to limited mobility as well as causing possible irritation, distress, and discomfort to patients during the monitoring process. These limitations have led to stronger demands for non-contact sleep monitoring systems. The aim of this paper is to provide a comprehensive review of the current state of non-contact Doppler radar sleep monitoring technology and provide an outline of current challenges and make recommendations on future research directions to practically realize and commercialize the technology for everyday usage

MNP-enhanced microwave medical imaging by means of pseudo-noise sensing

Magnetic nanoparticles have been investigated for microwave imaging over the last decade. The use of functionalized magnetic nanoparticles, which are able to accumulate selectively within tumorous tissue, can increase the diagnostic reliability. This paper deals with the detecting and imaging of magnetic nanoparticles by means of ultra-wideband microwave sensing via pseudo-noise technology. The investigations were based on phantom measurements. In the first experiment, we analyzed the detectability of magnetic nanoparticles depending on the magnetic field intensity of the polarizing magnetic field, as well as the viscosity of the target and the surrounding medium in which the particles were embedded, respectively. The results show a nonlinear behavior of the magnetic nanoparticle response depending on the magnetic field intensity for magnetic nanoparticles diluted in distilled water and for magnetic nanoparticles embedded in a solid medium. Furthermore, the maximum amplitude of the magnetic nanoparticles responses varies for the different surrounding materials of the magnetic nanoparticles. In the second experiment, we investigated the influence of the target position on the three-dimensional imaging of the magnetic nanoparticles in a realistic measurement setup for breast cancer imaging. The results show that the magnetic nanoparticles can be detected successfully. However, the intensity of the particles in the image depends on its position due to the path-dependent attenuation, the inhomogeneous microwave illumination of the breast, and the inhomogeneity of the magnetic field. Regarding the last point, we present an approach to compensate for the inhomogeneity of the magnetic field by computing a position-dependent correction factor based on the measured magnetic field intensity and the magnetic susceptibility of the magnetic particles. Moreover, the results indicate an influence of the polarizing magnetic field on the measured ultra-wideband signals even without magnetic nanoparticles. Such a disturbing influence of the polarizing magnetic field on the measurements should be reduced for a robust magnetic nanoparticles detection. Therefore, we analyzed the two-state (ON/OFF) and the sinusoidal modulation of the external magnetic field concerning the detectability of the magnetic nanoparticles with respect to these spurious effects, as well as their practical application