NON-CONTACT TECHNIQUES FOR HUMAN VITAL SIGN DETECTION AND GAIT ANALYSIS

Human vital signs including respiratory rate, heart rate, oxygen saturation, blood pressure, and body temperature are important physiological parameters that are used to track and monitor human health condition. Another important biological parameter of human health is human gait. Human vital sign detection and gait investigations have been attracted many scientists and practitioners in various fields such as sport medicine, geriatric medicine, bio-mechanic and bio-medical engineering and has many biological and medical applications such as diagnosis of health issues and abnormalities, elderly care and health monitoring, athlete performance analysis, and treatment of joint problems. Thoroughly tracking and understanding the normal motion of human limb joints can help to accurately monitor human subjects or patients over time to provide early flags of possible complications in order to aid in a proper diagnosis and development of future comprehensive treatment plans. With the spread of COVID-19 around the world, it has been getting more important than ever to employ technology that enables us to detect human vital signs in a non-contact way and helps protect both patients and healthcare providers from potentially life-threatening viruses, and have the potential to also provide a convenient way to monitor people health condition, remotely. A popular technique to extract biological parameters from a distance is to use cameras. Radar systems are another attractive solution for non-contact human vital signs monitoring and gait investigation that track and monitor these biological parameters without invading people privacy. The goal of this research is to develop non-contact methods that is capable of extracting human vital sign parameters and gait features accurately. To do that, in this work, optical systems including cameras and proper filters have been developed to extract human respiratory rate, heart rate, and oxygen saturation. Feasibility of blood pressure extraction using the developed optical technique has been investigated, too. Moreover, a wideband and low-cost radar system has been implemented to detect single or multiple human subject’s respiration and heart rate in dark or from behind the wall. The performance of the implemented radar system has been enhanced and it has been utilized for non-contact human gait analysis. Along with the hardware, advanced signal processing schemes have been enhanced and applied to the data collected using the aforementioned radar system. The data processing algorithms have been extended for multi-subject scenarios with high accuracy for both human vital sign detection and gait analysis. In addition, different configurations of this and high-performance radar system including mono-static and MIMO have been designed and implemented with great success. Many sets of exhaustive experiments have been conducted using different human subjects and various situations and accurate reference sensors have been used to validate the performance of the developed systems and algorithms

Measurement-based feasibility exploration on detecting and localizing multiple humans using MIMO radio channel properties

This paper explores the feasibility of using the multiple-input multiple-output (MIMO) radio channel properties to passively detect and localize multiple humans in indoor environments. We propose to utilize the unique reverberation characteristics of indoor channels for the purpose of detecting, and the power angular delay profile (PADP) for localizing humans. On the one hand, the reverberation time corresponds with the decay rate of multipath in a closed or partially closed cavity, and varies with the change of the number of humans or the moving of humans relative to the antennas at link ends. On the other hand, the PADP is proposed to be calculated by the Multiple Signal Classification (MUSIC) super resolution algorithm with frequency smoothing preprocessing. The proposed approach is evaluated based on real-world MIMO radio channel measurements obtained from a meeting room. Measurements with and without the presence of humans have been conducted, where the maximum number of humans considered is four. Humans facing different directions, either in parallel or orthogonal to the direct line between the transmit and the receive antennas have been taken into account. In term of the detection feasibility, it is found that the change of the number of humans as well as the change of their facing/moving directions inside the partial reverberant region can be reflected on the change of the reverberation time estimated from the power delay profile of channel. In term of the localization feasibility, it is found that single human location can be well associated to the peak of the variation of the PADP during his/her movement, while multiple humans' movements result in obvious power variation in the very vicinity of some of them, and also in the vicinity of some background objects that is far from target humans

MEDUSA: Scalable Biometric Sensing in the Wild through Distributed MIMO Radars

Radar-based techniques for detecting vital signs have shown promise for continuous contactless vital sign sensing and healthcare applications. However, real-world indoor environments face significant challenges for existing vital sign monitoring systems. These include signal blockage in non-line-of-sight (NLOS) situations, movement of human subjects, and alterations in location and orientation. Additionally, these existing systems failed to address the challenge of tracking multiple targets simultaneously. To overcome these challenges, we present MEDUSA, a novel coherent ultra-wideband (UWB) based distributed multiple-input multiple-output (MIMO) radar system, especially it allows users to customize and disperse the $16 \times 16$ into sub-arrays. MEDUSA takes advantage of the diversity benefits of distributed yet wirelessly synchronized MIMO arrays to enable robust vital sign monitoring in real-world and daily living environments where human targets are moving and surrounded by obstacles. We've developed a scalable, self-supervised contrastive learning model which integrates seamlessly with our hardware platform. Each attention weight within the model corresponds to a specific antenna pair of Tx and Rx. The model proficiently recovers accurate vital sign waveforms by decomposing and correlating the mixed received signals, including comprising human motion, mobility, noise, and vital signs. Through extensive evaluations involving 21 participants and over 200 hours of collected data (3.75 TB in total, with 1.89 TB for static subjects and 1.86 TB for moving subjects), MEDUSA's performance has been validated, showing an average gain of 20% compared to existing systems employing COTS radar sensors. This demonstrates MEDUSA's spatial diversity gain for real-world vital sign monitoring, encompassing target and environmental dynamics in familiar and unfamiliar indoor environments.Comment: Preprint. Under Revie

Detection and Localisation Using Light

Visible light communication (VLC) systems have become promising candidates to complement conventional radio frequency (RF) systems due to the increasingly saturated RF spectrum and the potentially high data rates that can be achieved by VLC systems. Furthermore, people detection and counting in an indoor environment has become an emerging and attractive area in the past decade. Many techniques and systems have been developed for counting in public places such as subways, bus stations and supermarkets. The outcome of these techniques can be used for public security, resource allocation and marketing decisions. This thesis presents the first indoor light-based detection and localisation system that builds on concepts from radio detection and ranging (radar) making use of the expected growth in the use and adoption of visible light communication (VLC), which can provide the infrastructure for our light detection and localisation (LiDAL) system. Our system enables active detection, counting and localisation of people, in addition to being fully compatible with existing VLC systems. In order to detect human (targets), LiDAL uses the visible light spectrum. It sends pulses using a VLC transmitter and analyses the reflected signal collected by an optical receiver. Although we examine the use of the visible spectrum here, LiDAL can be used in the infrared spectrum and other parts of the light spectrum. We introduce LiDAL with different transmitter-receiver configurations and optimum detectors considering the fluctuation of the received reflected signal from the target in the presence of Gaussian noise. We design an efficient multiple input multiple output (MIMO) LiDAL system with wide field of view (FOV) single photodetector receiver, and also design a multiple input single output (MISO) LiDAL system with an imaging receiver to eliminate ambiguity in target detection and localisation. We develop models for the human body and its reflections and consider the impact of the colour and texture of the cloth used as well as the impact of target mobility. A number of detection and localisation methods are developed iii for our LiDAL system including cross correlation, a background subtraction method and a background estimation method. These methods are considered to distinguish a mobile target from the ambient reflections due to background obstacles (furniture) in a realistic indoor environment

Localisation and tracking of people using distributed UWB sensors

In vielen Überwachungs- und Rettungsszenarien ist die Lokalisierung und Verfolgung von Personen in Innenräumen auf nichtkooperative Weise erforderlich. Für die Erkennung von Objekten durch Wände in kurzer bis mittlerer Entfernung, ist die Ultrabreitband (UWB) Radartechnologie aufgrund ihrer hohen zeitlichen Auflösung und Durchdringungsfähigkeit Erfolg versprechend. In dieser Arbeit wird ein Prozess vorgestellt, mit dem Personen in Innenräumen mittels UWB-Sensoren lokalisiert werden können. Er umfasst neben der Erfassung von Messdaten, Abstandschätzungen und dem Erkennen von Mehrfachzielen auch deren Ortung und Verfolgung. Aufgrund der schwachen Reflektion von Personen im Vergleich zum Rest der Umgebung, wird zur Personenerkennung zuerst eine Hintergrundsubtraktionsmethode verwendet. Danach wird eine konstante Falschalarmrate Methode zur Detektion und Abstandschätzung von Personen angewendet. Für Mehrfachziellokalisierung mit einem UWB-Sensor wird eine Assoziationsmethode entwickelt, um die Schätzungen des Zielabstandes den richtigen Zielen zuzuordnen. In Szenarien mit mehreren Zielen kann es vorkommen, dass ein näher zum Sensor positioniertes Ziel ein anderes abschattet. Ein Konzept für ein verteiltes UWB-Sensornetzwerk wird vorgestellt, in dem sich das Sichtfeld des Systems durch die Verwendung mehrerer Sensoren mit unterschiedlichen Blickfeldern erweitert lässt. Hierbei wurde ein Prototyp entwickelt, der durch Fusion von Sensordaten die Verfolgung von Mehrfachzielen in Echtzeit ermöglicht. Dabei spielen insbesondere auch Synchronisierungs- und Kooperationsaspekte eine entscheidende Rolle. Sensordaten können durch Zeitversatz und systematische Fehler gestört sein. Falschmessungen und Rauschen in den Messungen beeinflussen die Genauigkeit der Schätzergebnisse. Weitere Erkenntnisse über die Zielzustände können durch die Nutzung zeitlicher Informationen gewonnen werden. Ein Mehrfachzielverfolgungssystem wird auf der Grundlage des Wahrscheinlichkeitshypothesenfilters (Probability Hypothesis Density Filter) entwickelt, und die Unterschiede in der Systemleistung werden bezüglich der von den Sensoren ausgegebene Informationen, d.h. die Fusion von Ortungsinformationen und die Fusion von Abstandsinformationen, untersucht. Die Information, dass ein Ziel detektiert werden sollte, wenn es aufgrund von Abschattungen durch andere Ziele im Szenario nicht erkannt wurde, wird als dynamische Überdeckungswahrscheinlichkeit beschrieben. Die dynamische Überdeckungswahrscheinlichkeit wird in das Verfolgungssystem integriert, wodurch weniger Sensoren verwendet werden können, während gleichzeitig die Performanz des Schätzers in diesem Szenario verbessert wird. Bei der Methodenauswahl und -entwicklung wurde die Anforderung einer Echtzeitanwendung bei unbekannten Szenarien berücksichtigt. Jeder untersuchte Aspekt der Mehrpersonenlokalisierung wurde im Rahmen dieser Arbeit mit Hilfe von Simulationen und Messungen in einer realistischen Umgebung mit UWB Sensoren verifiziert.Indoor localisation and tracking of people in non-cooperative manner is important in many surveillance and rescue applications. Ultra wideband (UWB) radar technology is promising for through-wall detection of objects in short to medium distances due to its high temporal resolution and penetration capability. This thesis tackles the problem of localisation of people in indoor scenarios using UWB sensors. It follows the process from measurement acquisition, multiple target detection and range estimation to multiple target localisation and tracking. Due to the weak reflection of people compared to the rest of the environment, a background subtraction method is initially used for the detection of people. Subsequently, a constant false alarm rate method is applied for detection and range estimation of multiple persons. For multiple target localisation using a single UWB sensor, an association method is developed to assign target range estimates to the correct targets. In the presence of multiple targets it can happen that targets closer to the sensor induce shadowing over the environment hindering the detection of other targets. A concept for a distributed UWB sensor network is presented aiming at extending the field of view of the system by using several sensors with different fields of view. A real-time operational prototype has been developed taking into consideration sensor cooperation and synchronisation aspects, as well as fusion of the information provided by all sensors. Sensor data may be erroneous due to sensor bias and time offset. Incorrect measurements and measurement noise influence the accuracy of the estimation results. Additional insight of the targets states can be gained by exploiting temporal information. A multiple person tracking framework is developed based on the probability hypothesis density filter, and the differences in system performance are highlighted with respect to the information provided by the sensors i.e. location information fusion vs range information fusion. The information that a target should have been detected when it is not due to shadowing induced by other targets is described as dynamic occlusion probability. The dynamic occlusion probability is incorporated into the tracking framework, allowing fewer sensors to be used while improving the tracker performance in the scenario. The method selection and development has taken into consideration real-time application requirements for unknown scenarios at every step. Each investigated aspect of multiple person localization within the scope of this thesis has been verified using simulations and measurements in a realistic environment using M-sequence UWB sensors

Antennas and Propagation Aspects for Emerging Wireless Communication Technologies

The increasing demand for high data rate applications and the delivery of zero-latency multimedia content drives technological evolutions towards the design and implementation of next-generation broadband wireless networks. In this context, various novel technologies have been introduced, such as millimeter wave (mmWave) transmission, massive multiple input multiple output (MIMO) systems, and non-orthogonal multiple access (NOMA) schemes in order to support the vision of fifth generation (5G) wireless cellular networks. The introduction of these technologies, however, is inextricably connected with a holistic redesign of the current transceiver structures, as well as the network architecture reconfiguration. To this end, ultra-dense network deployment along with distributed massive MIMO technologies and intermediate relay nodes have been proposed, among others, in order to ensure an improved quality of services to all mobile users. In the same framework, the design and evaluation of novel antenna configurations able to support wideband applications is of utmost importance for 5G context support. Furthermore, in order to design reliable 5G systems, the channel characterization in these frequencies and in the complex propagation environments cannot be ignored because it plays a significant role. In this Special Issue, fourteen papers are published, covering various aspects of novel antenna designs for broadband applications, propagation models at mmWave bands, the deployment of NOMA techniques, radio network planning for 5G networks, and multi-beam antenna technologies for 5G wireless communications

Sensorless sensing with WiFi

Abstract: Can WiFi signals be used for sensing purpose? The growing PHY layer capabilities of WiFi has made it possible to reuse WiFi signals for both communication and sensing. Sensing via WiFi would enable remote sensing without wearable sensors, simultaneous perception and data transmission without extra communication infrastructure, and contactless sensing in privacy-preserving mode. Due to the popularity of WiFi devices and the ubiquitous deployment of WiFi networks, WiFi-based sensing networks, if fully connected, would potentially rank as one of the world’s largest wireless sensor networks. Yet the concept of wireless and sensorless sensing is not the simple combination of WiFi and radar. It seeks breakthroughs from dedicated radar systems, and aims to balance between low cost and high accuracy, to meet the rising demand for pervasive environment perception in everyday life. Despite increasing research interest, wireless sensing is still in its infancy. Through introductions on basic principles and working prototypes, we review the feasibilities and limitations of wireless, sensorless, and contactless sensing via WiFi. We envision this article as a brief primer on wireless sensing for interested readers to explore this open and largely unexplored field and create next-generation wireless and mobile computing applications. Key words: Channel State Information (CSI); sensorless sensing; WiFi; indoor localization; device-free human detection; activity recognition; wireless networks; ubiquitous computing

Radio channel characterisation and system-level modelling for ultra wideband body-centric wireless communications

PhDThe next generation of wireless communication is evolving towards user-centric networks, where constant and reliable connectivity and services are essential. Bodycentric wireless network (BCWN) is the most exciting and emerging 4G technology for short (1-5 m) and very short (below 1 m) range communication systems. It has got numerous applications including healthcare, entertainment, surveillance, emergency, sports and military. The major difference between the BCWN and conventional wireless systems is the radio channel over which the communication takes place. The human body is a hostile medium from the radio propagation perspective and it is therefore important to understand and characterise the effect of the human body on the antenna elements, the radio propagation channel parameters and hence the system performance. In addition, fading is another concern that affects the reliability and quality of the wireless link, which needs to be taken into account for a low cost and reliable wireless communication system for body-centric networks. The complex nature of the BCWN requires operating wireless devices to provide low power requirements, less complexity, low cost and compactness in size. Apart from these characteristics, scalable data rates and robust performance in most fading conditions and jamming environment, even at low signal to noise ratio (SNR) is needed. Ultra-wideband (UWB) technology is one of the most promising candidate for BCWN as it tends to fulfill most of these requirements. The thesis focuses on the characterisation of ultra wideband body-centric radio propagation channel using single and multiple antenna techniques. Apart from channel characterisation, system level modelling of potential UWB radio transceivers for body-centric wireless network is also proposed. Channel models with respect to large scale and delay analysis are derived from measured parameters. Results and analyses highlight the consequences of static and dynamic environments in addition to the antenna positions on the performance of body-centric wireless communication channels. Extensive measurement i campaigns are performed to analyse the significance of antenna diversity to combat the channel fading in body-centric wireless networks. Various diversity combining techniques are considered in this process. Measurement data are also used to predict the performance of potential UWB systems in the body-centric wireless networks. The study supports the significance of single and multiple antenna channel characterisation and modelling in producing suitable wireless systems for ultra low power body-centric wireless networks.University of Engineering and Technology Lahore Pakista