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Wireless sensing find many biomedical applications due to the benefit and convenience of having no contact with the patients. Low power radio waves, that are biologically safe, can monitor the patient's medical conditions such as the breathing and heart beat rate. Electro-magnetic (EM) waves extract the small movements of the chest and heart via field disturbance phenomena. The patient's breathing and heart beat modulate the radio waves for the vital signs to be monitored in real-time. Ultra-wideband (UWB) radar is an EM scattering technology that has been proven to discriminate targets with less than 30mm range resolution, which is smaller than the average size of a human heart. The UWB radar emits 200ps pulses that occupy a bandwidth from 3 to 10GHz. For linearly polarized radiation, the radar cross-section (RCS) of a moving target having complex shapes such as the thorax section of a human body causes regular fading. The scattering from a complex target rotates the radio wave vector to result in non-optimal signal reception due to polarization losses. The research focuses on the design of a circularly polarized (CP) UWB radar system for contactless vital signs monitoring of a patient. Circular polarization is introduced to address the fading RCS problem thus achieving a more robust system. The same CP UWB radar system with radio waves that penetrate through dielectric objects can be used for time-critical rescue operations in locating survivors buried under collapsed structures or in buildings engulfed in flames where visibility is hampered. Furthermore, by employing material characterization and microwave imaging techniques, it is possible to use the proposed system for other biomedical applications such as tumor localization and damaged tissue identification. The thesis is organized as follows. Firstly, the operation of UWB radar is presented and the research topic addressed. The pulse generator design suited for low pulse repetition rates is then introduced. The design of a decade bandwidth circularly polarized antenna array is described. The methodology and performance of the robust vital signs monitoring system is shown and compared with the linear polarized counterpart. A new method for material characterization using time domain RCS measurements is demonstrated. The future work is finally proposed.
Vital signs, such as heart rate and respiration rate, are useful to health monitoring because they can provide important physiological insights for medical diagnosis and well-being management. Most traditional methods for measuring vital signs require a person to wear biomedical devices, such as a capnometer, a pulse oximeter, or an electrocardiogram sensor. These contact-based technologies are inconvenient, cumbersome, and uncomfortable to use. There is a compelling need for technologies that enable contact-free, easily deployable, and long-term monitoring of vital signs for healthcare. Contactless Vital Signs Monitoring presents a systematic and in-depth review on the principles, methodologies, and opportunities of using different wavelengths of an electromagnetic spectrum to measure vital signs from the human face and body contactlessly. The volume brings together pioneering researchers active in the field to report the latest progress made, in an intensive and structured way. It also presents various healthcare applications using camera and radio frequency-based monitoring, from clinical care to home care, to sport training and automotive, such as patient/neonatal monitoring in intensive care units, general wards, emergency department triage, MR/CT cardiac and respiratory gating, sleep centers, baby/elderly care, fitness cardio training, driver monitoring in automotive settings, and more. This book will be an important educational source for biomedical researchers, AI healthcare researchers, computer vision researchers, wireless-sensing researchers, doctors/clinicians, physicians/psychologists, and medical equipment manufacturers. Includes various contactless vital signs monitoring techniques, such as optical-based, radar-based, WiFi-based, RFID-based, and acoustic-based methods. Presents a thorough introduction to the measurement principles, methodologies, healthcare applications, hardware set-ups, and systems for contactless measurement of vital signs using camera or RF sensors. Presents the opportunities for the fusion of camera and RF sensors for contactless vital signs monitoring and healthcare.
Human vital signs are crucial parameters which reflect essential body functions and are often accessed by medical professionals at the first place during clinical diagnostics to provide immediate assistance in health status measurements. However, due to the recent COVID-19 pandemic, measurements made with direct body contact have become increasingly challenging and costly because of the spreading nature of this virus. Therefore, contactless vital sign measurements are highly desirable, and it motivates us to research and develop a new solution which is capable of performing real time heart rate (HR) detection, respiratory (RR) detection, and body temperature (BT) measurement together from a distant human subject under an ambient light environment. The thesis describes a new system framework, which utilizes the power of computer vision to collect remote video image data, processes them using signal processing and machine learning (ML) technologies simultaneously, and produces rapid updates on display. Furthermore, our validation analysis on the system has showed varied results based on different methodologies used, which enables us to apply the most suitable approach on each component for an optimized final integration. At the time of completing this thesis, we have achieved a complete system integrated with remote HR, RR estimations and BT detection, which are all fully functional in both real-time and offline. To further refine the performance on HR estimation, we selected the extreme gradient boost model through a number of ML models we tested, as it not only gives the lowest root mean square error of 8.2 but also produces stable and robust output.
There has been a push to modernize the technology used in patient monitoring. One area that is being investigated is the use of in situ sensors for real time, continuous vital signs monitoring, particularly to measure pressure. We developed two sensors fulfilling different roles. One is fully implantable and wireless for long term urological pressure monitoring using conventional MEMS technology. This sensor required the use of a battery-powered wireless transmitter. The second sensor utilizes an entirely new method of pressure sensing designed to be easily scaled down in size while being extremely cost effective. By using an electrolyte solution-filled elastic tube, the sensor does not require further packaging; also the materials used are easily obtainable commercially, so no custom components are required even when downsizing. Although initially designed and tested as a wired sensor, the new catheter sensor was designed to be integrated with wireless capability later--to create a truly minimally invasive long term pressure monitor. Both pressure sensing systems were developed by fabricating a pressure sensitive catheter lead, designing the electronics required to amplify and filter the sensor signal, programming the software client that received, stored, graphed, and interpreted the data. Furthermore, both sensors were subjected to extensive in vitro testing to characterize sensor performance and lifetime, as well as simulate an in vivo environment. Both sensors required the investigation of robust packaging techniques to ensure functionality and survivability while implanted. Last, both sensors demonstrated their potential use as a pressure monitor in animal studies: within the bladder for the wireless implantable sensor and as an intravascular sensor for the new conductometric design.
This book serves as the first guideline of the integrative approach, optimal for our new and young generations. Recent technology advancements in computer vision, IoT sensors, and analytics open the door to highly impactful innovations and applications as a result of effective and efficient integration of those. Such integration has brought to scientists and engineers a new approach —the integrative approach. This offers far more rapid development and scalable architecting when comparing to the traditional hardcore developmental approach. Featuring biomedical and healthcare challenges including COVID-19, we present a collection of carefully selective cases with significant added- values as a result of integrations, e.g., sensing with AI, analytics with different data sources, and comprehensive monitoring with many different sensors, while sustaining its readability.
This volume presents the proceedings of the joint conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC), held in Tampere, Finland, in June 2017. The proceedings present all traditional biomedical engineering areas, but also highlight new emerging fields, such as tissue engineering, bioinformatics, biosensing, neurotechnology, additive manufacturing technologies for medicine and biology, and bioimaging, to name a few. Moreover, it emphasizes the role of education, translational research, and commercialization.
Respiratory care is undergoing a period of major change as it cautiously begins to embrace digital transformation. Catalysed by the need for remote consultation in the pandemic, time-honoured approaches to delivering care are now being challenged by technology-based initiatives. This Monograph deftly guides the reader through the potential benefits and pitfalls of such change, breaking the discussion down into three areas: technological opportunities and regulatory challenges ; social benefits, challenges and implications; exemplars of digital healthcare. Each chapter reviews contemporary literature and considers not ‘if’ but ‘how’ a digital respiratory future can provide optimal care. The result is an authoritative, balanced guide to developing digital respiratory health.
Sensor technology for monitoring vital signs is an important topic for various service applications, such as entertainment and personalization platforms and Internet of Things (IoT) systems, as well as traditional medical purposes, such as disease indication judgments and predictions. Vital signs for monitoring include respiration and heart rates, body temperature, blood pressure, oxygen saturation, electrocardiogram, blood glucose concentration, brain waves, etc. Gait and walking length can also be regarded as vital signs because they can indirectly indicate human activity and status. Sensing technologies include contact sensors such as electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmogram (PPG), non-contact sensors such as ballistocardiography (BCG), and invasive/non-invasive sensors for diagnoses of variations in blood characteristics or body fluids. Radar, vision, and infrared sensors can also be useful technologies for detecting vital signs from the movement of humans or organs. Signal processing, extraction, and analysis techniques are important in industrial applications along with hardware implementation techniques. Battery management and wireless power transmission technologies, the design and optimization of low-power circuits, and systems for continuous monitoring and data collection/transmission should also be considered with sensor technologies. In addition, machine-learning-based diagnostic technology can be used for extracting meaningful information from continuous monitoring data.
Contactless vital sensing is gaining prominence with applications in disease control, health monitoring, and medicine; airports are beginning to use infrared thermometers to screen for fevers, automobile companies are researching how cars can wirelessly detect drowsy drivers, and the medical field is exploring the benefits of how cameras can be used to remotely monitor neonates or detect diseases such as atrial fibrillation or sleep apnea. However, prior research to a large extent has not explored when remote vital sensing methods fail and if they may be disadvantageous to certain physiologies more than others such as age, weight, or gender. New methods in the field should strive to determine the impact of these variables as well as rectify inaccuracies in sensing that may occur if possible. This work explores how skin tone can adversely impact heart-rate detection with cameras and temperature evaluation with thermal cameras. Multimodal fusion and algorithmic techniques are proposed to improve skin tone equity while improving performance of contactless vital sensing methods.