Supervision of human vital signs has always been an essential part in healthcare. Nowadays there is a strong interest in contact-less monitoring methods as they operate less static and offer higher flexibility to the people observed. Recent industrial development enabled radar functionality to be packed in single-chip solutions, decreasing application complexity and speeding up designs. Within this thesis, a vital sign radar prototype has been developed utilising a recently released 60GHz frequency modulated continous wave single-chip radar. The electronics development has been focused on compactness and high system integration. Special attention has been given to the onboard analogue signal filtering and digital data preprocessing. The resulting prototype radar is then tested and evaluated using test scenarios with increasing difficulty. The final experiments prove that the radar is capable of tracking human respiration rate and heartbeat simultaneously from a distance of 1m. It can be concluded that modern radar devices may be significantly miniaturised for e.g. portable operation while offering a wide variety of application possibilities including vital sign monitoring.

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Distinguishing patients with acute coronary syndromes (ACS) within the very large proportion with suspected cardiac pain is a diagnostic challenge, especially in individuals without clear symptoms or electrocardiographic features. This thesis presents the development of a patient data fusion system that would ultimately be able to assist with early identification of patients with non-ST-elevation Acute Coronary Syndrome (NSTEACS) in the pre-hospital setting. In order to identify high-risk ACS patients, patients with ST changes need to be identified. A rule-based ST segment analysis technique was developed and validated on two publicly available databases. Even in subjects who are known to have myocardial ischaemia (MI), ST changes are not considered as a basis for a definitive diagnosis of individual episodes of ischaemia. A technique to differentiate between ST changes caused by MI and those caused by non-ischaemic ST changes such as body position changes or conduction changes was also developed. At the outset of this research there was no available database with continuous vital-sign data for recorded during the ambulance transport. A clinical study was set up to collect vitalsign data and ECG during ambulance transport. Additional parameters from the ECG such as heart rate variability that can be used for detecting ACS, particularly NSTEACS, were investigated. High-risk patients may be identified early by appropriate combination of vital-sign data, demographic information and ECG analysis. This thesis contributes to the literature on early identification of NSTEACS patient during the ambulance transportation. Firstly, it differentiate between ischaemic and non-ischaemic ST episodes using non-linear classifiers. pre-hospital data to ensure . Secondly, it investigates the diagnostic and prognostic value of heart rate variability in identifying high-risk NSTEACS patients in a pre-hospital setting. Thirdly, the thesis attempts to show how data fusion of vitalsign data and additional parameters from the ECG can be used to differentiate between noncardiac and NSTEACS patients in a pre-hospital setting. Lastly, the thesis also provides some insight into the data collection process in a pre-hospital setting.

This thesis uses injection-locked oscillators to realize spectrum and vital sign sensor. At first, the thesis discusses the factors to affect the locking range based on Adler¡¦s equation, and adopts an increase of injection power to enlarge the locking range. Then, the circuit simulation using ADS is carried out to predict the output response of an injection-locked oscillator. As an implementation result, a CMOS chip of an injection-locked oscillator achieves 70 MHz locking range at -17.5 dBm injection power. In addition, a CMOS FM demodulator is realized with the injection-locked oscillator, showing that the chip can demodulate the FSK signal with a minimum frequency deviation of 350 KHz, a minimum input power of -39.5 dBm, and a maximum data rate of 40 Mbps. With the help of the above CMOS chips, a spectrum sensor and a vital sign sensor are realized. In the test, the spectrum sensor can measure a minimum signal power of -100 dBm at a scan speed of 100 MHz/0.5 ms, while the vital sign sensor can detect the breathing and heartbeat rate at a sensing distance of 80 cm.

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.

This paper presents a novel power management analysis method to reduce the power consumption for the non-contact vital sign sensor. The sensor consisting of the class-E power amplifier (PA), low noise amplifier (LNA), single pole double through (SPDT) switch, and circularly polarized antenna (CPA) is integrated on the Flame Retardant Class 4 (FR-4) epoxy-glass laminate substrate. The appropriate pulse width and pulse period are determined to decrease the power consumption and accurately detect the human physiological signals (respiration and heartbeat). A simple direct down-conversion architecture with a tunable phase shifter is utilized to eliminate the null detection point and the direct current (DC) offset. The overall power consumption of the proposed sensor with the novel power management technique is only 40 % of the conventional system with the DC bias, which can be utilized for the green energy application.

The power management technique is employed in the direct down-conversion non-quadrature microwave Doppler radar transceiver for the non-contact vital sign detection based on 0.18 µm CMOS technology. The overshoot and undershoot types of the transient waveform distortion and the simultaneous switching noise (SSN) caused by the high speed pulse signal will severely influence the accuracy for the vital sign detection, so that this investigation clearly analyzes the pulse period, pulse width, rise/fall times and the voltage levels of the pulse bias. In the circuit design, the low power current-reused (CRU) power amplifier (PA) can maintain enough output power by using the crucial double primary transformer (DPTF) and balun. The presented LNA with a differential inductor can provide the noise matching needed and increase the transducer gain in order to achieve the optimal power consumption and the transducer gain in the Rx mode. The excellent isolation between the Tx and Rx mode is obtained with the new parallel directed switch. The overall power consumption of the presented transceiver with the optimal pulse bias is 60% lower than the conventional transceiver with the direct current (DC) bias, and the null detection point and DC offset can be eliminated by the tunable phase shifter.

Differences between indoor non-contact vital sign sensor and general sensors are ¡§indoor¡¨ and ¡§vital sign¡¨. In indoor environment, receiving signals encounter multipath problem caused by the reflection of walls and furniture. Two main vital signs that we are concerned with are heartbeat and respiration; both of them are weaker than general signals used in communication. To overcome problems caused by multipath and weak signal strength, in this thesis, we design a narrow beamwidth antenna operating at 2.45 GHz for indoor non-contact vital sign sensor. We propose a ground surrounded antenna (GSA) which differs from traditional slot and patch antenna. The proposed GSA excites slot mode and patch mode at the same time, so that we can achieve dual-bands or wide band by adjusting its physical parameters. Meanwhile, the reflected wave bounced back from the surrounding ground plane can cause constructive interference so that the antenna possesses better gain and beamwidth. Using GSA as the unit antenna of antenna array to achieve narrow beamwidth design, and adding the concept of superstrate can enhance antenna gain and reduce backlobe radiation. The minimum beamwidth at two orthogonal planes are 26 and 52 degrees respectively, and the antenna gain achieves 12.2 dBi. To reduce the interference between receiving and transmitting signals in single antenna, we use two separate antennas. Finally, we discuss and improve isolation problem between two antennas.

Active integrated antennas (AIAs) are divided into oscillator type AIAs, amplifier type AIAs and frequency-conversion type AIAs. The AIAs designed in this master thesis are oscillator type. Instead of using lumped component like inductors and capacitors, I use a half-wavelength antenna as resonator. In this design, antenna is also treat as a radiated loading. According to reciprocity, antenna receives the reflection signal affected by human body movement and vital sign at the same time. This behavior is regarded as a self-injection locking oscillator. In this master thesis, active antenna is used in monitoring and contacting measurement. In monitoring measurement, active antenna and subject keep their distance. Subject random body movement affects the measured result. Contacting measurement means active antenna pastes on the subject, thus there is no relative displacement between active antenna and subject. Random body movement affect iscancelled in theory. In contacting measurement design some different body motions to test the tolerance of this measurement structure, and use correlation to cancel random body movement. The sensitivity of active antenna structure is enough to detect the vocal vibration in contacting measurement.

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