Noncontact Vital Signs Detection

Human health condition can be accessed by measurement of vital signs, i.e., respiratory rate (RR), heart rate (HR), blood oxygen level, temperature and blood pressure. Due to drawbacks of contact sensors in measurement, non-contact sensors such as imaging photoplethysmogram (IPPG) and Doppler radar system have been proposed for cardiorespiratory rates detection by researchers.The UWB pulse Doppler radars provide high resolution range-time-frequency information. It is bestowed with advantages of low transmitted power, through-wall capabilities, and high resolution in localization. However, the poor signal to noise ratio (SNR) makes it challenging for UWB radar systems to accurately detect the heartbeat of a subject. To solve the problem, phased-methods have been proposed to extract the phase variations in the reflected pulses modulated by human tiny thorax motions. Advance signal processing method, i.e., state space method, can not only be used to enhance SNR of human vital signs detection, but also enable the micro-Doppler trajectories extraction of walking subject from UWB radar data.Stepped Frequency Continuous Wave (SFCW) radar is an alternative technique useful to remotely monitor human subject activities. Compared with UWB pulse radar, it relieves the stress on requirement of high sampling rate analog-to-digital converter (ADC) and possesses higher signal-to-noise-ratio (SNR) in vital signs detection. However, conventional SFCW radar suffers from long data acquisition time to step over many frequencies. To solve this problem, multi-channel SFCW radar has been proposed to step through different frequency bandwidths simultaneously. Compressed sensing (CS) can further reduce the data acquisition time by randomly stepping through 20% of the original frequency steps.In this work, SFCW system is implemented with low cost, off-the-shelf surface mount components to make the radar sensors portable. Experimental results collected from both pulse and SFCW radar systems have been validated with commercial contact sensors and satisfactory results are shown

Advanced signal processing solutions for ATR and spectrum sharing in distributed radar systems

Previously held under moratorium from 11 September 2017 until 16 February 2022This Thesis presents advanced signal processing solutions for Automatic Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems. Two Synthetic Aperture Radar (SAR) ATR algorithms are described for full- and single-polarimetric images, and tested on the GOTCHA and the MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments, that, being discrete defined, provide better representations of targets’ details. The proposed image moments based framework can be extended to the availability of several images from multiple sensors through the implementation of a simple fusion rule. A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopter’s rotor and received by the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating the number, the length and the rotation speed of the blades, parameters that are peculiar for each helicopter’s model. The algorithm is extended to deal with the identification of multiple helicopters flying in formation that cannot be resolved in another domain. Moreover, a fusion rule is presented to integrate the results of the identification performed from several sensors in a distributed radar system. Tests performed both on simulated signals and on real signals acquired from a scale model of a helicopter, confirm the validity of the algorithm. Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp sub-carriers generated through the Fractional Fourier Transform (FrFT), with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a cooperative system. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based waveform is extensively tested and compared with Orthogonal Frequency Division Multiplexing (OFDM) and LFM waveforms, in order to assess both its radar and communication performance.This Thesis presents advanced signal processing solutions for Automatic Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems. Two Synthetic Aperture Radar (SAR) ATR algorithms are described for full- and single-polarimetric images, and tested on the GOTCHA and the MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments, that, being discrete defined, provide better representations of targets’ details. The proposed image moments based framework can be extended to the availability of several images from multiple sensors through the implementation of a simple fusion rule. A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopter’s rotor and received by the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating the number, the length and the rotation speed of the blades, parameters that are peculiar for each helicopter’s model. The algorithm is extended to deal with the identification of multiple helicopters flying in formation that cannot be resolved in another domain. Moreover, a fusion rule is presented to integrate the results of the identification performed from several sensors in a distributed radar system. Tests performed both on simulated signals and on real signals acquired from a scale model of a helicopter, confirm the validity of the algorithm. Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp sub-carriers generated through the Fractional Fourier Transform (FrFT), with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a cooperative system. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based waveform is extensively tested and compared with Orthogonal Frequency Division Multiplexing (OFDM) and LFM waveforms, in order to assess both its radar and communication performance

Optimising access-site risks and complications in coronary angiography and percutaneous coronary intervention

Major access-site bleeding and vascular complications are among the most dreaded complications following coronary angiography and percutaneous coronary intervention. Despite continual improvements in pharmacological and technical measures, bleeding complications still remain a major concern in patients with acute coronary syndrome undergoing invasive coronary intervention. Major bleeding and vascular complications are not only associated with prolonged hospital stay, increased costs, and reduced quality of life; but also with increased morbidity and mortality. Thus, the objective of this research thesis is to investigate measures, particularly the role of ultrasound guidance, in optimising access-site risks and complications in coronary angiography and percutaneous coronary intervention. The results showed that transradial access significantly reduced the composite outcome compared to transfemoral access. Transfemoral access remained superior to transradial access in terms of reduced mean access time, mean access attempts, number of difficult accesses, as well as procedural time and dose-area product. However, there was no difference in the number of first pass successes between the two groups. The rate of venepuncture was markedly higher in the transfemoral approach. Ultrasound guidance did not demonstrate a benefit in clinical outcomes compared with standard access. Ultrasound guidance improved the efficiency and overall success rate of arterial access when compared with the standard palpation technique. It reduced mean access time, mean access attempts, number of difficult accesses, rate of venepuncture, and improved the number of first pass success. Ultrasound guidance significantly improved successful catheterisation of the femoral artery above the bifurcation without an increase in the rate of high punctures. Ultrasounnd guidance in femoral access achieved a high level of ideal puncture and did not increase the risk of retroperitoneal haemorrhage. Obese patients with an abdominal circumference ≥ 100cm had higher rates of vascular complications and ACUITY minor bleeding in comparison to those with an abdominal circumference < 100cm, when undergoing coronary angiogram and/or PCI via a transfemoral approach. Ultrasound guidance was shown to significantly improve femoral artery access outcomes in obese patients with thigh circumference ≥ 60cm when compared with the standard palpation technique. The numbers required to attain competency in ultrasound-guided transfemoral and transradial access were 15 and 25 punctures, respectively. The incidence of subclinical stenoses of the radial artery after being cannulated for catheterization occurred more frequently than anticipated. There were no significant changes in the levels of intercellular adhesion molecule-1, vascular cell adhesion molecule-1, P-selectin and E-selectin when comparing pre- and immediately post-coronary procedures

3D localisation of mosquitoes using digital holography over an extended field of view

Understanding mosquito interaction with long-lasting insecticidal bednets is crucial in the development of more effective intervention methods to protect humans from malaria transmission. Accurate 3D time-series imaging of mosquito-bednet interaction has not previously been possible, but has the potential to offer full kinematic analysis of mosquito flight, accurately determine in situ insecticide dosages, and examine behaviours not yet welldocumented. The work presented in this thesis relates to utilising digital holography for the accurate 3D imaging of mosquito flight using a single-view recording setup. A scalable digital methodology for single object reconstruction and localisation is developed through simulations and physical validation, and a novel focus metric, based on the zero-crossing of the reconstructed complex wavefront, is introduced. This work examines the boundaries presented by a digital hologram recording setup, and utilises the lowest imaging resolution that still yields acceptable localisation errors. Real-world problems typical in mosquito imaging, such as multi-object close proximity and occlusions, and obscured-object localisation, are examined in detail. The methods provided to overcome these obstacles largely involve the development of novel post-process software solutions. Finally, a large field of view digital holographic experiment is developed and preliminary qualitative data of livemosquito reconstruction and localisation is presented. Further work involving techniques to improved the calibration of the large field of view system are suggested to improve the quantitative analysis of the data. The result of this study is a scalable digital holographic methodology to examine mosquito-bednet interaction in 3D at a level of accuracy previously only seen in 2D planar imaging of mosquitoes in a much smaller volume, as well as introducing novel post-processing techniques for accurate localisation

Obesity-induced chronic inflammation in C57Bl6J mice, a novel risk factor in the progression of renal AA amyloidosis?

Background: Compelling evidence links obesity induced systemic inflammation to the development of chronic kidney disease (CKD). This systemic inflammation may result from exacerbated adipose inflammation. Besides the known detrimental effects of typical pro-inflammatory factors secreted by the adipose tissue (TNF-α, MCP-1 and IL-6) on the kidney, we hypothesize the enhanced obesity-induced secretion of serum amyloid A (SAA), an acute inflammatory protein, to play a key role in aggravating obesity-induced CKD. Methods: Groups of male C57Bl/6J mice (n = 99 in total) were fed a low (10% lard) or high (45% lard) fat diet for a maximum of 52 weeks. Mice were sacrificed after 24, 40 and 52 weeks. Whole blood samples, kidneys and adipose tissues were collected. The development of adipose and renal tissue inflammation was assessed on gene expression and protein level. Adipocytokine levels were measured in plasma samples. Results: A distinct inflammatory phenotype was observed in the adipose tissue of HFD mice prior to renal inflammation, which was associated with an early systemic elevation of TNF-α, leptin and SAA (1A-C). With aging, sclerotic lesions appeared in the kidney, the extent of which was severely aggravated by HFD feeding. Lesions exhibited typical amyloid characteristics (2A) and pathological severity positively correlated with bodyweight (2B). Interestingly, more SAA protein was detected in lesions of HFD mice. Conclusion: Our data suggest a causal link between obesity induced chronic inflammation and AA amyloidosis in C57Bl/6J mice. Though future studies are necessary to prove this causal link and to determine its relevance for the human situation, obesity may hence be considered a risk factor for the development and progression of renal AA amyloidosis in the course of CKD. (Figure Presented)