Development of non-invasive, optical methods for central cardiovascular and blood chemistry monitoring.

Cardiovascular disease and sepsis are leading causes of mortality, morbidity and high cost in hospitals around the world. Failure of the circulatory system during cardiogenic shock and sepsis both can significantly impair the perfusion of oxygen through organs, resulting in poor patient outcome if not detected and corrected early. Another common disorder which goes hand-in-hand with cardiovascular disease is Diabetes Mellitus. Diabetes is a metabolic disorder resulting from the inability of the body to regulate the level of glucose in the blood. The prevalence of diabetes worldwide is increasing faster than society’s ability to manage cost effectively, with an estimated 9% of the world population diagnosed with metabolic disease. The current gold standard measurements for venous oxygen saturation, arterial pulse wave velocity (PWV), and diabetes management through blood glucose concentration monitoring are all invasive. Invasive measurements increase risk of infection and com- plications, are often high cost and disposable, and have a low patient compliance to regular measurements. The aim of this thesis is to develop non-invasive methods of monitoring these important dynamic physiological variables, including, venous oxygen saturation, pulse wave velocity, and blood glucose concentration. A novel photoplethysmography-based NIR discrete wavelength spectrometer was developed using LEDs to both emit light, and detect the light reflected back through the tissue. Using LEDs to detect light simplifies sensing circuit design, lowering hardware costs, allowing adaptable sensing specific to the needs of the user. A reflectance pulse oximeter was developed to measure the oxygen saturation at both the external jugular vein, and carotid artery. Measuring the jugular venous pulse (JVP) allows estimation of the venous oxygen saturation through either the JVP, or through breathing induced variation of the JVP. In addition to oxygenation, the de- vice developed is capable of adapting the sensing layout to measure the arterial pulse waveform at multiple sites along a peripheral artery, such as the carotid or radial. The PWV local to the carotid artery, and radial artery can then be measured, providing key information of cardiovascular risk. A novel algorithm for PWV measurement over multiple pulse waveforms was also developed. Expanding the sensor to use multiple different wavelength LEDs allow discrete spectroscopy in pulsatile blood. An absorption model of components in blood at specific wavelengths was created to isolate the spectral fingerprint of glucose. The sensor successfully measured the oxygen saturation at the carotid artery, and external jugular vein across 15 subjects, giving mean oxygen saturations of 92% and 85% respectively, within the expected physiological ranges. Venous oxygen saturation calculated using breathing induced changes to JVP was 3.3% less than when calculated on the JVP alone, with a standard deviation of 5.3%, compared to 6.9%. Thus, future work on the sensor will focus on extraction of the breathing induced venous pulse, rather than measuring from the JVP itself. The PWV on the carotid and radial artery was successfully measured within the ex- pected physiological ranges, with the novel phase difference algorithm proving more robust to noise than the gold standard foot-foot method. The phase difference method returned a mean PWV at the radial artery of 4.7 ±0.6 m s−1, and a mean CoV of 20%, compared to 4.0 ±1.4 m s−1, and a moan CoV of 58% for the foot-foot method. The proof of concept PWV sensor gives promising results, but needs to be calibrated against invasive gold standards, such as aorta and femoral pressure catheters. A glucose trial involving adult and neonatal subjects provided validation of the NIR non-invasive pulse glucometer. The sensor has an R2 of 0.47, and a mean absolute relative difference (MARD) of 19% compared to gold standard reference measurements. Clarke error grid analysis returns 85% of measurements in Zone A, 11% in Zone B, and 4% in Zone C. While the sensor is not as accurate as the gold standard invasive measurements, the ability to constantly measure without any pain or discomfort will help increase measurement compliance, improving user quality of life, plus further development may improve this. Overall, this thesis provided novel contributions in non-invasive venous oxygen saturation, PWV, and glucose concentration monitoring. The adaptability of the sensor shows promise in helping reduce the pain and inconvenience of the current invasive measurements, especially in diabetes management, where the sensor has the most potential for impact

The 2023 wearable photoplethysmography roadmap

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology

Towards Patient-Specific Brain Networks Using Functional Magnetic Resonance Imaging

fMRI applications are rare in translational medicine and clinical practice. What can be inferred from a single fMRI scan is often unreliable due to the relative low signal-to-noise ratio compared to other neuroimaging modalities. However, the potential of fMRI is promising. It is one of the few neuroimaging modalities to obtain functional brain organisation of an individual during task engagement and rest. This work extends on current fMRI image processing approaches to obtain robust estimates of functional brain organisation in two resting-state fMRI cohorts. The first cohort comprises of young adults who were born at extremely low gestations and age-matched healthy controls. Group analysis between term- and preterm-born adults revealed differences in functional organisation, which were discovered to be predominantly caused by underlying structural and physiological differences. The second cohort comprises of elderly adults with young onset Alzheimer’s disease and age-matched controls. Their corresponding resting-state fMRI scans are short in scanning time resulting in unreliable spatial estimates with conventional dual regression analysis. This problem was addressed by the development of an ensemble averaging of matrix factorisations approach to compute single subject spatial maps characterised by improved spatial reproducibility compared to maps obtained by dual regression. The approach was extended with a haemodynamic forward model to obtain surrogate neural activations to examine the subject’s task behaviour. This approach applied to two task-fMRI cohorts showed that these surrogate neural activations matched with original task timings in most of the examined fMRI scans but also revealed subjects with task behaviour different than intended by the researcher. It is hoped that both the findings in this work and the novel matrix factorisation approach itself will benefit the fMRI community. To this end, the derived tools are made available online to aid development and validation of methods for resting-state and task fMRI experiments

Wearable and Nearable Biosensors and Systems for Healthcare

Biosensors and systems in the form of wearables and “nearables” (i.e., everyday sensorized objects with transmitting capabilities such as smartphones) are rapidly evolving for use in healthcare. Unlike conventional approaches, these technologies can enable seamless or on-demand physiological monitoring, anytime and anywhere. Such monitoring can help transform healthcare from the current reactive, one-size-fits-all, hospital-centered approach into a future proactive, personalized, decentralized structure. Wearable and nearable biosensors and systems have been made possible through integrated innovations in sensor design, electronics, data transmission, power management, and signal processing. Although much progress has been made in this field, many open challenges for the scientific community remain, especially for those applications requiring high accuracy. This book contains the 12 papers that constituted a recent Special Issue of Sensors sharing the same title. The aim of the initiative was to provide a collection of state-of-the-art investigations on wearables and nearables, in order to stimulate technological advances and the use of the technology to benefit healthcare. The topics covered by the book offer both depth and breadth pertaining to wearable and nearable technology. They include new biosensors and data transmission techniques, studies on accelerometers, signal processing, and cardiovascular monitoring, clinical applications, and validation of commercial devices