AbstractThe development of sensing technologies has enabled digitisation to penetrate sectors that were traditionally non-digital such as healthcare. Internet of things sensor design, designated for health monitoring, has been accelerated from this development.
The following work focuses on the identification of key challenges, enabling factors and potential improvements in sensor design, implementation and operation in an interconnected network. The focus is specifically on challenging applications such as a home healthcare monitoring system.
Identifying the key challenges in these scenarios requires interaction with those environments, the sensor systems and the use case. By designing wearable and environmental sensors, integrated into a digital healthcare platform, those challenges were identified.
Most prominent challenges observed were the minimisation of maintenance and high reliability. The most notable maintenance concern lies in the storage and performance limitations of the sensors' energy source. In this study, notable improvements in the design were identified and implemented in certain cases, reducing the power consumption by 3 orders of magnitude and improving the reliability and predictability.
Novel concepts in environmental and wearable sensing, together with bespoke solutions, were put to test in simulations and real-world deployments. Along with the sensor design, user interactive interfaces were created, providing means for verifying data generated from those sensors. As such, improvements and results could be justified based on data gathered from simulations and real-world deployments.
Findings from deployments are well-considered throughout this thesis. Examining the findings helped in optimising and future-proofing the sensor technologies developed throughout this document. Further development potentials on individual sub-systems were integrated into a complete data-collection pipeline, leading to an end-to-end optimisation.
The system proposed serves digital health monitoring systems while allowing for interoperability, expansion and customisation. The maximisation of the suitability of such a system was achieved by minimising the power consumption and expanding the sensing capabilities of individual sensors.
The engineering work delivered provides new and improved sensor modalities, which other digital healthcare technologies can be compared with. The data generated from the real-world deployments can be used as a baseline dataset. Data gathered through any new proposed systems can be evaluated against such baseline data.
|Date of Award||21 Jan 2021|
|Sponsors||Engineering and Physical Sciences Research Council|
|Supervisor||George Oikonomou (Supervisor), Robert J Piechocki (Supervisor) & Ian J Craddock (Supervisor)|