abstract: Widespread adoption of smartphone based Mobile Medical Apps (MMAs) is opening new avenues for innovation, bringing MMAs to the forefront of low cost healthcare delivery. These apps often control human physiology and work on sensitive data. Thus it is necessary to have evidences of their trustworthiness i.e. maintaining privacy of health data, long term operation of wearable sensors and ensuring no harm to the user before actual marketing. Traditionally, clinical studies are used to validate the trustworthiness of medical systems. However, they can take long time and could potentially harm the user. Such evidences can be generated using simulations and mathematical analysis. These methods involve estimating the MMA interactions with human physiology. However, the nonlinear nature of human physiology makes the estimation challenging. This research analyzes and develops MMA software while considering its interactions with human physiology to assure trustworthiness. A novel app development methodology is used to objectively evaluate trustworthiness of a MMA by generating evidences using automatic techniques. It involves developing the Health-Dev β tool to generate a) evidences of trustworthiness of MMAs and b) requirements assured code generation for vulnerable components of the MMA without hindering the app development process. In this method, all requests from MMAs pass through a trustworthy entity, Trustworthy Data Manager which checks if the app request satisfies the MMA requirements. This method is intended to expedite the design to marketing process of MMAs. The objectives of this research is to develop models, tools and theory for evidence generation and can be divided into the following themes: • Sustainable design configuration estimation of MMAs: Developing an optimization framework which can generate sustainable and safe sensor configuration while considering interactions of the MMA with the environment. • Evidence generation using simulation and formal methods: Developing models and tools to verify safety properties of the MMA design to ensure no harm to the human physiology. • Automatic code generation for MMAs: Investigating methods for automatically • Performance analysis of trustworthy data manager: Evaluating response time generating trustworthy software for vulnerable components of a MMA and evidences.performance of trustworthy data manager under interactions from non-MMA smartphone apps. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2015

Developing non-invasive and accurate diagnostics that are easily manufactured, robust and reusable will provide monitoring of high-risk individuals in any clinical or point-of-care environment, particularly in the developing world. There is currently no rapid, low-cost and generic sensor fabrication technique capable of producing narrow-band, uniform, reversible colorimetric readouts with a high-tuneability range. This thesis aims to present a theoretical and experimental basis for the rapid fabrication, optimisation and testing of holographic sensors for the quantification of pH, organic solvents, metal cations, and glucose in solutions. The sensing mechanism was computationally modelled to optimise its optical characteristics and predict the readouts. A single pulse of a laser (6 ns, 532 nm, 350 mJ) in holographic “Denisyuk” reflection mode allowed rapid production of sensors through silver-halide chemistry, in situ particle size reduction and photopolymerisation. The fabricated sensors consisted of off-axis Bragg diffraction gratings of ordered silver nanoparticles and localised refractive index changes in poly(2-hydroxyethyl methacrylate) and polyacrylamide films. The sensors exhibited reversible Bragg peak shifts, and diffracted the spectrum of narrow-band light over the wavelength range λpeak ≈ 500-1100 nm. The application of the holographic sensors was demonstrated by sensing pH in artificial urine over the physiological range (4.5-9.0), with a sensitivity of 48 nm/pH unit between pH 5.0 and 6.0. For sensing metal cations, a porphyrin derivative was synthesised to act as the crosslinker, the light absorbing material, the component of a diffraction grating, as well as the cation chelating agent. The sensor allowed reversible quantification of Cu2+ and Fe2+ ions (50 mM - 1 M) with a response time within 50 s. Clinical trials of a glucose sensor in the urine samples of diabetic patients demonstrated that the glucose sensor has an improved performance compared to a commercial high-throughput urinalysis device. The experimental sensitivity of the glucose sensor exhibited a limit of detection of 90 µM, and permitted diagnosis of glucosuria up to 350 mM. The sensor response was achieved within 5 min and the sensor could be reused about 400 times without compromising its accuracy. Holographic sensors were also tested in flake form, and integrated with paper-iron oxide composites, dyed filter and chromatography papers, and nitrocellulose-based test strips. Finally, a generic smartphone application was developed and tested to quantify colorimetric tests for both Android and iOS operating systems. The developed sensing platform and the smartphone application have implications for the development of low-cost, reusable and equipment-free point-of-care diagnostic devices.