Development of Wearable Sensors for Medical Diagnostics and Monitoring Health and Wellbeing

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In this project, we will work to develop novel advanced wearable biosensors which can be used either for healthcare applications or assessing lifestyle and wellbeing markers (such as those for hydration or stress). Our ambition is to expand our sensing capabilities, combining microfabricated electrochemical biosensors with microfluidics to develop novel biosensors that can sample the metabolic activity of the body, non-invasively. The project will deliver the following objectives/milestones:1. We will develop an initial microsensor platform either as a watch or a patch/bandage, and explore a range of potential analytes to measure, including those of electrolytes, pH, cortisol, and hormones such as adrenaline as a first objective Milestone 1.2. We will engage in a programme of Patient and Public Involvement and Engagement (PPIE) exploring the co-creation of products and concepts with industry, stakeholders, clinicians, healthcare professional and nurses. We will also engage with end-user groupings including the elderly as well as sportspeople/exercise physiologists, Milestone 2. The PPIE activity will run throughout the project, integrated into all facets of the developments. 3. The sensor array will be integrated with microfluidic platform, testing the efficacy of new methods to draw sample from the skin including e.g. the use of reverse iontophoresis Milestone 3.4. The platform will be interfaced with a smartphone using a low power communications interface to enable data collection and storage, signal processing and artificial intelligence to interpret the results, Milestone 4. Training outcomes: At the end of the project, the student will have developed new understanding of wearable biosensors in particular within the context of user-centered design concepts, enabling new technologies to be deployed rapidly. The student will obtain training in all aspects of biosensors developments, including building molecular interfaces and data analysis, but importantly the student will also be exposed and then will drive PPIE efforts.