The importance of analysing health data collected as part of clinical care and stored in electronic health records is well-established. This has led to vital research about the occurrence and progression of disease, treatment effectiveness and safety, and health service delivery. The current Covid-19 pandemic has demonstrated the public health need to efficiently use data collected at the point of care to rapidly understand patterns, risk factors and outcomes of emerging diseases. Much of this work comes from primary care electronic health records, where general practitioners (GPs) enter and use structured, coded healthcare data. The picture in hospitals, however, is very different. One in four people in the UK live with one or more long-term conditions like cardiovascular diseases, chronic respiratory diseases, type 2 diabetes, arthritis and cancer, which account for 70% of the NHS budget. Specialised opinion about management of long-term conditions (LTCs) is provided through hospital outpatient care. Data and insight from outpatient clinics, however, is almost entirely absent. There is, surprisingly, no national system for recording diagnoses in hospital outpatient clinics. Information about key clinical events is instead recorded in outpatient letters, which are primarily used to communicate with patients and GPs. The ways in which letters are written and their sensitive content mean that they are not available for larger-scale "secondary use", i.e. to support clinical practice, research or service improvement. For example, shielding for the current pandemic relied on hospital clinical teams going through patient letters manually to identify those who needed shielding based on free-text information about diagnoses and medications, with clear time constraints and risks to under- and over-shield patients. Natural language processing (NLP) and text mining develop computer algorithms to automatically extract relevant information from free-text documents. This project will establish a partnership between academia, secondary care and industry to develop a standards-based information management framework to safely unlock information stored in outpatient letters, link it with other health data and demonstrate its impact and benefits through two case studies. We will develop new methods to extract key clinical events from letters and represent their details (e.g. medication used, duration of symptoms) in a computerised form so that it can be easily accessed. In doing so, we will use the NHS-adopted standards so that the outpatient letters can be linked to other hospital databases and do not live in their own silo. The protection of sensitive data that potentially appear in outpatient data is a prime concern, so we will develop clear rules on who and how can access such data, in particular considering that third parties (e.g. industry) may need to access that data for developing their tools. These rules will be developed in a close collaboration between patient representatives, clinicians and specialists to ensure safeguards, public trust and transparency of decision making. We will demonstrate the potential impact of the proposed methods through two case studies with our clinical and business partners. Our first case study will demonstrate how the proposed models can assist in timely, efficient, dynamic and transparent identification of patients for shielding in a pandemic, or for vaccination prioritisation. In the second case study, we will illustrate how the same information can be used address important gaps in our knowledge about health and care, including, for example, disease prevalence and drug utilisation patterns. All outputs will be developed in a way that can be scaled beyond the single clinical site and single speciality.

Worldwide, there are over three million people living with upper-limb loss. Recent wars, industrialisation in developing countries and vascular disease, e.g. diabetes, have caused the number of amputations to soar. Adding to this population each year, one in every 2,500 people are born with upper-limb reduction. Advanced prostheses can play a major role in enhancing the quality of life for people with upper-limb loss, however, they are not available under the NHS. Notably, many people with traumatic limb loss are otherwise physically fit. If they are equipped with advanced prostheses and treated to recover psychologically, they can live independently, with minimal need for social support, return to work and contribute to the economy. There are a plethora of underlying reasons that limit wide clinical adoption of advanced prosthetic hands. For instance, surveys on their use reveal that 20% of upper-limb amputees abandon their prosthesis, with the primary reason being that the control of these systems is still limited to one or two movements. In addition, the process of switching a prosthetic hand into an appropriate grip mode, e.g. to use scissors, is cumbersome or requires an ad-hoc solution, such as using a smart phone application. Other reasons include: users finding their prosthesis uncomfortable or unsuitable for their needs. As such, everyday tasks, such as tying shoe-laces, are currently very challenging for prosthetic hand users. These functional shortcomings, coupled with high costs and lack of concrete evidence for added benefit, have emerged as substantial barriers limiting clinical adoption of advanced prosthetic hands. The long-term aim of this cross-disciplinary programme is to develop, and move towards making available, the next generation of prosthetic hands that can improve the users' quality of life. Our underlying scientific novelty is in utilising users' capability of learning to operate a prosthesis. For instance, we examine the extent to which the activity of muscles can deviate from natural patterns employed in controlling movement of the biological arm and hand and whether prosthesis users can learn to synthesise these functional maps between muscles and prosthetic digits. Basing this approach upon our pilot data, we hypothesise that practice and availability of sensory feedback can accelerate this learning experience. To address this fundamental question, we will employ in-vivo experiments, exploratory studies involving able-bodied volunteers and pre-clinical work with people with limb loss. The insight gained from these studies will inform the design of novel algorithms to enable seamless control of prosthetic hands. Finally, the programme will culminate with a unifying theory for learning to control prosthetic hands that will be tested in an NHS-approved, pre-clinical trial. Maturing this approach into a clinically-viable solution needs a dedicated team of engineers and scientists as well as a consortium of users, NHS-based clinicians and healthcare and high-tech industries. With the flexibility that a Healthcare Technologies Challenge Award affords me, I will be able to nurture and grow sustainably my multi-disciplinary team. In addition, this flexible funding will enable to focus on a converging research programme with the ultimate aim of providing prosthetic solutions that enhance NHS-approved clinical patient outcome measures significantly. Within this programme, I will identify and bring together the engineering, scientific, clinical, ethical and regulatory elements necessary to form a recognised national hub for the development of next-generation prosthetics. This work will provide the foundations for my 15-year plan to establish the Centre for Bionic Limbs. The origin of this Centre will be to act as a mechanism to safeguard engineering and scientific innovations, increase value, and accelerate transfer into commercial and clinical fields.

Worldwide, there are over three million people living with upper-limb loss. Recent wars, industrialisation in developing countries and vascular disease, e.g. diabetes, have caused the number of amputations to soar. Adding to this population each year, one in every 2,500 people are born with upper-limb reduction. Advanced prostheses can play a major role in enhancing the quality of life for people with upper-limb loss, however, they are not available under the NHS. Notably, many people with traumatic limb loss are otherwise physically fit. If they are equipped with advanced prostheses and treated to recover psychologically, they can live independently, with minimal need for social support, return to work and contribute to the economy. There are a plethora of underlying reasons that limit wide clinical adoption of advanced prosthetic hands. For instance, surveys on their use reveal that 20% of upper-limb amputees abandon their prosthesis, with the primary reason being that the control of these systems is still limited to one or two movements. In addition, the process of switching a prosthetic hand into an appropriate grip mode, e.g. to use scissors, is cumbersome or requires an ad-hoc solution, such as using a smart phone application. Other reasons include: users finding their prosthesis uncomfortable or unsuitable for their needs. As such, everyday tasks, such as tying shoe-laces, are currently very challenging for prosthetic hand users. These functional shortcomings, coupled with high costs and lack of concrete evidence for added benefit, have emerged as substantial barriers limiting clinical adoption of advanced prosthetic hands. The long-term aim of this cross-disciplinary programme is to develop, and move towards making available, the next generation of prosthetic hands that can improve the users' quality of life. Our underlying scientific novelty is in utilising users' capability of learning to operate a prosthesis. For instance, we examine the extent to which the activity of muscles can deviate from natural patterns employed in controlling movement of the biological arm and hand and whether prosthesis users can learn to synthesise these functional maps between muscles and prosthetic digits. Basing this approach upon our pilot data, we hypothesise that practice and availability of sensory feedback can accelerate this learning experience. To address this fundamental question, we will employ in-vivo experiments, exploratory studies involving able-bodied volunteers and pre-clinical work with people with limb loss. The insight gained from these studies will inform the design of novel algorithms to enable seamless control of prosthetic hands. Finally, the programme will culminate with a unifying theory for learning to control prosthetic hands that will be tested in an NHS-approved, pre-clinical trial. Maturing this approach into a clinically-viable solution needs a dedicated team of engineers and scientists as well as a consortium of users, NHS-based clinicians and healthcare and high-tech industries. With the flexibility that a Healthcare Technologies Challenge Award affords me, I will be able to nurture and grow sustainably my multi-disciplinary team. In addition, this flexible funding will enable to focus on a converging research programme with the ultimate aim of providing prosthetic solutions that enhance NHS-approved clinical patient outcome measures significantly. Within this programme, I will identify and bring together the engineering, scientific, clinical, ethical and regulatory elements necessary to form a recognised national hub for the development of next-generation prosthetics. This work will provide the foundations for my 15-year plan to establish the Centre for Bionic Limbs. The origin of this Centre will be to act as a mechanism to safeguard engineering and scientific innovations, increase value, and accelerate transfer into commercial and clinical fields.

This multidisciplinary project will exploit an established UK based team's track record comprising RF & bio-sensing engineers, battery & materials scientists, and CPI, the UK National Catapult for Printed Electronics. Centred around Additive Manufacture and aimed towards scale-up, we will transform nascent wireless skin-based sensing to the high data rate capacity offered by upcoming communications systems using license-free 24 GHz channels. This will enable new streaming of biodata for remote diagnostics, monitoring and care, as well as ultra-low impact wireless EEG for forehead/ear/hair free regions. It will make possible the use of multiple sensing tags on multiple people simultaneously monitoring physiological parameters such as accelerometery (for activity tracking), photoplesmography (for heart rate monitoring), and sweat (for metabolite monitoring). At high data rate, this represents a step change over available technologies. Manufactured on highly flexible, potentially stretchable, substrates the skin tags take the form factor of temporary tattoos and are highly long lasting, discrete for social acceptability, and can follow the micro-contours of the skin to give a large contact surface area and consequently sensing signal-to-noise ratio. To achieve our aims, we will advance wireless mmWave devices, on-skin electronics, low-power bio-sensing, and additive manufacture. Additionally, through CPI, we will develop scale-up processes for these mmWave devices. Through existing investments the applicant team is positioning the UK for the large scale manufacture of on-skin sensor tags. EP/P027075/1 is creating an inkjet printing based manufacturing process for sensors on flexible substrates which avoids cleanrooms, uses graphene based ink formulations for biodegradability, and can be scaled up large run roll-to-roll screen printing. EP/R02331X/1 added the capability to print TiO2/LiFePO4 batteries integrated into the platform, removing a key integration bottleneck. This new proposal 'MultiSense' seeks to build upon the manufacturing base created by these two projects, extending it to overcome the key sensing limitation of current on skin tags: that they can only monitor one parameter from one person at a time, and at a comparatively low data rate. These projects are further limited to producing first principle non-elastic, low capacity integrated batteries and UHF frequency (868 MHz) RF devices which require print resolutions similar to conventional masks for wet etching (typically 200 um). Further, our experience of UHF RFID reveals transmission delays of 6 ms, and a reliable data rate upper limit of only 400 bps (corresponding to a sample rate of just 30 Hz for a modality such as accelerometry). In MultiSense, we propose to overcome these limitations by moving from RFID to 24 GHz ISM (Industrial, Scientific Medical) band transmission, where very substantial uncongested bandwidth is available, offering orders of magnitude higher bit rates than UHF. In addition, the smaller wavelengths will increase antenna miniaturisation on integrated elastic substrate batteries, requiring print resolutions of 50 um. The new batteries will be solid state and polymer based with elastic current collectors. We will also investigate the mmWave signal surface guiding over the skin as a mechanism to allow for inter-patch communications. Sensing robustness will be improved as minor variations/misplacements in the sensor positions could be captured, and potentially corrected for in software. This will impact on diagnostic EEG measurements where currently entire datasets (from cabled electrodes) might be abandoned when individual electrodes disconnect. To enable the measurement of skin-based transmission between patches with new dry electrode designs, we will work with International Research Visitor Professor Koichi Ito of Chiba university, an expert in human phantom design.

Dementia is often presented as a global issue with substantial economic consequences for all countries and societies providing diagnostic and/or supportive services. Whilst we believe this is necessary and important information, in our 5-year study we want to celebrate the achievements, growth and contribution that people with dementia and their carers make to society. To do this, we are putting the local neighbourhood and networks in which people with dementia and their carers live and belong at the centre of our work. We have designed a study on neighbourhood living that has 4 inter-linked work packages (WPs), an international partner , the Center for Dementia Research [CEDER] at Linköping University, Sweden, and strong user involvement through the EDUCATE and Open Doors groups [Greater Manchester, England]; The ACE Club [Rhyl, North Wales]; and the Scottish Dementia Working Group [Glasgow, Scotland]. In the UK our academic partners are situated in Manchester, Salford, Stirling, Liverpool and London and we have third sector involvement through the Deaf Heritage Project at the British Deaf Association, as well as a range of project partners which includes the North West People in Research Forum, the Citizen Scientist initiative and a Community Integrated Company that supports people with dementia through accessible technology [Finerday]. As this is a complex set of networks based around a neighbourhoods theme, each WP will use different research methods and partners to meet their primary aims and objectives. WP1 is a secondary analysis of the English Longitudinal Study of Aging database which will compile Neighbourhood Profiles that will be available for the whole country; these Profiles will include information on cognitive risk factors and clusters of population; WP2 will develop a set of core outcomes measures in dementia that will involve people with dementia and their carers in deciding what measures and priorities are important for them; WP3 will explore what makes a dementia friendly neighbourhood and will take place in Stirling, Salford and Linköping; WP4 has 3 interventions representing various stages of the Medical Research Council's complex interventions framework. Intervention 1 will be a full RCT of an educational intervention for general hospitals that several members of the project team have developed and piloted over the last 2 years. In this study, we want to find out if the educational intervention results in people with dementia leaving hospital for their neighbourhood home sooner, but with high levels of satisfaction. Interventions 2 and 3 are pilot trials. Intervention 2 will be conducted in Sweden and Manchester, UK and will use technology to help couples, where one person has a dementia, to better self-manage the condition and, more importantly, their relationship. In intervention 3, we are looking at the diversity of a neighbourhood and will develop the first digitalised life story intervention in the world for Deaf people (BSL users) who live with dementia. This will be the first intervention for this group in the world. In this programme of work we will develop a user research programme as some people with dementia have told us that they would like to work alongside the research team as co-researchers. We will therefore appoint a PPI co-ordinator for the duration of the study with a responsibility for identifying co-researcher training needs, running a regular co-research programme, mentoring co-researchers, ensuring user goal preferences are met and facilitating user dissemination. Through the implementation of a neighbourhood approach each WP will promote closer relations and working between professionals, lay people and people living with dementia. This study will also contribute to the currently limited evidence base for dementia friendly communities and provide knowledge and insights to support a robust theoretical framework of neighbourhood work that will have international scope and relevance.