Wearable neurotechnology utilization is expected to increase dramatically in the coming years, with applications in enabling movement-independent control and communication, rehabilitation, treating disease and improving health, recreation and sport among others. There are multiple driving forces:- continued advances in underlying science and technology; increasing demand for solutions to repair the nervous system; increase in the ageing population worldwide producing a need for solutions to age-related, neurodegenerative disorders, and "assistive" brain-computer interface (BCI) technologies; and commercial demand for nonmedical BCIs. There is a significant opportunity for the UK to lead in the development of AI-enabled neurotechnology R&D. There are a number of key challenges to be addressed, mainly associated with the complexity of signals measured from the brain. AI has the potential to revolutionise the neurotechnology industry and neurotechnology presents an excellent challenge for AI. This fellowship will build on the award-winning AI and neurotechnology research of the fellow and offer real potential for impact through established clinical partnerships and in the neurotechnology industry. The objective of this project is to build on award-winning AI and neurotechnology R&D to address key shortcomings of neurotechnology that limit its widespread use and adoption using a range of key neural network technologies in a state-of-the-art framework for processing neural signals developed by the proposed fellow. The AI technologies developed for neurotechnology will be applied across sectors to demonstrate translational AI through engagement with at least 10 companies across at least 5 sectors during the fellowship, to demonstrate societal and economic benefit and interdisciplinary and translational AI skills development. The project has multiple industry, clinical and academic partners and is expected to produce world-leading AI technologies and propel the fellow to world-leading status in developing AI for neurotechnology which will impact widely. A major focus of the project is ensuring the expectations of the fellow role are met. This includes:- -Ensuring the processes and resources are in place to build a world-leading profile by the end of the fellowship; -Focusing on planning research of the team as new results emerge and hypothesis are tested, to refine and develop a high-quality programme of ambitious, novel and creative research, in AI-enabled Neurotechnology. Specific focus will be ensuring meticulous planning, execution and follow-up to produce world-leading results; -Continuing to perform my leadership role as director of the ISRC and leader of the data analytics theme, expanding the team and actively seek to develop into a position of higher leadership of the research agenda at Ulster, and in the national and international research community; -Focusing on strengthening relationships and collaborations with colleagues in industry and academia, and maximising the potential for flexible career paths for researchers within the team -Acting as an ambassador and advocate for AI, science and ED&I including by continuing to actively provide opinions and engaging with questions around AI and ethics, and responsible research and innovation (RRI). A focus will be embedding this throughout the activities of the fellowship but across the region and internationally; -Seeking to engage with and influence the strategic direction of the UK AI research and innovation landscape through engagement with their peers, policymakers, and other stakeholders including the public through. -Ensuring that the fundamental research is developed to have a high likelihood of impact on UK society/economy through trials across a range of patient groups to develop the evidence base and transfer of intellectual property to products, in particular through NeuroCONCISE Ltd, a main project partner.

Wearable neurotechnology utilization is expected to increase dramatically in the coming years, with applications in enabling movement-independent control and communication, rehabilitation, treating disease and improving health, recreation and sport among others. There are multiple driving forces:- continued advances in underlying science and technology; increasing demand for solutions to repair the nervous system; increase in the ageing population worldwide producing a need for solutions to age-related, neurodegenerative disorders, and "assistive" brain-computer interface (BCI) technologies; and commercial demand for nonmedical BCIs. There is a significant opportunity for the UK to lead in the development of AI-enabled neurotechnology R&D. There are a number of key challenges to be addressed, mainly associated with the complexity of signals measured from the brain. AI has the potential to revolutionise the neurotechnology industry and neurotechnology presents an excellent challenge for AI. This fellowship will build on the award-winning AI and neurotechnology research of the fellow and offer real potential for impact through established clinical partnerships and in the neurotechnology industry. The objective of this project is to build on award-winning AI and neurotechnology R&D to address key shortcomings of neurotechnology that limit its widespread use and adoption using a range of key neural network technologies in a state-of-the-art framework for processing neural signals developed by the proposed fellow. The AI technologies developed for neurotechnology will be applied across sectors to demonstrate translational AI through engagement with at least 10 companies across at least 5 sectors during the fellowship, to demonstrate societal and economic benefit and interdisciplinary and translational AI skills development. The project has multiple industry, clinical and academic partners and is expected to produce world-leading AI technologies and propel the fellow to world-leading status in developing AI for neurotechnology which will impact widely. A major focus of the project is ensuring the expectations of the fellow role are met. This includes:- -Ensuring the processes and resources are in place to build a world-leading profile by the end of the fellowship; -Focusing on planning research of the team as new results emerge and hypothesis are tested, to refine and develop a high-quality programme of ambitious, novel and creative research, in AI-enabled Neurotechnology. Specific focus will be ensuring meticulous planning, execution and follow-up to produce world-leading results; -Continuing to perform my leadership role as director of the ISRC and leader of the data analytics theme, expanding the team and actively seek to develop into a position of higher leadership of the research agenda at Ulster, and in the national and international research community; -Focusing on strengthening relationships and collaborations with colleagues in industry and academia, and maximising the potential for flexible career paths for researchers within the team -Acting as an ambassador and advocate for AI, science and ED&I including by continuing to actively provide opinions and engaging with questions around AI and ethics, and responsible research and innovation (RRI). A focus will be embedding this throughout the activities of the fellowship but across the region and internationally; -Seeking to engage with and influence the strategic direction of the UK AI research and innovation landscape through engagement with their peers, policymakers, and other stakeholders including the public through. -Ensuring that the fundamental research is developed to have a high likelihood of impact on UK society/economy through trials across a range of patient groups to develop the evidence base and transfer of intellectual property to products, in particular through NeuroCONCISE Ltd, a main project partner.

Developing new health technologies is complicated and often fails to lead to improved patient care. Successfully taking an idea through the necessary research studies and developing it to the point of use in the NHS requires many different areas of expertise. These include; understanding patients' and health professionals' needs, medical and healthcare environments, engineering and digital technologies, design, manufacturing, legal and ethical regulation, business development, how to obtain funding, and many other topics (in our application we refer to these areas the "Innovation Curriculum"). Our Hub covers a region of 1.4 million people in a region that is affected by high levels of disease and health inequalities. Our team includes all regional NHS organisations including GPs, adult and children's hospitals, mental health services and the recently introduced South Yorkshire "Integrated Care System", hundreds of researchers from the University of Sheffield and Sheffield Hallam University, many large and small companies, and patient and public groups. These partners between them have all the necessary expertise and experience in developing new Digital Health technologies to the point of use in the NHS. We will help researchers develop Digital Health technologies by training them in all aspects of the Innovation Curriculum, and by supporting them to work together with the NHS and patients on real ideas and projects. We will hold Citizen's Juries to understand the public and patients' views of Digital Health and to help design our research. We will produce sixty hours of training in Digital Health for researchers, clinicians, patients and the public, freely available and accredited through our partnership with YouTube's authoritative health content programme. We will hold regular "Calls for Ideas" where we support project teams and train them in Digital Health, providing the most promising ideas with initial project funding to help take these towards potential commercialisation.

Humans are highly adaptable, and speech is our natural medium for informal communication. When communicating, we continuously adjust to other people, to the situation, and to the environment, using previously acquired knowledge to make this adaptation seem almost instantaneous. Humans generalise, enabling efficient communication in unfamiliar situations and rapid adaptation to new speakers or listeners. Current speech technology works well for certain controlled tasks and domains, but is far from natural, a consequence of its limited ability to acquire knowledge about people or situations, to adapt, and to generalise. This accounts for the uneasy public reaction to speech-driven systems. For example, text-to-speech synthesis can be as intelligible as human speech, but lacks expression and is not perceived as natural. Similarly, the accuracy of speech recognition systems can collapse if the acoustic environment or task domain changes, conditions which a human listener would handle easily. Research approaches to these problems have hitherto been piecemeal and as a result progress has been patchy. In contrast NST will focus on the integrated theoretical development of new joint models for speech recognition and synthesis. These models will allow us to incorporate knowledge about the speakers, the environment, the communication context and awareness of the task, and will learn and adapt from real world data in an online, unsupervised manner. This theoretical unification is already underway within the NST labs and, combined with our record of turning theory into practical state-of-the-art applications, will enable us to bring a naturalness to speech technology that is not currently attainable.The NST programme will yield technology which (1) approaches human adaptability to new communication situations, (2) is capable of personalised communication, and (3) takes account of speaker intention and expressiveness in speech recognition and synthesis. This is an ambitious vision. Its success will be measured in terms of how the theoretical development reshapes the field over the next decade, the takeup of the software systems that we shall develop, and through the impact of our exemplar interactive applications.We shall establish a strong User Group to maximise the impact of the project, with a members concerned with clinical applications, as well as more general speech technology. Members of the User Group include Toshiba, EADS Innovation Works, Cisco, Barnsley Hospital NHS Foundation Trust, and the Euan MacDonald Centre for MND Research. An important interaction with the User Group will be validating our systems on their data and tasks, discussed at an annual user workshop.

The EMERGENCE network aims to create a sustainable eco-system of researchers, businesses, end-users, health and social care commissioners and practitioners, policy makers and regulatory bodies in order to build knowledge and capability needed to enable healthcare robots to support people living with frailty in the community. By adopting a person-centred approach to developing healthcare robotics technology we seek to improve the quality of life and independence of older people at risk of, and living with frailty, whilst helping to contain spiralling care costs. Individuals with frailty have different needs but, commonly, assistance is needed in activities related to mobility, self-care and domestic life, social activities and relationships. Healthcare can be enhanced by supporting people to better self-manage the conditions resulting from frailty, and improving information and data flow between individuals and healthcare practitioners, enabling more timely interventions. Providing cost-effective and high-quality support for an aging population is a high priority issue for the government. The lack of adequate social care provisions in the community and funding cuts have added to the pressures on an already overstretched healthcare system. The gaps in ability to deliver the requisite quality of care, in the face of a shrinking care workforce, have been particularly exposed during the ongoing Covid-19 crisis. Healthcare robots are increasingly recognised as solutions in helping people improve independent living, by having the ability to offer physical assistance as well as supporting complex self-management and healthcare tasks when integrated with patient data. The EMERGENCE network will foster and facilitate innovative research and development of healthcare robotic solutions so that they can be realised as pragmatic and sustainable solutions providing personalised, affordable and inclusive health and social care in the community. We will work with our clinical partners and user groups to translate the current health and social care challenges in assessing, reducing and managing frailty into a set of clear and actionable requirements that will inspire novel research and enable engineers to develop appropriate healthcare robotics solutions. We will also establish best practice guidelines for informing the design and development of healthcare robotics solutions, addressing assessment, reduction and self-management of frailty and end-user interactions for people with age-related sensory, physical and cognitive impairments. This will help the UK develop cross-cutting research capabilities in ethical design, evaluation and production of healthcare robots. To enable the design and evaluation of healthcare robotic solutions we will utilize the consortium's living lab test beds. These include the Assisted Living Studio in the Bristol Robotics Lab covering the South West, the National Robotarium in Edinburgh together with the Health Innovation South East Scotland's Midlothian test bed, the Advanced Wellbeing Research Centre and HomeLab in Sheffield, and the Robot House at the University of Hertfordshire covering the South East. Up to 10 funded feasibility studies will drive co-designed, high quality research that will lead to technologies capable of transforming community health and care. The network will also establish safety and regulatory requirements to ensure that healthcare robotic solutions can be easily deployed and integrated as part of community-based frailty care packages. In addition, we will identify gaps in the skills set of carers and therapists that might prevent them from using robotic solutions effectively and inform the development of training content to address these gaps. This will foster the regulatory, political and commercial environments and the workforce skills needed to make the UK a global leader in the use of robotics to support the government's ageing society grand challenge.