Towards a practical framework for managing the risks of selecting technology to support independent living

Information and communication technology applications can help increase the independence and quality of life of older people, or people with disabilities who live in their own homes. A risk management framework is proposed to assist in selecting applications that match the needs and wishes of particular individuals. Risk comprises two components: the likelihood of the occurrence of harm and the consequences of that harm. In the home, the social and psychological harms are as important as the physical ones. The importance of the harm (e.g., injury) is conditioned by its consequences (e.g., distress, costly medical treatment). We identify six generic types of harm (including dependency, loneliness, fear and debt) and four generic consequences (including distress and loss of confidence in ability to live independently). The resultant client-centred framework offers a systematic basis for selecting and evaluating technology for independent living

Workflow Variability for Autonomic IoT Systems

Autonomic IoT systems require variable behaviour at runtime to adapt to different system contexts. Building suitable models that span both design-time and runtime is thus essential for such systems. However, existing approaches separate the variability model from the behavioural model, leading to synchronization issues such as the need for dynamic reconfiguration and dependency management. Some approaches define a fixed number of behaviour variants and are therefore unsuitable for highly variable contexts. This paper extends the semantics of the DX-MAN service model so as to combine variability with behaviour. The model allows the design of composite services that define an infinite number of workflow variants which can be chosen at runtime without any reconfiguration mechanism. We describe the autonomic capabilities of our model by using a case study in the domain of smart homes

East Midlands Research into Ageing Network (EMRAN) Discussion Paper Series

Academic geriatric medicine in Leicester . There has never been a better time to consider joining us. We have recently appointed a Professor in Geriatric Medicine, alongside Tom Robinson in stroke and Victoria Haunton, who has just joined as a Senior Lecturer in Geriatric Medicine. We have fantastic opportunities to support students in their academic pursuits through a well-established intercalated BSc programme, and routes on through such as ACF posts, and a successful track-record in delivering higher degrees leading to ACL post. We collaborate strongly with Health Sciences, including academic primary care. See below for more detail on our existing academic set-up. Leicester Academy for the Study of Ageing We are also collaborating on a grander scale, through a joint academic venture focusing on ageing, the ‘Leicester Academy for the Study of Ageing’ (LASA), which involves the local health service providers (acute and community), De Montfort University; University of Leicester; Leicester City Council; Leicestershire County Council and Leicester Age UK. Professors Jayne Brown and Simon Conroy jointly Chair LASA and have recently been joined by two further Chairs, Professors Kay de Vries and Bertha Ochieng. Karen Harrison Dening has also recently been appointed an Honorary Chair. LASA aims to improve outcomes for older people and those that care for them that takes a person-centred, whole system perspective. Our research will take a global perspective, but will seek to maximise benefits for the people of Leicester, Leicestershire and Rutland, including building capacity. We are undertaking applied, translational, interdisciplinary research, focused on older people, which will deliver research outcomes that address domains from: physical/medical; functional ability, cognitive/psychological; social or environmental factors. LASA also seeks to support commissioners and providers alike for advice on how to improve care for older people, whether by research, education or service delivery. Examples of recent research projects include: ‘Local History Café’ project specifically undertaking an evaluation on loneliness and social isolation; ‘Better Visits’ project focused on improving visiting for family members of people with dementia resident in care homes; and a study on health issues for older LGBT people in Leicester. Clinical Geriatric Medicine in Leicester We have developed a service which recognises the complexity of managing frail older people at the interface (acute care, emergency care and links with community services). There are presently 17 consultant geriatricians supported by existing multidisciplinary teams, including the largest complement of Advance Nurse Practitioners in the country. Together we deliver Comprehensive Geriatric Assessment to frail older people with urgent care needs in acute and community settings. The acute and emergency frailty units – Leicester Royal Infirmary This development aims at delivering Comprehensive Geriatric Assessment to frail older people in the acute setting. Patients are screened for frailty in the Emergency Department and then undergo a multidisciplinary assessment including a consultant geriatrician, before being triaged to the most appropriate setting. This might include admission to in-patient care in the acute or community setting, intermediate care (residential or home based), or occasionally other specialist care (e.g. cardiorespiratory). Our new emergency department is the county’s first frail friendly build and includes fantastic facilities aimed at promoting early recovering and reducing the risk of hospital associated harms. There is also a daily liaison service jointly run with the psychogeriatricians (FOPAL); we have been examining geriatric outreach to oncology and surgery as part of an NIHR funded study. We are home to the Acute Frailty Network, and those interested in service developments at the national scale would be welcome to get involved. Orthogeriatrics There are now dedicated hip fracture wards and joint care with anaesthetists, orthopaedic surgeons and geriatricians. There are also consultants in metabolic bone disease that run clinics. Community work Community work will consist of reviewing patients in clinic who have been triaged to return to the community setting following an acute assessment described above. Additionally, primary care colleagues refer to outpatients for sub-acute reviews. You will work closely with local GPs with support from consultants to deliver post-acute, subacute, intermediate and rehabilitation care services. Stroke Medicine 24/7 thrombolysis and TIA services. The latter is considered one of the best in the UK and along with the high standard of vascular surgery locally means one of the best performances regarding carotid intervention

LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft

An IoT-based Thermal Modelling of Dwelling Rooms to Enable Flexible Energy Management

The thermal model of dwellings is the basis for flexible energy management of smart homes, where heating load is a big part of demand. It can also be operated as virtual energy storage to enable flexibility. However, constrained by data measurements and learning methods, the accuracy of existing thermal models is unsatisfying due to time-varying disturbances. This paper, based on the edge computing system, develops a dark-grey box method for dwelling thermal modelling. This darkgrey box method has high accuracy for: i) containing a thermal model integrated with time-varying features, and ii) utilising both physical and machine-learning models to learn the thermal features of dwellings. The proposed modelling method is demonstrated on a real room, enabled by an Internet of Things (IoT) platform. Results illustrate its feasibility and accuracy, and also reveal the data-size dependency of different feature-learning methods, providing valuable insights in selecting appropriate feature-learning methods in practice. This work provides more accurate thermal modelling, thus enabling more efficient energy use and management and helping reduce energy bills

An IoT-based Thermal Modelling of Dwelling Rooms to Enable Flexible Energy Management

The thermal model of dwellings is the basis for flexible energy management of smart homes, where heating load is a big part of demand. It can also be operated as virtual energy storage to enable flexibility. However, constrained by data measurements and learning methods, the accuracy of existing thermal models is unsatisfying due to time-varying disturbances. This paper, based on the edge computing system, develops a dark-grey box method for dwelling thermal modelling. This darkgrey box method has high accuracy for: i) containing a thermal model integrated with time-varying features, and ii) utilising both physical and machine-learning models to learn the thermal features of dwellings. The proposed modelling method is demonstrated on a real room, enabled by an Internet of Things (IoT) platform. Results illustrate its feasibility and accuracy, and also reveal the data-size dependency of different feature-learning methods, providing valuable insights in selecting appropriate feature-learning methods in practice. This work provides more accurate thermal modelling, thus enabling more efficient energy use and management and helping reduce energy bills