Our research has an impact on society.
Our research is important to us and we are very pleased that it has made an impact on our society locally and worldwide, take a look at the information below to see how our research is helping people around the globe.
Findings from recent research studies show that 91% of adults aged between 57 and 85 consume at least one item of medication daily, and that around 76% of prescribed medications are taken incorrectly with 29% not taken at all. When not adhered to correctly, medicated treatment can be ineffective, wasting both money and the valuable time of doctors and healthcare professionals. Forgetfulness is the most commonly reported reason for people not taking their medication properly.
The Computer Science Research Institute (CSRI) at Ulster has tackled this problem by developing an internet-based care model that helps patients, pharmacists, carers and GPs to dynamically manage the prescription of medication for patients and that also helps patients to comply with taking their medication in the prescribed way and at the right times. This care model has been incorporated into a service platform produced by an international telecare company that provides products and services for the healthcare market. This research has extended the functionality of the company's product, which is now being used by over 400 patients in Europe. By using the product, patients are managing improved levels of medication compliance, caregivers are finding that their burden is reduced, and healthcare professionals are experiencing improvements in the management of their workflow. The product also now incorporates reminders for patients and carers that are delivered as short video clips, and this extension to the product has enabled CSRI to set up formal collaboration agreements with the company to further extend the usefulness of the product for patients and carers in the future.
CSRI has been working on developing technologies for managing medication for over 15 years, and particularly to support people with dementia. The work originated though a project called MEDICATE, which started in the year 2000 with funding from the European Union's Framework Programme 5. The research developed an internet-based care model to support all stakeholders in the supply to intake chain of personal medication management. The approach was very effective, with two-thirds of users showing improved compliance with taking their prescribed medication, and a reduction in the average contact time that was needed every week by caregivers.
The MEDICATE solution was extended to a mobile-based reminding application, which inspired the concept of video-based reminders for persons with dementia. A video-based reminding system that uses everyday mobile phone technologies was developed. The system was tested extensively with cohorts of elderly users, persons with dementia and control groups, along with their carers; in total, over 400 days worth of evaluations were conducted between 2006 and 2012.
Following these evaluations, analysis provided insights into the most appropriate ways to use video-based messages for medication reminders and how user interaction with the technology should be designed for people with dementia. The analysis also identified an additional key challenge: assessing the factors that influence whether patients and carers will adopt the new technologies, and then using that knowledge to improve the rate of technology adoption.
Since incorporating the new functionality into its product in 2008, the company has reported securing new contracts for the product, with substantial new revenue; creating additional new posts for research and development engineers to further develop the product; and use of the system by over 400 users. A joint commercial venture between CSRI and the company was established in November 2012, with the aim to provide support for the product within the UK, from both marketing and installation perspectives, and to promote the further uptake of the product within Europe. From a healthcare perspective, General Practitioners have reported the positive benefits of being able to monitor patients remotely using the system without the need for home-based visits. In addition, patients have provided positive feedback about how the system gives them a solution that offers constant monitoring and communication with a doctor.
In modern healthcare services, a growing emphasis is being placed on people to be more aware of their own health and wellbeing and to play a more active part in the self-management of their health. This is particularly important amongst the increasing number of older but active members of the population. At the centre of this paradigm is a new range of biophysical monitoring devices (for example, heart rate monitors and step-counters). For such devices to be most effective, there are significant challenges about where and how to best locate them on the body. If the monitoring devices are not placed optimally there can be significant loss in accuracy of the measurements that are processed from the data acquired, so the devices will be less effective for people who are self-monitoring their health and wellbeing.
Researchers in the Computer Science Research Institute (CSRI) have been tackling this problem and have developed solutions that are now being incorporated into products that can enhance people's everyday lives. Based on research carried out by CSRI on wearable technologies for people who are ageing but active, two leading manufacturers of clothing for outdoor activities have produced a new range of functional clothing. The new outdoor garments are designed to be age-appropriate, and they incorporate wearable technologies that enable people to self-monitor their physiological parameters, such as heart-rate and respiration-rate, and their activity levels, such as step-counts and the distances that they have walked. These smart garments incorporate sensors that are positioned optimally to gather physiological signals from the body and to measure physical movements. Additionally, a company that produces components that are embedded in the smart garments has used feedback from Ulster's research evaluations to design a new range of components that can make the clothing easier to use by elderly people.
Research on processing and classifying physiological signals has been a core area of research at Ulster for over 15 years. Results of our research in electrocardiology have been extended through the classification of entire body surface potential maps. This research stimulated the hypothesis that a reduced set of electrodes from the body surface map could be used to improve the interpretation of cardiac signals. Our research also considered the restrictive nature of connecting electrodes/cables to human subjects and the impracticalities of this for long-term monitoring. Subsequently, textile-based electrodes showed promise for the measurement of the ECG signals, as they don't require any gel membrane or adhesive, and clothing enables textile sensors to be placed in close physical proximity to a large area of the body.
The results from this work formed the basis of the technologies that CSRI developed in the Design for Ageing Well project, which was funded by the UK Economic and Social Research Council's New Dynamics of Ageing research programme. User evaluations with walking groups provided insights into the ways in which the feedback on wearable devices should be provided to users and how the garments should be designed to incorporate the technological components to make them as easy as possible to use. The co-design process was one of the central results from the Design for Ageing Well project and was used as a methodology to produce a range of age-appropriate clothing with integrated technologies. These garments were demonstrated in a joint trade exhibition and the garment manufacturers have incorporated the research results into their current range of clothing relating to age-appropriate shape and fit, styling and fabric selection. The recommendations from the Design for Ageing Well project have also guided the companies in the design of the garment layering system as a basis for incorporating wearable electronics. These recommendations are a result of CSRI's research findings for the most appropriate positioning of sensor and control technologies within the garments in order to both make them easy to use from an active ageing perspective and to improve the accuracy of the physiological measurements processed from the data acquired by the sensors. A niche outdoor clothing manufacturer has now adapted their manufacturing procedures to support the incorporation of technology within their smart garments.
The smart garments have been tested with users from walking groups, and we have had a series of testimonials that report the positive experiences of active older persons who have used the new clothing for outdoor activities. A 70-year-old participant in the evaluations, who reported that she enjoyed walking as part of an active life, said that her involvement in the Design for Ageing Well project has resulted in her being more inclined to go out and exercise and that she was now more aware of the options available for technology-enabled age-appropriate clothing. A 67-year-old male member of a walking group said that in his opinion the use of the age-appropriate clothing would make people more likely to become involved in recreational activities. The research expertise developed by CSRI in wearable technologies is also influencing new standards within the textile industry. The Textile Institute, a worldwide organisation for textiles, clothing and footwear, recognises the importance of smart textiles and has invited Prof Chris Nugent from CSRI to join a committee of 12 international experts from the smart textiles community.
Stroke disease places a heavy burden on society, incurring long periods of hospital and community care, with all of the associated costs. Strokes are also highly complex with diverse outcomes and multiple strategies for therapy and care. Professor Sally McClean and co-researchers in the Computer Science Research Institute (CSRI) at Ulster have tackled this problem by developing a mathematical modelling framework that can be used by hospitals to predict how long patients requiring stroke care are likely to stay in hospital. Using this information, hospitals can better plan their capacity for treating patients and the next stage in their treatment, such as discharge to home or nursing home.
Research on modelling stroke patient pathways through hospital, social and community services carried out in CSRI has helped the Belfast Health and Social Care Trust to reorganise its acute stroke services. By suitably administering thrombolysis (clot-busting drugs), a stroke patient's time in hospital, community rehabilitation and nursing homes can be reduced, so that although the treatment costs money up front, it saves in the long-term and also improves quality-of-life for patients. The research has contributed to changing stroke patient policy in the Belfast Trust as well as enhancing patient quality-of-life, and it could be applied more widely in the future throughout the UK and beyond.
Professor McClean began this research in the 1990's, in collaboration with Professor Peter Millard (formerly Professor and now Emeritus Professor of Geriatric Medicine, St. George's, London, and former President of the British Geriatric Society). Their early work in statistical modelling led to the development of software that could be used by hospital managers to plan bed occupancy. The methods were later incorporated into a modelling tool, initially for the London Merton Borough Social Services to cost and plan care provision and later also used by other Social Services in England. Since 2007 the model has been extended for use with stroke services in collaboration with Dr Ken Fullerton and colleagues in the Belfast Health and Social Care Trust, and a software tool for capacity planning has been developed.
The approach has used data on nearly 10,000 patients, collected from hospital databases and matched to social services databases to form a view of patient behaviour across the integrated care system. The methodology has a strong mathematical underpinning, and the research has been supported by a number of prestigious collaborative grants, including the UK Engineering and Physical Sciences Research Council.
The model developed at Ulster for patient flow through care pathways, including phases in hospital, social services and community care, and extended in collaboration with Dr Ken Fullerton and colleagues from the Belfast City Hospital Stroke Unit, has pioneered an integrated probabilistic model of patient flow that enables associated costs and quality-of-life metrics to be measured. Based on stroke patients' data from the Belfast City Hospital, various scenarios have been explored to compare the costs and patient quality-of-life for thrombolysis (clot-busting) under different regimes. The results have shown that increasing thrombolysis participation from 10% to 50% of eligible patients can reduce cost as well as improving overall patient quality-of-life.
Increasingly, many healthcare services are being delivered through home-based technologies, and a key element is the ability to assess the extent of a person's functional deterioration, particularly in many of the conditions that are associated with ageing. Smart environments enable sensor technologies, information and communication technologies, and adaptive interfaces to be combined to record people's movements and interactions with objects in their environment (for example, in the home or workplace). The purpose is often to conduct subsequent analysis to understand how people are behaving or coping with carrying out everyday tasks, and this analysis is based on automated recognition of the activities that a person is undertaking (for example, cooking, or eating). Within the smart environments research community, there is a lack of validated and annotated datasets, stored in a common format, that can be used to test and evaluate technologies that are developed for activity recognition. This is a well-recognised problem within the research and development community, both academic and commercial. Without such datasets, training and evaluation of automated activity recognition models are limited, which in turn leads to the development of methods for automatically recognising behaviour change being limited in terms of how well they can be generalised, scaled or transferred to other domains. Such methods are an essential part of technology-based approaches to assessing functional deterioration in persons with conditions such as dementia.
Researchers in the Computer Science Research Institute (CSRI) at Ulster are addressing this problem. Based on research in CSRI relating to data storage formats and activity recognition for applications within smart home environments, a European company developing high-precision medical devices has produced a new tool for data annotation. The company has developed a product that is used with a system of stereo-based cameras to record activities that people may carry out in a specified environment (for example, within the kitchen in their own home). Using the product these activities are then annotated (or labelled) to indicate what the person is doing (for example, preparing a meal, or washing the dishes). The new product has the ability to record user interactions with objects (for example, turning on a tap, lifting a cup, opening a door) within a smart environment and to synchronise recordings with data generated by other sensors (for example, notifications via contact or motion sensors of a door opening, a person moving, or a household object being lifted). This product has generated significant additional sales and revenue for the company, which has enabled the company to employ additional technical development staff to extend the product's functionality. CSRI has also established a formal Memorandum of Understanding with the company through which the product now supports automated annotation of activities that is based on CSRI's research on activity recognition.
For the past 10 years a core theme of CSRI research has been data collection and storage, coupled with automated activity recognition within smart environments. During 2003 CSRI developed and evaluated an approach for storage and exchange of electrocardiogram data through an XML-based approach. The output, referred to as ecgML, was the motivation for a subsequent approach developed for use within the smart environments research domain (homeML). HomeML provides a structure that enables all user-related data (activity levels, vital signs, object interactions), both within the home environment and beyond, to be stored in a common format. This format has been evaluated by researchers from 11 different international research centres during 2009-2012, and the evaluation results established the need to introduce the homeML concept more widely across the research community. HomeML is now freely available, and a repository where datasets can be uploaded/downloaded is also being promoted.
This research was also used to support Belfast City Council's successful 13.7M funding bid in 2012 to the NI Department of Culture Media and Sport's Urban Broadband Fund to position Belfast as a super-connected city. As part of the bid CSRI provided supporting rationale in the form of Connected Health Case Studies that would benefit the community if a super-connected city were to be established, demonstrating the significance of high-speed network access for remote monitoring of smart environments and automated recognition of activities taking place in those environments.
The award is enabling Belfast to become a world-class digital city, providing consumers with faster access to wireless broadband services throughout the city and growth potential for local industry.
Estimates from the World Health Organisation suggest that by 2050 the global number of older people will have increased three-fold from the year 2000. Coupled with this will be an increase in prevalence of long-term chronic health conditions. Technology-based solutions have been introduced in efforts to address these challenges. One such solution is the smart environment: a smart environment entails embedding technologies within the environment (for example, the home, the workplace, or a public building) to record people's interactions with objects in the environment, and subsequent processing of the data recorded to infer the activities that are being undertaken by persons in the environment. Smart environments make it possible to monitor a person's health-related conditions over a period of time, and by understanding a person's behaviour it is then possible to provide support when these conditions are detected to be deteriorating, or in cases of an emergency situation.
To successfully monitor a person's health through the use of technology requires the development of sensors that can be worn on the body and that can continuously collect and stream data wirelessly for analysis. Researchers at Ulster's Computer Science Research Institute (CSRI) have been tackling this problem in collaboration with a leading international manufacturer of sensor platforms. This sensor platform development company has produced a new software interface for programming their flagship platform based on research undertaken by researchers in CSRI on rapid prototype development of healthcare applications. This new product has led to an increase in turnover for the company and is now in use globally. The company is also currently marketing a new training product based on research in CSRI.
In 2009 CSRI established a smart environment at Ulster University, funded by the NI Department of Employment and Learning. The smart environment has a wireless sensor network, so that as a person interacts with objects in the environment the sensors continually generate data that are streamed wirelessly. Research has focused on using this data to identify automatically what a person is doing (for example, entering a room, lifting an object, or sitting down), and this work has been extended to infer whether the person is carrying out particular everyday tasks known as activities of daily living, such as making a drink, grooming, or watching TV. The research was developed further through a major cross-border project, the Centre for Intelligent Point-of-Care Sensors, to better understand the behaviour of persons within smart environments. This work developed innovative approaches to detect daily activities, incorporating measures of physical activity, such as step-counts and distance travelled, and physiological data from biometric signals.
Further collaborative research with the company led to user-friendly interfaces being developed that are suitable for non-technical users to programme sensor devices for use in clinical settings, thus enabling widespread use of the sensor platform across the healthcare sector. Configuration and programming of wireless sensor platforms would usually require use of an integrated development environment that could only be fully understood by electronic and software engineers. However, the results of CSRI's research have been used to provide an intermediate layer between the user and the integrated development environment. This intermediate layer makes it possible for healthcare professionals without technical knowledge of sensor platforms to configure wireless sensor devices easily, so that they can monitor functions such as vital signs, movement and orientation, and dictate how the information is visualised, all from a non-technical perspective.
The collaboration between CSRI and the company has been highly successful, resulting in winning a national Project of the Year Award in 2012 from a selection of 50 projects. As a direct result of the collaboration with CSRI the company has increased the number of staff within its Research and Development department, employing new research and development engineers and a new Research and Development Director. A further collaboration between the company and CSRI has led to the joint development of a new product launched in May 2013. This new product, guided and supported by CSRI, provides a starter-pack for the sensor platform that is targeted at the educational market.