MyLifeHub: An interoperability hub for aggregating lifelogging data from heterogeneous sensors and its applications in ophthalmic care
Lead Research Organisation:
University of Bedfordshire
Department Name: Inst for Res in Applicable Computing
Abstract
Visual impairment is one of the most feared forms of medical disability, which imposes a great social and economic burden on our society. In the UK, the number of visually impaired people is almost 2 million, with total annual costs estimated over £13,000 million. Notably, age-related increase of visual impairment has been well-documented and is set to be on constant rise owing to the growing ageing population nowadays. Visual impairment has significant impact on quality of life (QoL), as reduced visual acuity seriously affect patients' daily and social activities, with substantial increase of risk of mortality, fracture and falls, depression and other emotional distress.
A variety of responsive instruments for quantifying functional impairment related to vision have been developed. Also, there are well-recognised generic instruments for the assessment of QoL in general health terms. These instruments contain questionnaires referring to a broad range of physical, social and psychological aspects, offering the basis for establishing the QoL profiles of the individuals under concern.
Any changes in the QoL profile, for instance, the increase or drop of the level of physical and social activities before and after an eye surgery, can be used as important indicators for the outcome of the treatment.
However, QoL assessment through written questionnaires has several significant drawbacks. Many answers often rely on participants' memory over a long period of time; people may read differently into the questions with their own interpretations; often there is no way of validating the truthfulness of many responses. These limitations raise serious questions on the reliability and validity of the measurements.
Remarkably, the rapid advance of the Internet of Things (IoT) technology grants us opportunities to build QoL profiles of individuals with increased reliability and validity by monitoring their lifelogging data captured by a variety of IoT assets (namely objects, sensors, mobile apps, web-objects, etc.) with constant connectivity and interaction in a pervasive network. MyLifeHub is such an attempt with focus on the interoperability of the IoT assets, aiming at a common, interoperable and internet-based environment for long-term lifestyle information for individuals. The system will keep users well informed about their daily activities, diet, sleep, mood, blood pressure, pulse, etc., enhancing self-awareness in health and encouraging positive attitudes towards lifestyles. Data sharing among different users will also be enabled to allow for experience exchange and to build healthcare social-networks among users.
Especially, MyLifeHub will feature new techniques enabling simultaneously and long-term quantifying the functional impairment related to vision underpinned with smart glasses (e.g. Google-Glass), which provide wearable sensors to connect with the environment through RFID, infrared, Bluetooth or QR code, allowing for a constant monitoring of the behaviours of people's vision.
MyLifeHub will be utilized as a platform to assess the impact of visual impairment on the QoL of ophthalmic patients both in general health terms and in vision specific terms. The research will be conducted "in the wild" through direct exposure to potential beneficiaries. Our clinical collaborator, Moorfields Eye Hospital (MEH), is the largest eye hospital in the UK and earns a reputation worldwide. The outcome of MyLifeHub will be evaluated by the end users (namely MEH and its patients), allowing for the assessment and forecast of the transformational impact of the IoT technologies in real world terms.
A variety of responsive instruments for quantifying functional impairment related to vision have been developed. Also, there are well-recognised generic instruments for the assessment of QoL in general health terms. These instruments contain questionnaires referring to a broad range of physical, social and psychological aspects, offering the basis for establishing the QoL profiles of the individuals under concern.
Any changes in the QoL profile, for instance, the increase or drop of the level of physical and social activities before and after an eye surgery, can be used as important indicators for the outcome of the treatment.
However, QoL assessment through written questionnaires has several significant drawbacks. Many answers often rely on participants' memory over a long period of time; people may read differently into the questions with their own interpretations; often there is no way of validating the truthfulness of many responses. These limitations raise serious questions on the reliability and validity of the measurements.
Remarkably, the rapid advance of the Internet of Things (IoT) technology grants us opportunities to build QoL profiles of individuals with increased reliability and validity by monitoring their lifelogging data captured by a variety of IoT assets (namely objects, sensors, mobile apps, web-objects, etc.) with constant connectivity and interaction in a pervasive network. MyLifeHub is such an attempt with focus on the interoperability of the IoT assets, aiming at a common, interoperable and internet-based environment for long-term lifestyle information for individuals. The system will keep users well informed about their daily activities, diet, sleep, mood, blood pressure, pulse, etc., enhancing self-awareness in health and encouraging positive attitudes towards lifestyles. Data sharing among different users will also be enabled to allow for experience exchange and to build healthcare social-networks among users.
Especially, MyLifeHub will feature new techniques enabling simultaneously and long-term quantifying the functional impairment related to vision underpinned with smart glasses (e.g. Google-Glass), which provide wearable sensors to connect with the environment through RFID, infrared, Bluetooth or QR code, allowing for a constant monitoring of the behaviours of people's vision.
MyLifeHub will be utilized as a platform to assess the impact of visual impairment on the QoL of ophthalmic patients both in general health terms and in vision specific terms. The research will be conducted "in the wild" through direct exposure to potential beneficiaries. Our clinical collaborator, Moorfields Eye Hospital (MEH), is the largest eye hospital in the UK and earns a reputation worldwide. The outcome of MyLifeHub will be evaluated by the end users (namely MEH and its patients), allowing for the assessment and forecast of the transformational impact of the IoT technologies in real world terms.
Planned Impact
The potential beneficiaries of MyLifeHub are in 4 categories, including those from (1) ophthalmic care, (2) general healthcare, (3) the academic community for IoT research and (4) industry.
Visual impairment imposes a great social and economic burden on individuals and society. In the UK, it is estimated that almost 2 million people have sigh loss, among which around 360,000 people have severe and irreversible conditions. This number is set to increase dramatically, reaching 4 million by 2050. Visual impairment affects people at all ages especially the elderlies, causing significant problems in the increase of mortality, falls, and emotional distress, and many social problems unemployed and isolation. The cost of ophthalmic care is very high in the UK, for example, expenditure directly linked to eye health was over billions from 2009 to 2010.
MyLifeHub is an attempt to build quality of life(QoL) profiles of individuals with increased reliability and validity by constantly monitoring their lifelogging data using the latest IoT technologies. The long-term collection of lifelogging data from a spectrum of IoT assets will offer a completed set of evidence for reliable QoL assessment in ophthalmic care.
From a more general perspective beyond ophthalmic care, MyLifeHub also contributes to general healthcare by bringing fundamental transform to healthcare:
1) A long-term lifestyle record of individuals offer a significant input for personalised medicine, allowing individualised risk prediction and treatment that leads to enhanced reliability and timeliness of medical decisions.
2) Citizens/Patients receive great benefit by active involvement in self-healthcare. MyLifeHub keeps citizens informed about their daily activities and health, encouraging positive attitudes towards healthy lifestyles. This is supported by a rapid growing of public interest in self-healthcare.
3) Healthcare and associated social welfare costs are increasing exponentially due to growing ageing population and prolonged life expectancy, and they will soon become unsustainable unless we change the way in which people are supported. In many cases, there is a need to shift medical care from institutions to the home environment.
From the academic perspective, IoT research under new settings equipped with newly developed ICT gadgets from a very wide variety of background, such as lifelogging devices, smart glasses and mHealth apps, etc. brings new opportunities in addressing new challenges within the area of IoT and its technology enablers (e.g. scalable data mining, visualization and security). In addition, MyLifeHub also supports to build an infrastructure to maximise the yield of biomedical research expenditure by supplying healthcare providers with more comprehensive patient information.
MyLifeHub also comes with great commercial potentials. There is a growing public interest in self monitoring for transformative healthcare, evidenced by strong market indications: e.g. consumers used to self-monitor health conditions will account for more than 80% of wireless devices in 2016; more than 97,000 mobile apps available related to health, with the top 10 mobile health apps generating up to four million free and 300,000 paid downloads per day.
Visual impairment imposes a great social and economic burden on individuals and society. In the UK, it is estimated that almost 2 million people have sigh loss, among which around 360,000 people have severe and irreversible conditions. This number is set to increase dramatically, reaching 4 million by 2050. Visual impairment affects people at all ages especially the elderlies, causing significant problems in the increase of mortality, falls, and emotional distress, and many social problems unemployed and isolation. The cost of ophthalmic care is very high in the UK, for example, expenditure directly linked to eye health was over billions from 2009 to 2010.
MyLifeHub is an attempt to build quality of life(QoL) profiles of individuals with increased reliability and validity by constantly monitoring their lifelogging data using the latest IoT technologies. The long-term collection of lifelogging data from a spectrum of IoT assets will offer a completed set of evidence for reliable QoL assessment in ophthalmic care.
From a more general perspective beyond ophthalmic care, MyLifeHub also contributes to general healthcare by bringing fundamental transform to healthcare:
1) A long-term lifestyle record of individuals offer a significant input for personalised medicine, allowing individualised risk prediction and treatment that leads to enhanced reliability and timeliness of medical decisions.
2) Citizens/Patients receive great benefit by active involvement in self-healthcare. MyLifeHub keeps citizens informed about their daily activities and health, encouraging positive attitudes towards healthy lifestyles. This is supported by a rapid growing of public interest in self-healthcare.
3) Healthcare and associated social welfare costs are increasing exponentially due to growing ageing population and prolonged life expectancy, and they will soon become unsustainable unless we change the way in which people are supported. In many cases, there is a need to shift medical care from institutions to the home environment.
From the academic perspective, IoT research under new settings equipped with newly developed ICT gadgets from a very wide variety of background, such as lifelogging devices, smart glasses and mHealth apps, etc. brings new opportunities in addressing new challenges within the area of IoT and its technology enablers (e.g. scalable data mining, visualization and security). In addition, MyLifeHub also supports to build an infrastructure to maximise the yield of biomedical research expenditure by supplying healthcare providers with more comprehensive patient information.
MyLifeHub also comes with great commercial potentials. There is a growing public interest in self monitoring for transformative healthcare, evidenced by strong market indications: e.g. consumers used to self-monitor health conditions will account for more than 80% of wireless devices in 2016; more than 97,000 mobile apps available related to health, with the top 10 mobile health apps generating up to four million free and 300,000 paid downloads per day.
Organisations
- University of Bedfordshire (Lead Research Organisation)
- NHS Greater Glasgow and Clyde (NHSGGC) (Collaboration)
- Queens Park Group Surgery (Collaboration)
- Bedford Hospital (Collaboration)
- Kingston General Hospital (Collaboration)
- Putnoe Medical Centre (Collaboration)
- DIGITAL HEALTH AND CARE INSTITUTE (Collaboration)
- London Road Health Centre (Collaboration)
- NHS LANARKSHIRE (Collaboration)
- NHS Scotland (Collaboration)
- UNIVERSITY OF BEDFORDSHIRE (Collaboration)
- iManageCancer (Collaboration)
- Addenbrooke's Hospital (Collaboration)
- Hinchingbrooke Hospital (Collaboration)
- Ansmart (United Kingdom) (Project Partner)
Publications
Petkov H
(2022)
Causality Learning with Wasserstein Generative Adversarial Networks
in International Journal of Artificial Intelligence & Applications
Yang P
(2016)
GSWO: A programming model for GPU-enabled parallelization of sliding window operations in image processing
in Signal Processing: Image Communication
Yang P
(2018)
Improving Utility of GPU in Accelerating Industrial Applications With User-Centered Automatic Code Translation
in IEEE Transactions on Industrial Informatics
Yang P
(2018)
Lifelogging Data Validation Model for Internet of Things Enabled Personalized Healthcare
in IEEE Transactions on Systems, Man, and Cybernetics: Systems
Wu S
(2019)
Literature Explorer: effective retrieval of scientific documents through nonparametric thematic topic detection
in The Visual Computer
Parvinzamir F
(2019)
MyEvents: A Personal Visual Analytics Approach for Mining Key Events and Knowledge Discovery in Support of Personal Reminiscence
in Computer Graphics Forum
Zhang X
(2018)
MyHealthAvatar lifestyle management support for cancer patients.
in Ecancermedicalscience
| Description | By working with MyHealthAvtar, we have already achieved the following the key funding: MyLifeHub project attempts with a focus on the interoperability of the IoT assets, aiming at a common, interoperable and internet-based environment for long-term lifestyle information for individuals. The system keeps users well informed about their daily activities, diet, sleep, mood, blood pressure, pulse rate, etc., enhancing self-awareness in health and encouraging positive attitudes towards lifestyles. Data sharing among different users is enabled to allow for experience exchange and to build healthcare social-networks among users. MyLifeHub features new techniques enabling simultaneously and long-term capturing the behaviour of individual citizens and patients, allowing for a constant monitoring of their behaviours. It is utilized as a platform to assess the impact of visual impairment on the QoL of ophthalmic patients both in general health terms and in vision specific terms. The project provides a unique platform that empowers normal citizens in terms of supporting their life management and healthy lifestyles. Whereas in the past, the so-called 'grey area' patients with potential problems in health were not looked after by the health care system. As a citizen oriented platform, the platform provides services to the general public that help them identify and mange their risk of developing diabetes. It is a perfect complement to the health care system. It offers a one-stop service for citizens in terms of data collection, and self-management services, such as monitor, record, and education. The system supports the storage the behaviours and daily activities of citizen. It functions as a supportive environment to empower normal citizens in looking after their own health, raising their self-awareness of any potential risk of developing diseases while encouraging their healthy lifestyles in terms of doing routine daily exercise, stopping smoking and controlling their diet. In addition, we have incorporated tailored services, such as quality of life assessment ophthalmic care, which is used by the users access the impact of visual impairment to their life. Technically: • Regard the above technique investigation, it appears that personal user activities based health data can be collected by mobile apps and sensors • The implementation of repositories takes into account the scalability requirements of life logging data as well as reliability of the data storage in disaster events, e.g. hard drive failure. Since large amount of data is constantly coming lots of users' various data sources, it is fair to treat the data repository in the context of Big Data. Bearing in mind the number of users is increasing and the quantity and types of the information are emerging that will be stored on daily basis for the duration of a person's entire life, the repository implementation tackles this ever increasing data with the ability to scale horizontally. • The ultimate goal of data collection is to make use of data. With the data reasoning tools, The platform is not only a health data collecting tool and repository but also a powerful data analysis platform, including Sensor data validation, Event and activity extraction and ranking, Information summary .and recommendation model, Knowledge extraction and reasoning. • The data information delivered to the users via summary information visualization with the dashboard, Life pattern visual analytics, daily activity information extraction, annotation and visualization from the data repository with the diary and Profile summary display. This information delivery is done via both web browsers and mobile platform. • Develop a novel multiobjective genetic programming (MOGP) hidden Markov model (HMM) as a supervised learning technique to predict human daily active states and monitor behaviour pattern from sequential life-logging data. We demonstrate that the new method performs accurately and effectively over range of sensor limitations and provides competitive results compared to one of the-state-of-art classifiers, with better generality and potential in healthcare setting. Some of this work has been recently presented in IASTED biomedical engineering conference 2016, at Austria. A full paper submitted to Artificial Intelligent in Medicine is currently under review. • Transform a high-dimensional feature space into a new low-dimensional discrete class space using MOGP to construct an effective emission matrix for HMM model. The compact HMM helps improving the overall sequential learning performance. • Develop a semi-supervised learning HMM with differential evolution (DE) method for semantic behaviour modelling. The technology developed in this project can make significant contribution to the following areas: • Assess the effectiveness of ophthalmic patient treatment by semi-automatically respond to Quality of Life (QOL) related questionnaires both in general health and vision specific terms with more reliability and validity. In the current ophthalmic clinical practice, a variety of responsive measures for quantifying functional impairment related to vision are used. The measures include questionnaires referring to a broad range of physical, social and psychological aspects, such as, VF-14 [5], SF-12 [6]. The intelligent data analysis suite can overcome the limitations caused by the written questionnaires and provide a fast and accurate assessment of QoL. Examples include automated prediction of overall daily active scores and assessing night driving capability using sequential lifelogging data, such as walking steps, travel duration, distance. This will enable ophthalmologists to carry out reliable assessment of the QoL of eye patients, resulting in useful measures for the impact of eye diseases and for the effectiveness of treatments. • Monitor individual's behaviour patterns (e.g. the level of physical and social activities before and after treatment) using daily activities data and diet, sleep, mood, blood pressure, pulse rate, etc, enhancing self-awareness in health and encouraging positive attitudes towards lifestyles. • We also expect new research and outcomes from QoL assessment using lifelogging data, which will promote a high level of interest in healthcare research. During the lifetime of the project development, we have built a strong cross-disciplinary network with our academic partner (University of Bedfordshire) and Moorfields Eye Hospital (MEH), who provide key clinical input to the project from the perspective of ophthalmic care. The outcome of the project will be evaluated by the end users. MEH is currently recruiting 50 participants in either a single visit or number of visits over the course of up to 3 month. This will allow us to assess the transformational impact of the advanced technologies in real world terms. The following is a clinical study to assess the outcomes of the MyHealthAvatar app developed within the scope of this project. A mobile phone app for reducing prolonged sedentary behaviour in Type 2 diabetes: a randomised controlled feasibility study There are an estimated 4 million people in the UK living with diabetes; 90% of these being Type 2 diabetes mellitus (T2DM). This disease costs the UK £9 billion each year making this a leading public health concern. Cardiovascular disease (CVD) is responsible for 52% of mortalities in people with T2DM, which is largely due to poor regulation of fasting and postprandial glucose levels. Interventions are thus needed to improve glycaemic control in this population. Total daily sedentary time is associated with an increased risk of T2DM, CVD and cardiometabolic disease risk markers, often independent of moderate-to-vigorous physical activity (MVPA) levels. Experimental studies have also demonstrated that breaking up prolonged sitting with regular short bouts of activity (e.g. standing and slow walking) can help regulate postprandial glucose levels and blood pressure. Reducing total and prolonged sitting time has thus been suggested as a potential approach to improve outcomes in T2DM care. This study aimed to evaluate the feasibility and acceptability of a self-regulation mobile phone app for reducing prolonged sedentary behaviour in people with T2DM. Twenty people with T2DM (age 55.0±7.1 years, body mass index 31.3±5.9 kg/m2, nine males) were recruited and randomised to an 8-week intervention or control condition. Physical activity and sitting were measured at baseline and during the last intervention week using an activPAL device and cardiometabolic risk markers were taken at baselines and post-intervention. Means and effect sizes were calculated to compare between-group changes from baseline to end of intervention; 0.2, 0.5 and 0.8 indicated a small, medium and large effect. A total of nine intervention participants and nine control participants completed the study (n=2 dropouts) and provided 100% of data at each time point. The intervention group decreased total sedentary time by 20.6 min/day (d=0.35) and increased the number of breaks from sitting by 8.8 breaks/day (d=0.72) and light physical activity by 7.0 min/day (d=0.62) from baseline to follow-up compared to the control group. There were no meaningful changes (d<0.25) between groups in daily standing time, MVPA or number of steps. 2-h blood glucose concentrations (-0.65 mmol/L; d=0.42), body fat% (-1.2%; d=0.57) and diastolic blood pressure (-2.3 mmHg; d=0.27) decreased in the intervention group relative to controls. The MyHealthAvatar app has the potential to reduce prolonged sedentary behaviour and improve cardiometabolic risk in individuals with T2DM. The effectiveness of this app will now be investigated in a fully powered randomised controlled trial. Aim: To evaluate the feasibility and acceptability of a self-regulation smartphone app for reducing prolonged sitting in people with Type 2 diabetes mellitus (T2DM). Methods: This was a two-arm randomised controlled feasibility trial. The intervention group used the MyHealthAvatar-Diabetes smartphone app for 8 weeks. The app uses a number of behaviour change techniques aimed at reducing and breaking up sitting time. Eligibility, recruitment, retention and completion rates for the outcomes (sitting, standing, stepping and health-related measures) assessed trial feasibility. Interviews with participants explored intervention acceptability. Results: Participants with T2DM were randomised to the control (n=10) and intervention groups (n=10). Recruitment and retention rates were 71% and 90%, respectively. The remaining participants provided 100% of data for study measures. The MyHealthAvatar-Diabetes app was viewed as acceptable for reducing and breaking up sitting time. There were preliminary improvements in the number of breaks in sitting per day, body fat %, glucose tolerance, attitude, intention, planning, wellbeing, positive affect and negative affect in favour of the intervention group. Conclusions: The findings indicate that it would be feasible to deliver and evaluate the efficacy of the MyHealthAvatar-Diabetes app for breaking up sitting time and improving health outcomes in a full trial. |
| Exploitation Route | During the lifetime of the project development, we have built a strong cross-disciplinary network with our academic partner (University of Bedfordshire) and Moorfields Eye Hospital (MEH), who provide key clinical input to the project from the perspective of ophthalmic care. The outcome of the project will be evaluated by the end users. MEH is currently recruiting 50 participants in either a single visit or number of visits over the course of up to 3 month. This will allow us to assess the transformational impact of the advanced technologies in real world terms. A number of new research proposals or ideas have been put forward, which will make use of the platform. A brief summary of these proposals and ideas is given as follows: • For peer-support: The success of diabetes management depends on the ability of patients with diabetes to successfully sustain effective self-management behaviors, taking prescribed medications, following diet and exercise regimens, self-monitoring, and coping emotionally with the rigors of living with diabetes. Productive health care visits and nurse case management programs are important means of supporting patients' diabetes self-management but alone often cannot adequately meet many patients' needs. Higher levels of social support-especially illness-specific or regimen-specific support-are associated with better diabetes and other illness self-management. Peer support among patients with the same chronic health problem may be a particularly effective intervention, combining the benefits of both receiving and providing social support. "Peer support" is defined as "support from a person who has experiential knowledge of a specific behavior or stressor and similar characteristics as the target population." MyLifHub has been designed with inherent features to support self-management. A research proposal has been put forward to extend and evaluate the platform with respect to its capacity to support peer education among the communities for diabetes care. • For healthcare research in frailty: There has been research interest in utilising MyLifeHub in frailty research. The idea is to use the app as a way to collect patient information in order to detect early signs of frailty. We expect two MSc students (MSc by Research) to work on this topic. • For sport science: Research in sports science is interested in exploring the correlations between the activities and health (i.e. measured according to bio measures such as glucose, blood pressure). Normally such a test is done in a lab environment intensively within a short period of days. However, researchers are particularly interested in exploring the relationships during daily life. MyLifeHub may play such a role to support their research. It has been decided that one MSc student (Rachael Champion) will start to use MyLifeHub to work on this and we are seeking further support for MSc by Research to explore this area. • For patients with memory problems: To help patients which start to have early sign of memory problems, doctors from memory clinics often help them with hints about their past experience with a purpose of stimulating their own memory. Since MyLieHub records the daily activities of individuals without requiring much of their efforts, it is seen potentially as an ideal tool used by the doctors and patients for the treatment of memory problems. Currently through the collaborator we are seeking a trial of the system by the patients in memory clinics. • For Care home: Advinia is a network of care homes providing the full spectrum of care services. The senior management team has been involved in care since 1999 and works in partnership with staff, residents, family and social workers. It provides homely facilities without an institutional feel. Following an initial meeting on 10th Feb 2016 with the Care Home owner, Mr. Sanjeev Kanoria, who has expressed a great interest in using MyLifeHub as a place for clinical records and lifestyle activity, the next meeting will set up on 1st March 2016 to continue the discussion with Mr. Len Merton (CEO) to arrange details in the collaboration. • For Africa: Through our contact in Nigeria, we have sent letters for the expression of interest for research to the ministry of Health and Executive Governor. Through discussions with colleagues from Africa, we realised that many rural areas in Africa still lack the most basic system of healthcare records. Records are vital to medical decision-making because they allow the doctors to see all the relevant information about the patients' health, such as previous visits, medication given and vaccine history. Without records, there is nowhere to store lab results, and consequently basic errors can occur on important matters such as blood transfusions. At a national level, medical records are needed to collectively provide up-to-date information about the health of the population: the Ebola outbreak in West Africa has especially highlighted the need for an effective record system which could deliver advanced warnings of the outbreaks, monitor the long-term health of survivors, and assess the effectiveness of treatments. We believe that MyLifeHub has the potential to fulfil this need. It is cost effective to deploy and maintain, since it requires only a web-based app to communicate with a server in Europe, so it is ideally suited to use in developing areas • The technique findings discovered in this project have also been integrated into our newly developed MyHealthAvatar platform, which is a 3-year research project funded by the European Commission. MyHealthAvatar aims to build up the entire concept of "digital patient for individual citizens to maintain and manage their long-term health-status information in support of clinical care and clinical research excellence. The integrated system can keep users well informed about their daily activities, diet, sleep, mood, blood pressure, pulse rate, etc. estimating/predicting overall daily active scoring, and monitoring individual's behaviour pattern, leading to enhancing self-awareness in health and encouraging positive attitudes towards lifestyles. • Some of the key techniques findings have been presented in the international Association of Science and Technology for Development (IASTED) Biomedical Engineering Conference, in February 2016. A detailed description of the technique findings has also submitted to the journal of Artificial Intelligence in Medicine. The purposes of the study for eye patients are: Study 1. Adherence with topical glaucoma medications in patients with glaucoma and ocular hypertension and effects of device interventions. Study 2. Investigating the representativeness of a single clinic-based tonometry measurement of the intraocular pressure profile as measured with self-tonometry throughout the day. Study 3: The relationship between activity, intraocular pressure and ocular perfusion pressure in patients with pigment dispersion syndrome and pigmentary glaucoma. The purposes of the diabetic study are to assess the feasibility of using the MyHealthAvatar mobile phone application to reducing prolonged sedentary behaviour and improve glucose control in Type 2 diabetes. Capability, opportunity, and motivation (COM-B) to reduce prolonged sedentary behaviour and monitor glucose levels are assessed in addition to impact on cardiometabolic risk markers The purpose of the study for prostate/breast cancer patient is to test the technology adaptation by patients with prostate/breast cancers. |
| Sectors | Digital/Communication/Information Technologies (including Software),Healthcare |
| Description | MyLifeHub attempts with a focus on the interoperability of the IoT assets, aiming at a common, interoperable and internet-based environment for long-term lifestyle information for individuals. The system keeps users well informed about their daily activities, diet, sleep, mood, blood pressure, pulse rate, etc., enhancing self-awareness in health and encouraging positive attitudes towards lifestyles. Data sharing among different users is enabled to allow for experience exchange and to build healthcare social-networks among users. It features new techniques enabling simultaneously and long-term capturing the behaviour of individual citizens and patients, allowing for a constant monitoring of their behaviours. It is utilized as a platform to assess the impact of visual impairment on the QoL of ophthalmic patients both in general health terms and in vision specific terms. The research is conducted "in the wild" through direct exposure to potential beneficiaries. Our clinical collaborator, Moorfields Eye Hospital (MEH). The outcome of MyLifeHub is evaluated by the end users (namely the Moorfields Eye Hospital and its patients), allowing for the assessment and forecast of the transformational impact of the IoT technologies in real world terms. Therefore, there is a strong partnership between the academia and healthcare professionals. Moorfields Eye Hospital is an NHS eye hospital is the oldest and largest eye hospital in the world and is internationally renowned for its comprehensive clinical and research activities. The hospital is a major international tertiary care and training centre in ophthalmology, and over half of all ophthalmologists in the UK have received specialist training at the hospital Visual impairment imposes a great social and economic burden on individuals and society. MyLifeHub aims to develop a computing platform to build QoL profiles of individuals with increased reliability and validity by constantly monitoring their lifelogging data using the latest internet of things (IoT) and intelligent data analysis technologies. This research aims at impact not only in ophthalmic care, but also in general healthcare by bring fundamental transform to healthcare, allowing for individualised risk prediction and treatment and raising self-awareness in health and encouraging positive attitudes towards healthy lifestyles. MyLifeHub has huge implications for patient self-monitoring healthcare in the UK, as it has the potential to change the way in which traditional healthcare is undertaken. The acceptance of this system by general research communities, hospitals and clinics will open opportunities for many hospital sectors, leading to reinforced synergy and leadership of the UK universities. MyLifeHub is collaborating with an on-going 3-year European project under 7th Framework called MyHealthAvata(with a EC investment over €2.4 million), which aims at solutions for the access, collection and sharing of long term and consistent personal health status through an integrated representation of "digital patient" in silico environment, allowing for the delivery of clinical analysis, prediction, prevention and treatment tailored to individual citizens. The platform is currently undergoing a trial organised by MEH. Acquiring patient-based data for QoL assessment and Patient Reported Outcome Measures (PROMs) has been increasingly adopted as an important measure to estimate the impact of eye disease and to assess the effectiveness of ophthalmic treatment, for either individuals or groups of patients. This allows for comparison with other available alternatives, prioritisation and allocation of resource in ophthalmic care. Visual impairment has a significant impact on quality of life (QoL); reduced visual acuity seriously affects patients' daily and social activities, with substantial increased risk of mortality, fracture, falls, depression and other emotional distress. This study will examine 50 participants in either a single visit or number of visits over the course of up to 3 months. Participants who take devices away from the hospital setting for self-use will be invited back to return the devices so that the health data collated over the 3 month period can be extracted and then sent to the University of Bedfordshire and University of Lincoln for analysis. • To assess feasibility of application of novel visual function and ophthalmic disease monitoring technologies in patients and ophthalmic care professionals • To assess the impact of visual impairment on the Quality of Life of ophthalmic patients both in general health and vision specific terms. • To build an interoperability hub that will allow the collection of data from a range of IoT assets into a common, internet-enabled environment, providing profiles of lifestyles of individuals, which will enable interoperability, accessibility and innovation from novel applications and services in healthcare. • To track the level of physical and social activities before and after eye surgery Self-reported activity and compliance data by patient including: • behavioural measurements. • Patient-reported outcome and experience measures. • Visual function measurements. • Clinical measures such as intraocular pressure. The study consists of 3 methods of recruitment, by which a total of 50 participants will be recruited. We have set the sample value of participants to 50. The following sites will be recruiting: Bedford Hospital NHS Trust, Hinchingbrooke Healthcare NHS Trust, Ealing Hospital and Moorfields Eye Hospital NHS Foundation Trust. Participants are recruited from sub-specialty clinics (Oculoplastics, Glaucoma, Cataract, Age-related Macular Degeneration (AMD), Diabetic), and also from healthy volunteers (members of staff and from professional bodies) who will be invited along with patients from clinics to participate in Patient and Public Involvement (PPI) focus groups. All aforementioned participants willing to undergo the 3 month study may be introduced to the devices in the study after their scheduled clinic appointment, during the PPI groups. Participants will be invited to attend and will be escorted either by their carers or by a member of the research team to either the Richard Desmond Children's' Eye Centre and or the Clinical Tutorial Centre and NIHR BRC Simulation Room, which are situated at Moorfields Eye Hospital. Alternatively, if the participants are being seen at Bedford Hospital they will be escorted either by their carers or a member of the research team to a PPI group in either the Room 5 Rye Close building or the Porta Cabin in Rye Close. During these PPI focus groups, participants will be given information leaflets, consent forms, and a manual of the devices being used. Participants can familiarise themselves with the devices and the utilisation of the associated usage of the MyHealthAvatar platform. Participants will then be asked to complete quality of life questionnaires before using any devices and on returning the devices at their next scheduled visit. The Follow up stage will vary from within a few days for example for intensive Intraocular Pressure (IOP) monitoring - where clinically applicable, a number of weeks for Post-operative Cataract and drop compliance/ restriction of daily activities; to possibly 3 months for mobile tracking apps. Participation in the study starts from the day participants come in for their routine appointments and are invited to attend the patient forums where they will be able to ask more questions about the study and test out the devices which may be used before deciding on whether they wish to formally consent to taking part in the study. The Follow up stage is likely to vary from within a few days for example for intensive Intraocular Pressure (IOP) monitoring - where clinically applicable, a few weeks for Post-operative Cataract and drop compliance/ restriction of daily activities; to possibly a couple of months for mobile tracking apps • Stage 1 (Introduction): Patient and Public Involvement (PPI) Focus Group - (Only the one visit /same visit that participants are attending for clinically) - patients in clinic or from the in-house patient forum database will be invited to come to a PPI event which would be located in either the Richard Despond's Children's' Eye Centre and or the Clinical Tutorial Centre and NIHR BRC Simulation Room which are all situated at Moorfields Eye Hospital Alternatively, if the participants are being seen at Bedford Hospital they will be escorted either by their carers or a member of the research team to a PPI group in either the Room 5 Rye Close building or the Porta Cabin in Rye Close. This PPI group will last for approximately 20-60 minutes depending on the level of interest from participants. All participants (both patients and healthy volunteers - which include staff and members from professional bodies in ophthalmic care) will be able to observe and test the technology available and will be given an explanation of how the study and technology works, and what will be measured. This will be communicated using demonstrations of the CE marked devices & sensors listed below, full details can be found in Section 12 Devices and Techniques: Feedback will be collated and assessed to see relevance of which form of technology is most helpful going forwards and what changes to existing software is needed to make it more clinically and patient friendly. Participants will have the option of using either their own smartphones or they will be able to use the products from those listed above, which we will have at our disposal by utilising the joint EPSRC grant from the University of Bedfordshire and University of Lincoln. Participants will then be able to download the advanced new apps in order for their data to be submitted and tracked. The information from the tracking, such as heart rate, blood pressure amongst other forms of data that is generated will be extracted from the technology and transmitted to the University of Bedfordshire and University of Lincoln. • Stage 2: (Measurement) MyLifeHub Study -Participants will be invited to take part in the main MyLifeHub study from the PPI/Unstructured Group or through their routine clinics. Participants will be invited to test, use or wear the selected technology from the sensors and devices listed above. The technology used will then be correlated with appropriate Visual Functioning questionnaires. All completed questionnaires will be in a paper format and kept in the Investigator Site File, whereby the results will be transposed into a digital format. Participants will be given the specific devices for up to 3 months to wear and use. Depending on the nature of the participants visit to Moorfields Eye Hospital, they will then be asked to return for one or more extra visits, whereby we will request that they return the devices given to them at their first visit. This will be timed for when a planned follow up appointment is booked; for example a Post-operative Cataract visit at 6 weeks, or Glaucoma follow up appointment. Clinical scenarios: • Oculoplastics: A visit at two weeks before the surgery (first appointment before surgery), the nurse will teach the patients how to use the technology and the self-monitoring will start. On the day of surgery (2 weeks after first visit) patient will meet the nurse (discuss any further queries). Postop two weeks after the surgery (finale visit) study terminated. Group of patients to be involved; Unilateral ptosis surgery, Bilateral blepharoplasty, Unilateral Floppy Eyelid syndrome patients. • Measurements; steps, HR, sleep activity, O2 • Glaucoma: Following the diagnosis of the condition (first visit), the patients will start the medication together with the self-monitoring for 2-4 weeks when follow up visit occurs, next follow up visit at 3-4 months. • Important to integrate in the platform the medications (antihypertensive) taken and what time for these patients to detect effect on IOP. • Measurements; steps, HR, sleep activity, IOP. • Cataract: Following the diagnosis of the condition (first visit), the nurse will teach the patients how to use the technology and the self-monitoring will start. On the day of surgery (up to 3 months after first visit) patient will meet the nurse. Next visit is 5 weeks postop when study terminated. • For patients with both glaucoma and cataract conditions, there is some evidence to show that the cataract surgery will help bring down the IOPs. Also, the absorption of the medicine may become greater because of the wound. • Measurements; steps, HR, sleep activity, IOP. • AMD: Following diagnosis of Exudative AMD, when patient listed for Injection (first visit) nurse will meet the the patient and self monitoring will start. On the day of injection patient will meet the nurse and 1 month later on postop visit when study will be terminated. • Measurements; steps, HR, sleep activity, IOP. Also, by collaborating with MyHealthAvatar, the platform has currently been under a trial by about 200 (healthy) participants European-wide. A number of workshops have been organised for the platform and technologies to be tried by the end users. We fully recognise that the best way of convincing the public to adopt the technology is to provide them with an opportunity to try it and see what performance benefits and the adoption of the project outcomes can bring. The platform has been made available to different user groups through a number of stages: • From June 2014 to Sept 2014, by internal members within the consortium • From Sept 2014 to Dec 2015: by selected members external to the consortium, mainly through the collaborators and other linked projects • From Dec 2015 onwards: by the public, allowing them to access by e-consent The platform is available at https://myhealthavatar.org/mha/. The app is available from the Google Play Store for free download and unlimited trial Activities by the University of Lincoln • The platform was demonstrated to our Computer Science third year students on image processing module, MSc students on advanced software engineering module, PhD/researchers in our school research groups. • It was also demonstrated in a number of events including during the early diagnosis innovation workshop organized by CRUK in December, 2015; • Medical image understanding and analysis (MIUA) conference organized by Lincoln in July 2015; • meeting with Lincoln hospital in March, 2015. • We have also recently presented our work in the 12th IASTED International Conference on Biomedical Engineering (BioMed), February, 2016 at Austria. All the participants are encouraged to use the platform and we also provided the participant with the evaluation survey forms and related material and invited them to complete the surveys. Activities by the University of Bedfordshire During the course of the development of several key components on site at the University of Bedfordshire, the developers and researchers were invited to demonstrate and discuss their work with current students from a varying range of courses and disciplines. Members of the team conducted talks and workshops during lectures and practical sessions to engage the student body, and conducted written and digital evaluations in guided sessions using the extensive computing resources of the Universities' computer science and technology department. All evaluation methods provided students with a number of individual component evaluation forms, participants were given the option of completing the evaluation in any order and to complete any number of forms they had the time for. • During the month of November 2015 two classroom sessions were arranged with students studying computer science undergraduate courses related to computer graphics and game development. The second group of computer science students in November were asked to trial and evaluate the components. • In December 2015 we were invited to make a presentation to a large group of sports science students in Bedford. • Later in December 2015 the opportunity arose to present and demonstrate the platform to students studying a health care pathway who were not as computer literate as previous groups of students. This was an important test of how regular users would react to the platform. • In February 2016 we provide specialist cover for a unit tackling the topic of mobile applications development. This presented a good opportunity to gather specific evaluation feedback on the mobile application component of the platform. • ICT 2015, Lisbon, 20-10-2015 4 multi-part paper based evaluations, converted into David's digital version 11-12-2015 • MobileHealth 2015, Oct 2015, London • IoTBDH-2015, Oct 2015, Liverpool • Bedford hospital eye clinic, 19-01-2016, Demo to Dr Saleh & Krisztina and iCare rep. No evaluations. • Practical CIS022-2 MK010, 16-02-2016, 5 digital evaluations (David's newest version) • C110 Evaluation drop in session, 17-02-2016, 2 digital evaluations (David's newest version) • Practical CIS022-2 C110, 18-02-2016, 6 digital evaluations (David's newest version) • C110 Evaluation drop in session, 19-02-2016, 14 digital evaluations (David's newest version) We have also conducted another trial for diabetes patients - data have been collected and a MSc for research dissertation has been written - more outcomes will be made available next year. |
| First Year Of Impact | 2016 |
| Sector | Digital/Communication/Information Technologies (including Software),Healthcare |
| Impact Types | Economic |
| Description | A tailored intervention to reduce sitting behaviour in people with Type 2 Diabetes: A randomised-controlled feasibility study |
| Amount | £137,510 (GBP) |
| Organisation | Diabetes UK |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 12/2020 |
| End | 06/2022 |
| Description | Virtual Clinical Trial Emulation with Generative AI Models |
| Amount | £112,060 (GBP) |
| Funding ID | MR/X005925/1 |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 09/2022 |
| End | 02/2023 |
| Description | iManageCancer |
| Amount | € 600,000 (EUR) |
| Funding ID | 643529 |
| Organisation | European Commission |
| Sector | Public |
| Country | European Union (EU) |
| Start | 02/2014 |
| End | 07/2017 |
| Description | Collaboration with Scotland NHS |
| Organisation | NHS Scotland |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | Initial discussions for future collaboration with three NHS local regions, NHS GGC, NHS Lanarkshire and NHS Lothian. A University-wide doctoral training centre is set up (from my side), in which they will make contributions by providing clinical input Feng Dong has recently joined NHS Lanarkshire as an honorary member of staff to work on the big data initiative. This initiative originally came from MyLifeHub. |
| Collaborator Contribution | Initial discussions for future collaboration with three NHS local regions, NHS GGC, NHS Lanarkshire and NHS Lothian. A University-wide doctoral training centre is set up, in which they will make contributions by providing clinical input |
| Impact | A University-wide doctoral training centre is set up |
| Start Year | 2020 |
| Description | Collabration with iManageCancer |
| Organisation | iManageCancer |
| Country | European Union (EU) |
| Sector | Public |
| PI Contribution | IManageCaner is a H2020 project offering services to support self-management in cancer care. MyLifeHub will be integrated into the architecture of the iManageCancer platform to support the lifestyle and physical activities of cancer patients. |
| Collaborator Contribution | The iManageCancer platform will utilise the hence promote the outcome of MyLifeHub |
| Impact | The MyLifeHub app will be integrated into the iManageCancer platform |
| Start Year | 2015 |
| Description | Digital Health and Care Institute, Scotland |
| Organisation | Digital Health and Care Institute |
| Sector | Learned Society |
| PI Contribution | Initial discussions took place for collaboration and this will continue in terms of collaborative funding bid. A University-wide doctoral training centre is set up, which includes the Digital Health and Care Institute, Scotland . |
| Collaborator Contribution | They will provide clinical expertise and connections with the clinical bodies in Scotland |
| Impact | A University-wide doctoral training centre is set up A new joint H2020 proposal will be submitted soon. |
| Start Year | 2019 |
| Description | Glaucoma test with Hinchingbrooke Hospital |
| Organisation | Hinchingbrooke Hospital |
| Country | United Kingdom |
| Sector | Hospitals |
| PI Contribution | The eye clinic unit from the hospital is organising a clinical trial to see the impact of technology to help the treatment of glaucoma patients. The MyLifeHub app was built by the technical partner including us. |
| Collaborator Contribution | The eye clinic unit from the hospital is organising a clinical trial to see the impact of technology to help the treatment of glaucoma patients. |
| Impact | We expect clinical publications and further larger scale studies. |
| Start Year | 2017 |
| Description | Low vision test at Kingston Hospitals |
| Organisation | Kingston General Hospital |
| Country | Canada |
| Sector | Hospitals |
| PI Contribution | The MyLifeHub app created by the technical partners in this project are used to detect the quality of life change of patients with low vision |
| Collaborator Contribution | The clinical partner is organising the trials by low vision patients |
| Impact | clinical publication in the future. |
| Start Year | 2017 |
| Description | MyLifeHub for healthcare research in diabetes |
| Organisation | London Road Health Centre |
| Country | United Kingdom |
| Sector | Hospitals |
| PI Contribution | The clinical partners (given above) are using the MyLifeHub app to evaluate the impact of the technologies in diabetes self-management. The technical partners within this project created the app. |
| Collaborator Contribution | The clinical partners (given above) are using the MyLifeHub app to evaluate the impact of the technologies in diabetes self-management. Data have been collected and analysed. A MSc research dissertation has been written. More to report in the next year |
| Impact | A mobile phone app for reducing prolonged sedentary behaviour in Type 2 diabetes: a randomised controlled feasibility study There are an estimated 4 million people in the UK living with diabetes; 90% of these being Type 2 diabetes mellitus (T2DM). This disease costs the UK £9 billion each year making this a leading public health concern. Cardiovascular disease (CVD) is responsible for 52% of mortalities in people with T2DM, which is largely due to poor regulation of fasting and postprandial glucose levels. Interventions are thus needed to improve glycaemic control in this population. Total daily sedentary time is associated with an increased risk of T2DM, CVD and cardiometabolic disease risk markers, often independent of moderate-to-vigorous physical activity (MVPA) levels. Experimental studies have also demonstrated that breaking up prolonged sitting with regular short bouts of activity (e.g. standing and slow walking) can help regulate postprandial glucose levels and blood pressure. Reducing total and prolonged sitting time has thus been suggested as a potential approach to improve outcomes in T2DM care. This study aimed to evaluate the feasibility and acceptability of a self-regulation mobile phone app for reducing prolonged sedentary behaviour in people with T2DM. Twenty people with T2DM (age 55.0±7.1 years, body mass index 31.3±5.9 kg/m2, nine males) were recruited and randomised to an 8-week intervention or control condition. Physical activity and sitting were measured at baseline and during the last intervention week using an activPAL device and cardiometabolic risk markers were taken at baselines and post-intervention. Means and effect sizes were calculated to compare between-group changes from baseline to end of intervention; 0.2, 0.5 and 0.8 indicated a small, medium and large effect. A total of nine intervention participants and nine control participants completed the study (n=2 dropouts) and provided 100% of data at each time point. The intervention group decreased total sedentary time by 20.6 min/day (d=0.35) and increased the number of breaks from sitting by 8.8 breaks/day (d=0.72) and light physical activity by 7.0 min/day (d=0.62) from baseline to follow-up compared to the control group. There were no meaningful changes (d<0.25) between groups in daily standing time, MVPA or number of steps. 2-h blood glucose concentrations (-0.65 mmol/L; d=0.42), body fat% (-1.2%; d=0.57) and diastolic blood pressure (-2.3 mmHg; d=0.27) decreased in the intervention group relative to controls. The MyHealthAvatar app has the potential to reduce prolonged sedentary behaviour and improve cardiometabolic risk in individuals with T2DM. The effectiveness of this app will now be investigated in a fully powered randomised controlled trial. The following paper has been submitted to Diabetes Research and Clinical Practice "Randomised controlled feasibility study of the MyHealthAvatar-Diabetes smartphone app for reducing prolonged sitting time in Type 2 diabetes mellitus" |
| Start Year | 2017 |
| Description | MyLifeHub for healthcare research in diabetes |
| Organisation | Putnoe Medical Centre |
| Country | United Kingdom |
| Sector | Hospitals |
| PI Contribution | The clinical partners (given above) are using the MyLifeHub app to evaluate the impact of the technologies in diabetes self-management. The technical partners within this project created the app. |
| Collaborator Contribution | The clinical partners (given above) are using the MyLifeHub app to evaluate the impact of the technologies in diabetes self-management. Data have been collected and analysed. A MSc research dissertation has been written. More to report in the next year |
| Impact | A mobile phone app for reducing prolonged sedentary behaviour in Type 2 diabetes: a randomised controlled feasibility study There are an estimated 4 million people in the UK living with diabetes; 90% of these being Type 2 diabetes mellitus (T2DM). This disease costs the UK £9 billion each year making this a leading public health concern. Cardiovascular disease (CVD) is responsible for 52% of mortalities in people with T2DM, which is largely due to poor regulation of fasting and postprandial glucose levels. Interventions are thus needed to improve glycaemic control in this population. Total daily sedentary time is associated with an increased risk of T2DM, CVD and cardiometabolic disease risk markers, often independent of moderate-to-vigorous physical activity (MVPA) levels. Experimental studies have also demonstrated that breaking up prolonged sitting with regular short bouts of activity (e.g. standing and slow walking) can help regulate postprandial glucose levels and blood pressure. Reducing total and prolonged sitting time has thus been suggested as a potential approach to improve outcomes in T2DM care. This study aimed to evaluate the feasibility and acceptability of a self-regulation mobile phone app for reducing prolonged sedentary behaviour in people with T2DM. Twenty people with T2DM (age 55.0±7.1 years, body mass index 31.3±5.9 kg/m2, nine males) were recruited and randomised to an 8-week intervention or control condition. Physical activity and sitting were measured at baseline and during the last intervention week using an activPAL device and cardiometabolic risk markers were taken at baselines and post-intervention. Means and effect sizes were calculated to compare between-group changes from baseline to end of intervention; 0.2, 0.5 and 0.8 indicated a small, medium and large effect. A total of nine intervention participants and nine control participants completed the study (n=2 dropouts) and provided 100% of data at each time point. The intervention group decreased total sedentary time by 20.6 min/day (d=0.35) and increased the number of breaks from sitting by 8.8 breaks/day (d=0.72) and light physical activity by 7.0 min/day (d=0.62) from baseline to follow-up compared to the control group. There were no meaningful changes (d<0.25) between groups in daily standing time, MVPA or number of steps. 2-h blood glucose concentrations (-0.65 mmol/L; d=0.42), body fat% (-1.2%; d=0.57) and diastolic blood pressure (-2.3 mmHg; d=0.27) decreased in the intervention group relative to controls. The MyHealthAvatar app has the potential to reduce prolonged sedentary behaviour and improve cardiometabolic risk in individuals with T2DM. The effectiveness of this app will now be investigated in a fully powered randomised controlled trial. The following paper has been submitted to Diabetes Research and Clinical Practice "Randomised controlled feasibility study of the MyHealthAvatar-Diabetes smartphone app for reducing prolonged sitting time in Type 2 diabetes mellitus" |
| Start Year | 2017 |
| Description | MyLifeHub for healthcare research in diabetes |
| Organisation | Queens Park Group Surgery |
| Country | United Kingdom |
| Sector | Hospitals |
| PI Contribution | The clinical partners (given above) are using the MyLifeHub app to evaluate the impact of the technologies in diabetes self-management. The technical partners within this project created the app. |
| Collaborator Contribution | The clinical partners (given above) are using the MyLifeHub app to evaluate the impact of the technologies in diabetes self-management. Data have been collected and analysed. A MSc research dissertation has been written. More to report in the next year |
| Impact | A mobile phone app for reducing prolonged sedentary behaviour in Type 2 diabetes: a randomised controlled feasibility study There are an estimated 4 million people in the UK living with diabetes; 90% of these being Type 2 diabetes mellitus (T2DM). This disease costs the UK £9 billion each year making this a leading public health concern. Cardiovascular disease (CVD) is responsible for 52% of mortalities in people with T2DM, which is largely due to poor regulation of fasting and postprandial glucose levels. Interventions are thus needed to improve glycaemic control in this population. Total daily sedentary time is associated with an increased risk of T2DM, CVD and cardiometabolic disease risk markers, often independent of moderate-to-vigorous physical activity (MVPA) levels. Experimental studies have also demonstrated that breaking up prolonged sitting with regular short bouts of activity (e.g. standing and slow walking) can help regulate postprandial glucose levels and blood pressure. Reducing total and prolonged sitting time has thus been suggested as a potential approach to improve outcomes in T2DM care. This study aimed to evaluate the feasibility and acceptability of a self-regulation mobile phone app for reducing prolonged sedentary behaviour in people with T2DM. Twenty people with T2DM (age 55.0±7.1 years, body mass index 31.3±5.9 kg/m2, nine males) were recruited and randomised to an 8-week intervention or control condition. Physical activity and sitting were measured at baseline and during the last intervention week using an activPAL device and cardiometabolic risk markers were taken at baselines and post-intervention. Means and effect sizes were calculated to compare between-group changes from baseline to end of intervention; 0.2, 0.5 and 0.8 indicated a small, medium and large effect. A total of nine intervention participants and nine control participants completed the study (n=2 dropouts) and provided 100% of data at each time point. The intervention group decreased total sedentary time by 20.6 min/day (d=0.35) and increased the number of breaks from sitting by 8.8 breaks/day (d=0.72) and light physical activity by 7.0 min/day (d=0.62) from baseline to follow-up compared to the control group. There were no meaningful changes (d<0.25) between groups in daily standing time, MVPA or number of steps. 2-h blood glucose concentrations (-0.65 mmol/L; d=0.42), body fat% (-1.2%; d=0.57) and diastolic blood pressure (-2.3 mmHg; d=0.27) decreased in the intervention group relative to controls. The MyHealthAvatar app has the potential to reduce prolonged sedentary behaviour and improve cardiometabolic risk in individuals with T2DM. The effectiveness of this app will now be investigated in a fully powered randomised controlled trial. The following paper has been submitted to Diabetes Research and Clinical Practice "Randomised controlled feasibility study of the MyHealthAvatar-Diabetes smartphone app for reducing prolonged sitting time in Type 2 diabetes mellitus" |
| Start Year | 2017 |
| Description | MyLifeHub for healthcare research in frailty |
| Organisation | University of Bedfordshire |
| Department | Faculty of Health and Social Sciences |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | The idea is to use the app as a way to collect patient information to detect early signs of frailty |
| Collaborator Contribution | we expect two MSc students from the partner (specialises in healthcare research) to work on this topic |
| Impact | no direct outcome yet |
| Start Year | 2016 |
| Description | NHS Lanarkshire |
| Organisation | NHS Lanarkshire |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | Feng Dong has been appointed as an honorary professor in NHS Lanarkshire. The contribution area is AI for health. |
| Collaborator Contribution | The NHS Lanarkshire offers clinical expertise and clinical scenarios. |
| Impact | We have submitted a number of research proposal. We have also set up a joint MSc project in AI for health |
| Start Year | 2021 |
| Description | NHSGGC |
| Organisation | NHS Greater Glasgow and Clyde (NHSGGC) |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | research work on data analysis |
| Collaborator Contribution | work on clinical input and data provision |
| Impact | expected joint publications |
| Start Year | 2022 |
| Description | The technologies for Eye Patients for Surgery Care |
| Organisation | Addenbrooke's Hospital |
| Country | United Kingdom |
| Sector | Hospitals |
| PI Contribution | we are providing technical support to the clinical assessment |
| Collaborator Contribution | The app and devices are used by the patients in the partnership hospital to check the quality of life change of the patients before and after the eye surgery. The clinical partner has organised a few clinical assessments to the technologies |
| Impact | we are looking into clinical publications on the outcomes from the assessment. |
| Start Year | 2014 |
| Description | The technologies for Eye Patients for Surgery Care |
| Organisation | Bedford Hospital |
| Country | United Kingdom |
| Sector | Hospitals |
| PI Contribution | we are providing technical support to the clinical assessment |
| Collaborator Contribution | The app and devices are used by the patients in the partnership hospital to check the quality of life change of the patients before and after the eye surgery. The clinical partner has organised a few clinical assessments to the technologies |
| Impact | we are looking into clinical publications on the outcomes from the assessment. |
| Start Year | 2014 |
| Title | MyHealthAvatar - Breast Cancer Care |
| Description | a mobile app for self management of breast cancer patients |
| Type Of Technology | Webtool/Application |
| Year Produced | 2017 |
| Impact | The software will be tested by patients in clinical piloting |
| Title | MyHealthAvatar - Diabetes Care |
| Description | A mobile app for diabetic care for the use by diabetic patients |
| Type Of Technology | Webtool/Application |
| Year Produced | 2017 |
| Impact | The app is used by a clinical trial organised through 3 GP clinics in Bedford |
| Title | MyHealthAvatar - EyeCare |
| Description | An eye care mobile app for eye patients |
| Type Of Technology | Webtool/Application |
| Year Produced | 2017 |
| Impact | The app is used in the clinical trial by eye patients at three UK hospitals. |
| Title | MyHealthAvatar Platform (with joint contribution from MyLifeHub) |
| Description | a web based platform to support health living and well being |
| Type Of Technology | Webtool/Application |
| Year Produced | 2015 |
| Impact | normal citizens and patients with long term conditions will use the platform for self-management of their diseases. |
| Title | MyHealthAvatar app - Prostate Cancer Care |
| Description | A mobile app for the use by prostate cancer patients |
| Type Of Technology | Webtool/Application |
| Year Produced | 2017 |
| Impact | The app is used by an European research project called iManageCacner and will be tried by patient organised by an Italian Hospital. |
| Title | Visual App for Health Records |
| Description | Based on the research outcome from the project, we have started a new initiative to develop a new app. This is an Android system based app to collect and visualise individual health records by patients. The app is still in development. |
| Type Of Technology | Webtool/Application |
| Year Produced | 2019 |
| Impact | We target the benefit for patients by allowing them to access to their long term medical history. |
| Description | A Talk to pharmaceutical professionals in China |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A Talk to pharmaceutical professionals in Beijing, China in Oct 2018, |
| Year(s) Of Engagement Activity | 2018 |
| Description | A presentation in Zhejiang University, China |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | A presentation to students at Zhejiang University, China, May 2018 |
| Year(s) Of Engagement Activity | 2018 |
| Description | A presentation in Zhejing Media University, China |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Undergraduate students |
| Results and Impact | A presentation to students in Zhejiang Media University, China, Oct 2018 |
| Year(s) Of Engagement Activity | 2018 |
| Description | A presentation in an industrial event in China |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | Present work to a small business audience in China |
| Year(s) Of Engagement Activity | 2018 |
| Description | A presentation in an industrial event in kuala lumpur |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | A presentation was made to industrial audience including some clinicians. The size of the audience is about 20. |
| Year(s) Of Engagement Activity | 2017 |
| Description | Demonstration at Warwick University |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | demonstration of the project outcome to the Cyber security research group at WWG at the University of Warwick |
| Year(s) Of Engagement Activity | 2015 |
| Description | Demonstration at the Moorfields Eye Hospital |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | demonstrate the results to the medical professionals at the Moorfields Eye Hospital |
| Year(s) Of Engagement Activity | 2015 |
| Description | Health and Care Futures Showcase Event |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Health and Care Futures Showcase Event with Golden Jubilee National Hospital, Scotland |
| Year(s) Of Engagement Activity | 2023 |
| Description | Industrial workshop in China |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | A presentation was given to the event and over 10 people attended the workshop. |
| Year(s) Of Engagement Activity | 2017 |
| Description | Keynote speech: Workshop on Computer Graphics in Biomedical and Biological Imaging Data, held in conjunction with Computer Graphics International 2016 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | An invited talk on a conference |
| Year(s) Of Engagement Activity | 2016 |
| Description | Meeting with Lanarkshire NHS |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Professional Practitioners |
| Results and Impact | Meeting with professionals and clinicians to discuss collaboration with NHS Lanarkshire in health data and AI. |
| Year(s) Of Engagement Activity | 2020 |
| Description | Meeting with students from Communication University of Zhejiang |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Undergraduate students |
| Results and Impact | Present the health research in my research group |
| Year(s) Of Engagement Activity | 2019 |
| Description | Meetings with medical professionals |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Professional Practitioners |
| Results and Impact | We have organised over 10 meetings to engage the medical professionals at both Bedford Hospital and Addenbrookes Hospital. The main purpose of the meeting is to discuss the details about the clinical assessment. We have also held other meetings to plan for future assessment, including with they eye clinicians in Oxford. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Participation in a workshop for public health in Hangzhou, China |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | A workshop in public health and patient engagement in health |
| Year(s) Of Engagement Activity | 2019 |
| Description | Participation in an AI event in Beijing, China |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | A public event about AI |
| Year(s) Of Engagement Activity | 2019 |
| Description | Presentation for AI in Complex Care |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | This workshop is organised to address people with multiple and complex needs experience several problems at the same time, such as mental health, homelessness, drug, and alcohol misuse, offending and family breakdown. We made a presentation about AI for complex care. |
| Year(s) Of Engagement Activity | 2022 |
| Description | Presentation for eHealth Forum 2016 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A presentation in eHealth Forum 2016 |
| Year(s) Of Engagement Activity | 2016 |
| Description | Presentation for experts in sport science |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Professional Practitioners |
| Results and Impact | Introduce the technologies for experts in sports science for arranging trials for diabetic patients with sport therapies |
| Year(s) Of Engagement Activity | 2016 |
| Description | Presentation for older patients |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Patients, carers and/or patient groups |
| Results and Impact | The event was to introduce the platform to some older patients who were interested in technology for healthcare |
| Year(s) Of Engagement Activity | 2016 |
| Description | Presentation to Integrated Community Mental Health Services for Older People |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | presentation for medical professionals in professional training |
| Year(s) Of Engagement Activity | 2016 |
| Description | Presentation to Policy Markers in China |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Policymakers/politicians |
| Results and Impact | A presentation in some police makers in Beijing, China, Sept 2018 |
| Year(s) Of Engagement Activity | 2018 |
| Description | Visit to Israel health system |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A visit to introduce research to healthcare professionals and industry colleagues in Tel aviv |
| Year(s) Of Engagement Activity | 2019 |
| Description | demonstration to ice-login |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Industry/Business |
| Results and Impact | speak to the owner of Ice-Login Ltd (a UK based SME) to explore chances for collaborations |
| Year(s) Of Engagement Activity | 2015 |
| Description | demonstration to vitalograph |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Industry/Business |
| Results and Impact | speak to the owner of vitalograph (a UK based family run SME) to explore chances for further collaborations |
| Year(s) Of Engagement Activity | 2015 |
| Description | visit to Bedford Hospital |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Discussion of the latest project outcomes |
| Year(s) Of Engagement Activity | 2017 |