Care Technology Research Group

Overview

The Care Technology research group (CARET) focuses on software technologies that support delivery of health and social care. This includes a wide range of approaches including:

ambient monitoring
decision support for health care
formal modelling of medical devices
hearing aid development
home care technologies and telecare
policy-based management of care delivery
services and platforms for care delivery
symptom management

Staff

Research Students

Research Activities

Members of the research group work on a number of different aspects of care technology:

Ambient Monitoring

This research is focused on long-term monitoring of people requiring support using ambient sensors. These are discreetly placed in the environment, are worn or are carried. The devices passively record data, detect subtle changes in activity signatures, and relate these changes to specific aspects of the user's condition. The current focus within the PAM project is on supporting patients with bipolar disorder at home. By detecting the onset of debilitating episodes, it is hoped that some patients will be helped to manage their condition more effectively.
Decision Support for Healthcare

This research is focussed on providing decision support tools to health care practitioners and patients. Research topics covered within this area include development of mobile decision support tools for paramedics, development of optimal strategies for scheduling chemotherapy, and prediction of the timing and types of side effects of chemotherapy treatment. As an example of this kind of research, the ASyMS project is working to help chemotherapy patients manage their symptoms more effectively. The aim is predict when symptoms will be at their worst and to provide advice on coping with them.
Formal Modelling of Medical Devices

This research aims to support rigorous specification, analysis and testing of medical devices. The approach has been piloted in the field of radiology by the CONFORMED project. A range of formal models has been developed of radiotherapy accelerators. This has allowed the automatic generation of tests to validate correct operation of these safety-critical devices.
Hearing Aid Development

This research aims at exploiting inter-disciplinary advances in intelligent multi-modal signal processing (audio and video) for developing the next generation of hearing aids and cochlear implants for the hearing-impaired.
Home Care Technologies and Telecare

This research is focused on techniques to support delivery of health and social care in the home. The MATCH project is developing and integrating a range of approaches to this. Stirling's contribution is in the fields of home networks, medical device interfacing, policy-based (rule-based) management of care delivery, and flexible service discovery in a home care environment.
Policy-Based Management of Care Delivery

This research is adapting rule-based techniques originally conceived for system management. The pioneering work of the ACCENT project has been extended to support the special needs of managing care delivery to the home. An enhanced version of the APPEL policy language has been developed for defining policies appropriate to home care. This is supported by a user-friendly Policy Wizard for defining home care policies, and a Policy Server for executing them dynamically.
Services and Platforms for Care Delivery

This research is using the techniques of Service-Oriented Architecture to underpin the delivery of health and social care in the home. OSGi (Open Services Gateway Initiative) is the preferred platform for supporting home care devices and services. Drivers (OSGi bundles) have been created for a variety of widely-used interfaces such SMS (Short Message Service), UPnP (Universal Plug and Play), X10 (mains-connected devices), and Visonic (wireless devices). A wide range of home care services has been created. New work is investigating the flexible integration of devices and services for rapid personalisation of care services.
Symptom Management

This research has contributed to the ASyMS project (Advanced Symptom Management System). Symptom data is collected and recorded using a simple interface on a mobile phone. Based on statistical information, this can reassure the patient that their symptoms are typical, and can also provide some indication of the future pattern of symptoms. This has been trialled in chemotherapy, where patients may exhibit a variety of symptoms (e.g. headache, nausea) during cycles of drug treatment.

Research Projects

ASyMS (Advanced Symptom Management System)

The research group has contributed to this project, run by the Cancer Care Research Centre at Stirling. The main aim of this study has been to determine changes in symptom outcomes as a result of collecting symptom data via mobile phone, and giving predictions of likely future symptoms.
CONFORMED (Conformance of Medical Devices)

This project piloted the creation of formal models for safety-critical medical devices such as radiotherapy accelerators. The approach allows the automatic generation of tests to validate correct operation.
COST 2102 (Cross-Modal Analysis of Verbal and Non-Verbal Communication)

Stirling is the grant holder for a large European Science Foundation research network, funded under the EU Framework Programme 7. This involves 27 research institutes and laboratories from across Europe. The aim is to develop advanced speech and natural language processing algorithms for enabling the next generation of telecommunications services and products. Applications include remote health monitoring systems, interactive dialogue systems, intelligent avatars, and multi-modal aids for the hearing-impaired.
DOTPI (Diagnosis and Optimal Treatment Recommendation for Progressive Illnesses)

This project was concerned with investigation and development of computer decision support systems to assist with health decision making. This is predominantly being applied to diagnosis of dementia. However, the techniques and methodologies developed are flexible and can be applied to different medical areas and to non-medical domains.
MATCH (Mobilising Advanced Technologies for Care at Home)

MATCH is a collaborative research project focused on technologies for care at home. Stirling leads a consortium with the Universities of Dundee, Edinburgh and Glasgow as the research partners, along with eleven external partners. The project is developing a range of solutions in the fields of home care networks, lifestyle monitoring, speech communication, and multimodal user interfaces.
PAM (Personal Ambient Monitoring)

PAM is a collaboration among the Universities of Southampton, Nottingham and Stirling. The project is investigating the feasibility of reducing the incidence of debilitating episodes among those with mental health problems. A non-intrusive approach is being developed, based on personalised ambient monitoring of patients in their homes.
Symptom Modelling using Data Mining

This project is part of the ASyMS project (Advanced Symptom Management System). The goal is to apply data mining to predict the likelihood of symptoms for patients undergoing chemotherapy. Analysis of historical data builds a picture of what factors influence the prevalence of certain side-effects, how often they occur, and the severity with which they occur. By providing information about a new individual, it is then possible to predict a pattern of side-effects. This allows the use of preventative techniques to alleviate these symptoms as far as possible.

Care Technology Research Group

Overview

Staff

Research Students

Research Activities

Ambient Monitoring

Decision Support for Healthcare

Formal Modelling of Medical Devices

Hearing Aid Development

Home Care Technologies and Telecare

Policy-Based Management of Care Delivery

Services and Platforms for Care Delivery

Symptom Management

Research Projects

ASyMS (Advanced Symptom Management System)

CONFORMED (Conformance of Medical Devices)

COST 2102 (Cross-Modal Analysis of Verbal and Non-Verbal Communication)

DOTPI (Diagnosis and Optimal Treatment Recommendation for Progressive Illnesses)

MATCH (Mobilising Advanced Technologies for Care at Home)

PAM (Personal Ambient Monitoring)

Symptom Modelling using Data Mining

Collaborators