Data-Assisted Rehabilitation (Dare)
How can data and new technologies improve stroke rehabilitation? In Dare, health and technology researchers collaborate to develop solutions for more objective measurement of patients’ progress and to provide better data-driven support throughout the rehabilitation process.
Yearly, more than 12,000 people in Norway and 12 million people worldwide suffer a stroke, and the vast majority require structured rehabilitation and training afterwards.
Stroke patients are among those with the greatest need for long-term, coordinated rehabilitation, often facing significant physical, cognitive and psychological challenges. At present, there is little or no use of technology for objective movement measurement after stroke. Instead, assessments are largely based on the clinical judgement, experience and time available to individual practitioners, supplemented by paper-based assessments and scoring tools, and the use of simple instruments.
New technology and new methods
The project aims to develop new technologies and methodologies for the objective analysis of patient movement data. The goals are to improve rehabilitation planning, provide more accurate and objective measurements of patient progress, and ultimately achieve better functional outcomes and a better quality of life for patients following rehabilitation.
At the system level, we examine how patients, family members, healthcare professionals, and different services interact throughout the rehabilitation pathway, and how digitalisation can improve service organisation, information flow, and collaboration.
At the individual level, we investigate how physical, psychological, and social factors influence rehabilitation, and how different types of data can be integrated to provide better insight into each patient's progress, motivation, and ability to cope with everyday challenges.
Through these subprojects, we aim to develop knowledge and solutions that can contribute to more coordinated, personalised, and data-driven rehabilitation.
Bringing together health and technology research
The project brings together researchers in robotics, healthcare services, innovation, interprofessional collaboration, physiotherapy and rehabilitation from the Faculty of Health and Social Sciences (FHS) and the Faculty of Technology, Environmental and Social Sciences (FTMS) at HVL. The project group works closely with Førde Hospital Trust (Helse Førde), Bergen Hospital Trust (Helse Bergen) and the Røde Kors Haugland Rehabilitation Centre (Hauglandssenteret).
Data-Assisted Rehabilitation
The research project is part of HVL’s strategic university initiative in Digital Health and builds on several doctoral research projects focusing on data-assisted measurement of patient progress and data-assisted rehabilitation through collaboration between healthcare professionals and patients. The project combines research in sensor technology, data analysis and artificial intelligence with research in service innovation and rehabilitation to improve rehabilitation services across specialist healthcare, municipal health services and the home environment.
Objectives
- Develop new methods for measuring and analysing objective movement data to assess progress and the effectiveness of rehabilitation, both within healthcare services and in the home environment.
- Develop new methods for data representation (such as a digital twin) that provide meaningful insights for specialists and generalist healthcare professionals, as well as for patients and their families at home.
- Link physical health, psychosocial factors, and exercise to investigate factors that may increase motivation for independent exercise and rehabilitation efforts.
- Work towards a more patient-centred and coordinated rehabilitation service, enabling patients to gain greater knowledge, insight, responsibility and self-management throughout their own rehabilitation journey.
Effects and impact
Stroke is one of the leading causes of long-term disability and death, and represents a significant economic burden on today’s healthcare system. Traditional diagnosis and rehabilitation are labour-intensive, rely on relatively few data points, and are largely subjective, depending on clinical judgement, professional experience and the time available to individual practitioners.
Data-assisted rehabilitation can provide continuous monitoring of patient progress, helping to compensate for human factors, while offering real-time feedback on improvements and adjustments to training programmes. This can increase patient motivation and help validate or correct self-reported data. Objective data are essential for identifying effective rehabilitation approaches and for delivering individually tailored treatment programmes.
Intensive rehabilitation with closer patient follow-up has been shown to significantly reduce costs, length of hospital stay and the proportion of patients requiring institutional care. Studies have also demonstrated that technology-supported rehabilitation in the home can reduce costs by up to 80%, while at the same time delivering substantial improvements in patients’ functional abilities. At present, approximately 50% of stroke survivors return to work, and even a modest improvement in this figure would have significant positive economic and societal impacts.
Data-assisted rehabilitation has considerable potential to reduce pressure on healthcare professionals, increase patient autonomy and enable more personalised rehabilitation programmes. It also offers major opportunities to improve the quality and consistency of rehabilitation across hospitals, municipal healthcare services and the home environment. Rehabilitation is a societal challenge that requires a radically interdisciplinary approach, bringing together technology development, service innovation and healthcare innovation in a collaborative effort.
Implementation
The project will organise Living Labs and interdisciplinary workshops involving users, healthcare professionals and researchers, while a postdoctoral researcher will focus on AI and machine learning for data-assisted rehabilitation. Applications for external research funding will constitute a major activity within the project.
The project team at HVL works closely with MD, PhD Eirik Vikane at Haukeland University Hospital, and Tarja Kvalheim, Head of Research at the Red Cross Haugland Rehabilitation Centre (Hauglandssenteret). Helse Førde is an integrated research partner in the project. In addition, the project collaborates with Helse Vest IKT, municipalities across Vestland county, various patient and user organisations, and an extensive international network of research partners.
Project management
Key personell at HVL
Key personell av HVL
- Jeanette Svarstad
- Raquel M. Tirach
- Merethe Hustoft
- Gizem Ates Venås
- Joost Van Wijchen
- Yngve Lamo
- Øystein Stavø Høvig
- Alireza Aliyari
- Laurenz Elstner
- Frederico Klein
- Tarja Kvalheim (extern)
- Eirik Vikane (extern)