Rehabilitation is essential for regaining motor, cognitive, and functional abilities following
stroke. Recent updates to the National Clinical Guidelines for Stroke in the UK and Ireland
now recommend a minimum of three hours of daily multidisciplinary therapy, a fourfold
increase from the previous 45-minutes. Accurately measuring the true delivery of rehabilitation
dosage and intensity, however, remains a critical challenge. Commonly, clinical trials describe
their control groups as "standard physiotherapy," but fail to detail accurately what this entails.
Without accurate measurement techniques, it is impossible to ensure guideline adherence,
correctly interpret research outcomes, or meaningfully compare new interventions against
existing practices.
This thesis presents the co-design, development, and evaluation of a Dosage and Intensity
Monitor (DAIM), a digital system specifically created to objectively quantify rehabilitation
dosage and intensity in stroke survivors across home, research, and clinical environments. Built
through a user-centred design framework aligned with Medical Research Council (MRC)
guidance for complex interventions, the thesis employed focus groups, iterative prototyping,
stakeholder feedback, and survey-based validation to ensure the system was relevant, usable,
and grounded in real-world rehabilitation needs.
The final DAIM system integrates a wearable movement sensor and NFC tagging with a user-friendly mobile application, accurately capturing rehabilitation activities such as walking,
cycling and sit-to-stand. Real-time feedback, gamified goal setting, and group-based progress
tracking were embedded to promote motivation, engagement, and adherence to rehabilitation.
Software prototypes, developed through collaborative design methods and Android Studio
prototyping, ensured optimal accessibility and usability, particularly for users with stroke-related cognitive or motor impairments.
Validation testing in both clinical and research settings demonstrated that the DAIM provided
highly accurate (96% agreement with optical tracking) data with a user friendly system (100%
user success) that agreed (1.23 min difference, on average) with clinician-recorded data. This
system, therefore, addresses the critical gap in objectively measuring rehabilitation dosage and
intensity, offering a robust solution for both clinical practice and research applications. Future
work should focus on optimising hardware ergonomics, producing a market ready system and
scaling up usability testing.
| Date of Award | 3 Mar 2026 |
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| Original language | English |
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| Awarding Institution | - University Of Strathclyde
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| Sponsors | University of Strathclyde |
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| Supervisor | Andy Kerr (Supervisor), Wei Yao (Supervisor), Mark Dunlop (Supervisor) & David Li (Supervisor) |
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