Occupational therapists will test a digital toolkit that turns data from movement sensors, door contacts, and under-mattress monitors into clinical reports for people living with dementia. The problem is that occupational therapists currently rely on brief clinic visits or carer reports to assess how well someone manages daily tasks like cooking, moving around the home, or sleeping. This gives them only a snapshot. Home sensors can track these activities continuously for months, but raw sensor data is not useful in a clinical setting. This project builds a bridge between the two: it will co-design a report template that translates sensor patterns into actionable insights for therapists. If the toolkit works, it could shift dementia care from reactive to proactive. Therapists might spot a gradual decline in kitchen use or disrupted sleep patterns weeks before a crisis, allowing them to adjust equipment, adapt the home, or revise care plans earlier. For the person living with dementia, this could mean staying in their own home longer and reducing the burden on unpaid carers. The study will also inform national strategies for integrating digital monitoring into dementia care frameworks.
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Background: Dementia care requires innovative approaches due to the rising number of cases globally. This research evaluates the use of digital descriptions of behaviour of people living with dementia (PLWD) to assist occupational therapists (OTs). This study will develop a digital toolkit that incorporates activities of daily living (ADL) data from home sensors. As a sub-study of the MinderCare translational research and digitally-enabled care study, this research will use the Minder digital platform developed by the UK Dementia Research Institute. Research Question: How can a digital toolkit using home sensors for monitoring acvtivities of daily living enhance the care provided by occupational therapists to people living with dementia? Aims and Objectives: The primary aim is to develop a digital toolkit for use by occupational therapists comprising automated analysis of data from low-burden home sensors for monitoring ADL in people living with dementia. Objectives include: Conducting a scoping review on sensor use for ADL monitoring in OT practice. Co-designing an ADL report template for clinical use. Evaluating the impact of sensor-derived ADL data on OT provision Assessing user experience and acceptance of the Minder ADL toolkit. Methods: This mixed-methods study will be conducted in two main work packages: 1. Scoping Review and Evaluation: A scoping review on the use of sensor data for ADL monitoring will inform the study. Fifty PLWD will be recruited and monitored for six months using the Minder system, which includes movement, door, under-mattress, kitchen appliance and environmental sensors. Minder algorithms transform sensor data into actionable information for clinical decision-making. An ADL report template co-designed with OTs, will be be used to share insights with clinical teams. The impact of sensor-derived ADL data on OT provision will be evaluated in: (i) Equipment prescription, risk management, care needs, and discharge destinations. (ii) Goal setting, achievement, and progress tracking. (iii) Environmental adaptations and functional performance (iv) Adaptability of interventions and longitudinal monitoring of performance (v) Changes in patients' routines and behaviours. Data from this evaluation process, standardised clinical measures, individual healthcare usage and clinical events will be analysed using statistical methods. 2. User Experience and Acceptance: Qualitative interviews will be conducted with 10 patients or their carers to evaluate user experience. The System Usability Scale and Technology Acceptance Model-2 questionnaire will be administered to OT users. Additionally, two focus groups will be conducted with OTs to explore the usability of the ADL report. Qualitative analysis methods will be used to synthesise and report findings. Anticipated Impact and Dissemination: This research aims to improve dementia care by providing occupational therapists with a digital toolkit which could enhance early detection of ADL risks, and facilitate personalised care plans. This can help PLWD by improving their overall well-being, reducing the burden on carers, and helping them to remain in their homes longer. Findings will be disseminated through journal articles, conferences, workshops, and public engagement events. The study will also inform policy and practice by integrating sensor technologies into dementia care frameworks, potentially influencing national strategies for digital monitoring in dementia care.
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