Abstract
There is an urgent need to provide quality-of-life to a growing population of older adults living independently. Solutions that focus on the person and take into account their preferences and context are recognised as key. We introduce a framework for representing and reasoning about the Activities of Daily Living of older adults living independently at home. The framework integrates data from sensors and data from participants derived from semi-structured interviews, home layouts and additional contextual information, such as the researchers’ observations. These data are used to create formal models, personalised for each participant according to their preferences and context. Requirements specific to each individual are formulated and encoded in Linear Temporal Logic, and a model checker is used to verify whether each is satisfied by the model of the participant’s behaviour. We demonstrate the framework’s generalisability by applying it to two different participants, highlighting its potential to enhance the safety and well-being of older adults ageing in place.
| Original language | English |
|---|---|
| Pages (from-to) | 1-10 |
| Number of pages | 10 |
| Journal | IEEE Sensors Journal |
| Early online date | 27 Nov 2025 |
| DOIs | |
| Publication status | E-pub ahead of print - 27 Nov 2025 |
Keywords / Materials (for Non-textual outputs)
- Activities of Daily Living
- older adults
- unobtrusive sensors
- linear temporal logic
- model checking
- personalised models
- contextual information
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Dive into the research topics of 'A personalised formal verification framework for monitoring activities of daily living of older adults living independently in their homes'. Together they form a unique fingerprint.Research output
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A Personalised Formal Verification Framework for Monitoring Activities of Daily Living of Older Adults Living Independently in Their Homes
Contreras, R., Smola, F., Farič, N., Zheng, J., Hillston, J. & Fleuriot, J. D., 11 Jul 2025, University of Edinburgh, p. 1-19, 19 p.Research output: Working paper › Preprint
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