Scottish national innovation centre unveils tool that could support early dementia detection


CENSIS, a specialist facility based in Glasgow University, has launched an Internet of Things system that could supporting independent living and provide new insights by monitoring anomalies in electrical usage

Scotland’s national innovation centre has developed an AI-powered device which could help healthcare professionals in making earlier detections of dementia.

Developed by CENSIS – based in the University of Glasgow and created by the Scottish Government as the national innovation centre for sensing, imaging, and IoT technologies – the device is aimed at making independent living safer for older and vulnerable people who live alone. Through internet of things sensor technology, the tool is designed to monitor the use of electric items at home, detecting unusual behaviour which might indicate a medical emergency.

The device is linked to a smart or conventional electric meter, so it can monitor different high-power electrical items within a home, such as kettles or electric showers. It later uses a machine-learning algorithm to analyse the power signatures coming from the house. Throughout the project, Edinburgh University researchers created a library of these signatures, tagging each item to identify when these are turned on, allowing the system to detect any anomalies.


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If an electrical appliance is not on at its usual time, the tool will first send an automated text message to the user. Then, if no response is received, an alert is sent to their nominated contact. The technology has been tested in 20 homes as part of Blackwood Homes and Care’s Peoplehood project, which aims to develop a new model to support for independent living for its residents.

Stephen Milne, director of strategic projects at CENSIS, said: “The system learns the typical activity of the individual living in the household and then spots any erratic behaviour, helping to identify when they may have issues. These could be one-off events, like a fall, and with further research, the system may be able to track changes over a longer time period that may indicate gradual, and more difficult-to-spot health issues, such as the onset of a condition such as dementia.”

A version of this story originally appeared on PublicTechnology sister publication Holyrood

Sofia Villegas

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