Using AI at-home monitoring to prevent falls

A new partnership aims to rethink fall prevention strategies and enable older people to live independently for longer.

Aston University’s experts in AI have entered a knowledge transfer partnership (KTP) with telecare provider Legrand Care to create a scientifically validated blueprint for a predictive assisted-living system.

The research team are developing new ways to use and understand patterns of sensor data from across the home environment. By carefully monitoring changes to an individual’s day-to-day conditions and patterns, the novel system will be able to predict and signal various issues — such as loneliness, dementia, depression and risk of falls — so preventative care can be given. It will incorporate machine learning, advanced data analytics and the latest knowledge of human behaviour.

Ensuring the system can be widely adopted will be crucial because many assistive-living devices are purchased but rarely used. The project will determine the optimal range of sensors needed for a system that is both predictive and minimally disruptive. Expertise in business model innovation and human centred design will support Legrand Care to develop a package that is technically advanced, affordable and acceptable to users.

If offered widely, this next-generation predictive system has the potential to transform the care sector, with smart sensors across connected home and care environments that support caregivers and provide peace of mind to relatives. Typically, care in these settings is reactive, responding only after a fall or incident has taken place. Preventing incidents will help to improve the long-term health and independence of older people so they can go about their day-to-day activities with confidence. Predictive assisted-living technology also has potential to facilitate more personalised care from service providers and reduce pressures on acute care services.

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