FITsense: Fall Prediction in Technology-Enabled ‘Fit Homes’

FITsense: Fall Prediction in Technology-Enabled ‘Fit Homes’
This project is developing a falls prediction system that uses data from Smart Home technologies installed in peoples’ homes. It identifies patterns of activity, and changes in these patterns, that are linked to increased risk of falling. This system will help residents live well and independently in their homes for longer.
Funding Body
Award Value
Start Date
End Date
Funding Body
The Data Lab
Award Value
£106,665
Start Date
September 2017
End Date
November 2018

Smart Home sensors are often used for home automation and security. In contrast, this system monitors the activities and behaviours of a person within their home using in-home sensors. It identifies patterns of activity, and changes in these patterns, that are linked to increased risk of falling. This system will allow timely interventions before falls occur and enable people to live independently and well in their own homes for longer.

Data is captured by a range of sensors installed in specially-designed, technology-enabled ‘Fit Houses’. Targeting specific activities identified as pre-cursors to falls, the system analyses data derived from these sensors to identify patterns of activity, and changes in these patterns, that are linked to increased risk of falling. These evidence-based alerts should enable families and agencies to intervene with preventative measures before incidents occur.

The system is being trialled at the 1st phase of the ‘FIT Houses’ project comprising 15 assisted living homes designed by Carbon Dynamic at Albyn’s Dalmore ‘FIT Houses’ village in Alness, near Inverness.

Fitsense Project Floor PlanFitsense Project Floor Plan Showing Sensors

Papers

Massie, Forbes, Craw, Fraser & Hamilton (2018). Monitoring Health in Smart Homes using Simple Sensors. 3rd International Workshop on Knowledge Discovery in Healthcare Data at IJCAI-ECAI-18, Stockholm, Sweden.

Massie, Forbes, Craw, Fraser & Hamilton (2018). FITsense: Employing Multi-Modal Sensors in Smart Homes to Predict Falls. 26th International Conference on Case-Based Reasoning (ICCBR-18), Stockholm, Sweden. Springer.

Leaflet

AWARDS
  • Holyrood Connect 2018 Digital Health & Care Award