The aim is to design, develop and evaluate a smart multi-sensor instrument that allows a personalised assessment of gait, stability and activities of daily living. The data will be used to perform different analysis to show risks associated with physical frailty and/or falls and pre-falls using AI approaches.

Approximately 28%-35% of people aged 65+ experience one fall every year
Near-falls, which include slips, trips and loss of balance which do not result in a fall are more common than an actual falls and have been shown to be associated with increased risk of an actual fall in the future. Detection however of falls and near falls rely upon accurate recognition and identification of high risk situations and activities linked with these types of adverse events. Identification of these high risk situations in the free living environment, may be more meaningful for effective preventive measures.

For more details and how to apply please follow the link
Contacts: and/or