An interdisciplinary team from The University of Manchester has created a ‘magic carpet’ which can immediately detect when someone has fallen over and can help to predict mobility problems.
Falling is the most serious and frequent accident in the home and accounts for 50% of hospital admissions in the over 65s. Our scientists have demonstrated a ‘magic carpet’ that can show a steady deterioration or change in walking habits, possibly predicting a dramatic episode such as a fall.
The research demonstrated that plastic optical fibres, laid on the underlay of a carpet, bend when anyone treads on it and map, in real-time, their walking patterns. Tiny electronics at the edges act as sensors and relay signals to a computer, which can then be analysed to show the image of the footprint and identify gradual changes in walking behaviour or a sudden incident such as a fall or trip. The technology could be used to fit smart carpets in care homes or hospital wards, as well as being fitted in people’s homes if necessary. Physiotherapists could also use the carpet to map changes and improvements in a person’s gait.
The interdisciplinary team used a novel tomographic technique similar to hospital scanners. It maps 2D images by using light propagating under the surface of the smart carpet. One of the team, Dr Patricia Scully said: “The carpet can gather a range of information about a person’s condition; from biomechanical to chemical sensing of body fluids, enabling holistic sensing to provide an environment that detects and responds to changes in patient condition. The carpet can be retrofitted at low cost, to allow living space to adapt as the occupiers’ needs evolve – particularly relevant with an aging population and for those with long term disabilities – and incorporated non-intrusively into any living space.”
University name: University of Manchester
Researcher name and department: Prof Krikor Ozanyan, Professor of Sensors and Sensing Systems and Head of Sensing, Imaging and Signal Processing at the School of Electrical and Electronic Engineering