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UK scientist creates futuristic shoe which can prevent the elderly from falling over

The inventor from the University of Bristol created the shoe when he noticed his 89-year-old mentor was unsteady on his feet

Scientist Dr Jiayang Li (right), from the University of Bristol with his 89-year-old mentor Peter Langlois (centre)
Scientist Dr Jiayang Li (right), from the University of Bristol with his 89-year-old mentor Peter Langlois (centre) (University of Bristol)

When an engineer noticed his 89-year-old mentor was unsteady on his feet, he created a new, futuristic shoe which could one day help him – and a large number of other elderly people – maintain their balance.

The shoe, worn by Peter Langlois, has an insole with hundreds of tiny sensors offering lab-quality, real-time data about his gait which can be displayed on a tablet or mobile phone.

And now, the prototype by University of Bristol inventor Dr Jiayang Li will be demonstrated to industry experts this week.

Dr Li, a lecturer in electrical engineering, said: “Peter has been a huge champion of my work since I started my PhD and it’s amazing that he still meticulously edits the research papers of my research group even at the age of 89.

“His mind remains extremely sharp and his dedication is so inspiring.

“One day I noticed he was unsteady on his feet and almost lost his balance.

“It got me thinking this is very risky and could have terrible consequences if it resulted in a fall, especially for people who live alone.

“Then I wondered if the semiconductor technology we’re working on might actually be able to help.”

The shoe comes with an insole with hundreds of tiny sensors offering lab-quality, real-time data which can be displayed on a tablet or mobile phone
The shoe comes with an insole with hundreds of tiny sensors offering lab-quality, real-time data which can be displayed on a tablet or mobile phone (University of Bristol)

Dr Li’s previous work developed advanced sensors to more accurately measure people’s lung function and pinpoint how their breathing is restricted.

“I realised we could apply similar techniques to monitor how well people are walking,” he said.

“Mapping their leg gestures in detail could detect risk of falls, helping people like Peter stay safe while also keeping their independence at home.

“Although this highly detailed analysis could be obtained in hospital, the challenge was to make the technology more mobile and accessible in everyday life.

“That’s what makes our shoe so special and such a huge leap forward.”

The science involved creating an advanced microchip – also known as a semiconductor – to read all 253 of the tiny sensors on the shoe sole simultaneously.

The data gathered is used to generate images of the person’s foot, highlighting pressure points and assessing whether they are walking in a balanced way or in danger of falling.

To make the device user-friendly, it runs on a low-voltage battery so it can in principle be powered by small screen devices, including a mobile phone or even a smart watch.

The science behind Dr Li’s device will be showcased at the Institute of Electrical and Electronics Engineers conference on Wednesday
The science behind Dr Li’s device will be showcased at the Institute of Electrical and Electronics Engineers conference on Wednesday (University of Bristol)

“The power of the microchip is just 100 microwatts so the device could run for around three months before it needs recharging,” Dr Li said.

“Fall prevention is a huge challenge for ageing populations, so the potential to anticipate and avoid that happening with our invention is really exciting.

“When I explained the concept to Peter, he was really touched and is pleased it might one day be manufactured and used to help so many people.”

The science behind the device will be showcased at the Institute of Electrical and Electronics Engineers conference on Wednesday.

“The concept could easily be mass produced, creating a low-cost shoe sole which could transform older people’s lives,” Dr Li said.

“Next, we’ll run a formal clinical evaluation with a larger and more diverse group to validate how well it predicts fall risk, refine the analysis provided by the device it’s connected to, and work with clinical and industry partners to translate it into a scalable product.”

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