Dr. Jiayang Li of the University of Bristol has developed a futuristic shoe designed to help older adults avoid falls. The invention emerged when the engineer noticed that his 89-year-old mentor, Peter Langlois, was becoming unsteady while walking, leading him to consider how this technology could help maintain balance.<\/p>\n
The shoe includes an insole equipped with hundreds of tiny sensors that provide real-time data about gait quality. In addition, an advanced microchip was developed to read all 253 sensors in the sole simultaneously.<\/p>\n
The collected data makes it possible to generate visual maps of the foot, highlighting pressure points and evaluating whether a person walks with proper balance or faces a high risk of falling.<\/p>\n
The device is easy to use and operates on a low-voltage battery, allowing it to be powered by small display devices. According to Dr. Li, \u201cThe power of the microchip is just 100 microwatts so the device could run for around three months before it needs recharging.\u201d<\/p>\n
Li explained how the project began: \u201cOne day I noticed [my mentor] 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\u2019re working on might actually be able to help.\u201d<\/p>\n
Previous work<\/p>\n
In earlier research, the engineer had developed advanced sensors to measure lung function with greater precision and detect respiratory restrictions. Through that project, he realized that similar techniques could be applied to analyze how people walk.<\/p>\n
\u201cMapping their leg gestures in detail could detect risk of falls, helping people like Peter stay safe while also keeping their independence at home,\u201d the expert explained.<\/p>\n
\u201cFall prevention is a huge challenge for ageing populations, so the potential to anticipate and avoid that happening with our invention is really exciting,\u201d he concluded.<\/p>\n
This new method will be tested on a larger group to evaluate how accurately it predicts falls. Researchers also plan to collaborate with clinicians and industry partners to make the product scalable.<\/p>\n
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