Textile production may be one of the oldest technologies known to humans, but it hasn't proven easy to adapt the advances of the information age to our garments. Sure, we've seen efforts like Google's Project Jacquard try to bring clothes into the modern era, but those haven't been particularly successful.
Not that that's stopping a team of researchers from the Massachusetts Institute of Technology and Sweden. They've created a smart fiber that can sense and respond to the movement of its wearer. Dubbed OmniFiber, the soft robotic fabric features a hollow center channel that allows a fluidic medium to travel through it. With the help of compressed air, the fibers can bend, stretch, curl and pulse on demand. That's something that allows them to provide tactile feedback in real-time, making them akin to an artificial muscle.
Artificial muscle fibers aren't a new idea; other research teams at MIT have approached the technology in their own way. However, what makes OmniFiber notable is that it doesn't need heat to change its shape. Immediately that makes it more practical since overheating the skin is not an issue. It has other advantages too. It's possible to make the fabric with relatively inexpensive materials, and the fibers don't require a delicate weaving process.
The team envisions their fabric making its way into garments that could help teach athletes and singers how to control their breathing better. Another even more exciting application could see an OmniFiber garment help someone recover their natural breathing pattern after a respiratory disease like COVID-19.
It may be some time before we see OmniFiber make its way into the real world, but that's not to suggest the project is done. Ozgun Kilic Afsar, one of the researchers who worked on the fabric, told MIT News she plans to continue working on the system. Among the things she wants to do is develop a manufacturing system that allows the creation of even longer filaments.
via https://AiUpNow.com October 15, 2021 at 01:33PM by Igor Bonifacic, Khareem Sudlow,
