Engineers At MIT Have Created Actual Programmable Fibers

Engineers At MIT Have Created Actual Programmable Fibers
Engineers at MIT have recently announced that they have successfully developed a programmable fiber. Interesting Engineering reports: Featured in Nature Communications, this new research could result in the development of wearable tech that could sense, store, analyze, and infer the activity(s) of its wearers in real-time. The senior author of the study, Yeol Fink, believes that digital fibers like those developed in this study could help expand the possibilities for fabrics to “uncover the context of hidden patterns in the human body that could be used for physical performance monitoring, medical inference, and early disease detection.” Applications for the technology could even expand into other areas of our lives like, for example, storing wedding music within the bride’s gown.

The fibers were created by chaining hundreds of microscale silicon digital chips into a preform to make a new “smart” polymer fiber. By using precision control, the authors of the study were able to create fibers with the continuous electrical connection between each chip of tens of meters. These fibers are thin and flexible and can even be passed through the eye of a needle. This would mean they could be seamlessly (pun intended) woven into existing fabrics, and can even withstand being washed at least ten times without degrading. This would mean this wearable tech could be retrofitted to existing clothing and you wouldn’t even know it’s there. Such innovation is interesting, but it could open up doors for applications only ever dreamed of.

The fiber also has a pretty decent storage capacity too — all things considered. During the research, it was found to be possible to write, store, and recall 767-kilobit full-color short movie files and a 0.48-megabyte music file. The files can be stored for two months without power. The fibers also integrate a neural network with thousands of connections. This was used to monitor and analyze the surface body temperature of a test subject after being woven into the armpit of the shirt. By training the neural network with 270-minutes of data the team got it to predict the minute-by-minute activity of the shirt’s wearer with 96% accuracy. The fibers are also controlled using a small external device that could have microcontrollers added to it in the future.

Read more of this story at Slashdot.