Researchers have created a fiber with digital capabilities that is able to sense, store, analyze, and infer activity after being sewn into a shirt. Digital fabrics uncover the context of hidden patterns in the human body that could be used for physical performance monitoring, medical inference, and early disease detection.
Until now, electronic fibers have been analog — carrying a continuous electrical signal — rather than digital, where discrete bits of information can be encoded and processed in 0s and 1s. The new fabric stores and processes data digitally, adding a new information content dimension to textiles and allowing fabrics to be programmed.
The new fiber was created by placing hundreds of square silicon microscale digital chips into a preform that was then used to create a polymer fiber. By precisely controlling the polymer flow, the researchers were able to create a fiber with continuous electrical connection between the chips over a length of tens of meters. The fiber itself is thin and flexible and can be passed through a needle, sewn into fabrics, and washed at least 10 times without breaking down.
A digital fiber offers a way to control individual elements within a fiber, from one point at the fiber’s end. The researchers devised a digital addressing method that allows them to “switch on” the functionality of one element without turning on all the elements.
A digital fiber can also store a lot of information in memory. The researchers were able to write, store, and read information on the fiber including a 767-kilobit full-color short movie file and a 0.48-megabyte music file. The files can be stored for two months without power.
The fiber also takes a few steps forward into artificial intelligence by including, within the fiber memory, a neural network of 1,650 connections. After sewing it around the armpit of a shirt, the researchers used the fiber to collect 270 minutes of surface body temperature data from a person wearing the shirt and analyzed how these data corresponded to different physical activities. Trained on these data, the fiber was able to determine with 96 percent accuracy what activity the person wearing it was engaged in.
Adding an AI component to the fiber further increases its possibilities. Fabrics with digital components can collect information across the body over time, and these lush data are perfect for machine learning algorithms. This type of fabric could give quantity and quality open-source data for extracting out new body patterns.
With this analytic power, the fibers someday could sense and alert people in real time to health changes like a respiratory decline or an irregular heartbeat, or deliver muscle activation or heart rate data to athletes during training. The fiber is controlled by a small external device, so the next step will be to design a new chip as a microcontroller that can be connected within the fiber itself.
For more information, contact Abby Abazorius at