Ultra-sensitive sensors are usually very fragile and resilient sensors aren't usually sensitive. Recently, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and the Wyss Institute for Biologically Inspired Engineering have developed an ultra-sensitive and resilient strain sensor that can be embedded in textiles and washed by water. It can be used in sportswear to clinical diagnostics for neurodegenerative diseases like Parkinson's Disease.
The research is published in Nature.
Similar Design as Slinky
The researchers created a design that looks and behaves very much like a Slinky. "A Slinky is a solid cylinder of rigid metal but if you pattern it into this spiral shape, it becomes stretchable," said Araromi, the author of the paper. "That is essentially what we did here. We started with a rigid bulk material, in this case carbon fiber, and patterned it in such a way that the material becomes stretchable. "
The pattern is known as a serpentine meander, because its ups and downs resemble the slithering of a snake. The patterned conductive carbon fibers are then sandwiched between two pre-strained elastic substrates.
The overall electrical conductivity of the sensor changes as the edges of the patterned carbon fiber come out of contact with each other. This process happens even with small amounts of strain, which is the key to the high sensitivity of sensor.
Unlike current highly sensitive stretchable sensors, which rely on exotic materials such as silicon or gold nanowires, this sensor doesn't require special manufacturing techniques. It could be made using any conductive material.
The researchers tested the resiliency of the sensor by stabbing it with a scalpel, hitting it with a hammer, running it over with a car, and throwing it in a washing machine ten times.
High Sensitivity Demonstration
To demonstrate its sensitivity, the researchers embedded the sensor in a fabric arm sleeve and asked a participant to make different gestures with their hand, including a fist, open palm, and pinching motion. The sensors detected the small changes in the subject's forearm muscle through the fabric and a machine learning algorithm was able to successfully classify these gestures.
Graduate students from SEAS demonstrated a fabric arm cover with embedded sensors. Sensors detect subtle changes in forearm muscles that pass through the fabric. This sleeve could be used in everything from virtual reality simulations and sportswear to clinical diagnostics for neurodegenerative diseases like Parkinson's Disease.