Textile embedded strain sensor makes it through the wash

The research is published in Nature. In the paper the team said the sleeve demonstration 'shows the potential of the strain-mediated contact in anisotropically resistive structures (SCARS) technology for the development of unobtrusive, wearable biomechanical feedback systems and human–computer interfaces.'

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"Current soft strain gauges are really sensitive but also really fragile," said Oluwaseun Araromi, a Research Associate in Materials Science and Mechanical Engineering at SEAS (John A. Paulson School of Engineering and Applied Sciences) and the Wyss Institute and first author of the paper. "The problem is that we're working in an oxymoronic paradigm - highly sensitivity sensors are usually very fragile and very strong sensors aren't usually very sensitive. So, we needed to find mechanisms that could give us enough of each property."

In the end, the researchers created a design likened to a Slinky.

"A Slinky is a solid cylinder of rigid metal but if you pattern it into this spiral shape, it becomes stretchable," Araromi said in a statement. "That is essentially what we did here. We started with a rigid bulk material, in this case carbon fibre, and patterned it in such a way that the material becomes stretchable."

The pattern is called a serpentine meander due to its resemblance to a slithering snake. The patterned conductive carbon fibres are then sandwiched between two pre-strained elastic substrates.

The overall electrical conductivity of the sensor changes as the edges of the patterned carbon fibre come out of contact with each other, a process that occurs with small amounts of strain, which the team said is the key to the sensor's high sensitivity.

The team added that unlike current highly sensitive stretchable sensors, which rely on materials such as silicon or gold nanowires, this sensor does not require special manufacturing techniques or a clean room. Furthermore, it could be made using any conductive material.

The researchers successfully tested the resiliency of the sensor by stabbing it with a scalpel, hitting it with a hammer, running it over with a car, and putting it through a machine wash ten times.

To demonstrate its sensitivity, the researchers embedded the strain 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 classify these gestures.

"These features of resilience and the mechanical robustness put this sensor in a whole new camp," said Araromi.

Such a sleeve could be used in everything from virtual reality simulations and sportswear to clinical diagnostics for neurodegenerative diseases like Parkinson's Disease.

"We are currently exploring how this sensor can be integrated into apparel due to the intimate interface to the human body it provides," said Conor Walsh, the Paul A. Maeder Professor of Engineering and Applied Sciences at SEAS and co-author of the study. "This will enable exciting new applications by being able to make biomechanical and physiological measurements throughout a person's day, not possible with current approaches."