The Slinky-like sensor, say the researchers, is both ultra-sensitive and resilient, and designed to survive the rigors of real-world use.

“Current soft strain gauges are really sensitive but also really fragile,” says Oluwaseun Araromi, a Research Associate in Materials Science and Mechanical Engineering at SEAS and the Wyss Institute and first author of a paper on the research. “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.”

Toward that end, the researchers created a design that looks and behaves very much like a Slinky – the popular precompressed helical spring toy invented in the early 1940s.

“A Slinky is a solid cylinder of rigid metal but if you pattern it into this spiral shape, it becomes stretchable,” says Araromi. “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, say the researchers, is known as a “serpentine meander,” because its sharp ups and downs resemble the slithering of a snake. The patterned conductive carbon fibers are then sandwiched between two prestrained 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 – similar to the way the individual spirals of a Slinky come out of contact with each other when both ends are pulled. This process happens even with small amounts of strain, which is the key to the sensor’s high sensitivity.

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 or even a clean room, say the researchers. It could be made using any conductive material.

To test the resiliency of the sensor, the researchers tried 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. The sensor emerged from each test unscathed.

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.

“These features of resilience and the mechanical robustness,” says Araromi, “put this sensor in a whole new camp.”

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

“The combination of high sensitivity and resilience are clear benefits of this type of sensor,” says Robert Wood, the Charles River Professor of Engineering and Applied Sciences at SEAS and senior author of the study. “But another aspect that differentiates this technology is the low cost of the constituent materials and assembly methods. This will hopefully reduce the barriers to get this technology widespread in smart textiles and beyond.”

The researchers say they are currently exploring how the sensor can be integrated into apparel due to the intimate interface to the human body it provides, and that they envision exciting new applications by being able to make biomechanical and physiological measurements throughout a person’s day, not possible with current approaches.

For more, see “Ultra-sensitive and resilient compliant strain gauges for soft machines.”

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