Hysteresis-free performance for soft sensor material
Guided by the theory of contact mechanics, researchers from the National University of Singapore (NUS) have invented a material that should enable more accurate wearable health technology and robotic sensing. The team have described their breakthrough in the journal Proceedings of the National Academy of Sciences.
Real-time health monitoring and sensing abilities of robots require soft electronics, but a challenge of using such materials lies in their reliability. Unlike rigid devices, being elastic and pliable makes their performance less repeatable; this variation in reliability is known as hysteresis. A soft sensor’s material properties can change in between repeated touches, affecting the reliability of the data. This makes it challenging to get accurate readouts every time, limiting the sensor’s possible applications.
The NUS team invented a material with high sensitivity but an almost hysteresis-free performance, developing a process to crack metal thin films into desirable ring-shaped patterns on a flexible material called polydimethylsiloxane (PDMS). The team integrated this metal/PDMS film with electrodes and substrates for a piezoresistive sensor and characterised its performance.
Repeated mechanical testing confirmed that the team’s design innovation improved sensor performance. Their material, named Tactile Resistive Annularly Cracked E-Skin (TRACE), is in fact claimed to be five times better than conventional soft materials.
“With our unique design, we were able to achieve significantly improved accuracy and reliability,” said research leader Assistant Professor Benjamin Tee. “The TRACE sensor could potentially be used in robotics to perceive surface texture or in wearable health technology devices; for example, to measure blood flow in superficial arteries for health monitoring applications.”
The next step for the team is to further improve the conformability of their material for different wearable applications and to develop artificial intelligence (AI) applications based on the sensors. They also aim to develop the material for use in prosthetics, where having a reliable skin interface allows for a more intelligent response.
“Our long-term goal is to predict cardiovascular health in the form of a tiny smart patch that is placed on human skin,” said Asst Prof Tee. “This TRACE sensor is a step forward towards that reality because the data it can capture for pulse velocities is more accurate, and can also be equipped with machine learning algorithms to predict surface textures more accurately.”
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