Using the theory of contact mechanics, a research team from the National University of Singapore (NUS) developed a new sensor material with significantly lower hysteresis. This ability enables more accurate wearable health technology and robotic recognition.
The research team, led by Assistant Professor Benjamin Tee from the NUS Institute of Health Innovation and Technology, published its results on September 28, 2020 in the prestigious Proceedings of the National Academy of Sciences.
Sensor for high sensitivity and low hysteresis pressure
When soft materials are used as pressure sensors, serious hysteresis problems usually arise. The material properties of the soft sensor can change between repeated touches, which affects the reliability of the data. This makes it difficult to get accurate readings every time, which limits the possible uses of the sensors.
The breakthrough by the NUS team is the invention of a material with high sensitivity but almost hysteresis-free performance. They developed a method to crack thin metal films on a flexible material called polydimethylsiloxane (PDMS) into desirable ring-shaped patterns.
The team integrated this metal / PDMS film with electrodes and substrates for a piezoresistive sensor and characterized its performance. They performed repeated mechanical tests and found that their design innovation improved sensor performance. Their invention, called Tactile Resistive Annularly Cracked E-Skin or TRACE, is five times better than conventional soft materials.
“With our unique design, we have been able to significantly improve accuracy and reliability. The TRACE sensor could potentially be used in robotics for surface texture sensing or in wearable health technology devices to measure, for example, blood flow in superficial arteries for health monitoring applications. “ said Asst Prof Tee, who is also from the NUS Department of Materials Science and Engineering.
The next step for the NUS team is to further improve the adaptability of the material for various wearable applications and to develop artificial intelligence (AI) applications based on the sensors.
“Our long-term goal is to predict cardiovascular health in the form of a tiny smart patch that is placed on human skin. This TRACE sensor is an advance towards that reality as the data it can capture for pulse rates is more accurate and can also be equipped with machine learning algorithms to more accurately predict surface textures. “ explained Asst Prof Tee.
Other applications that the NUS team would like to develop include applications in prosthetics, where a reliable skin interface enables a smarter response.
- Haicheng Yao, almost hysteresis-free soft tactile electronic skins for wearables and reliable machine learning, DOI: 10.1073 / pnas.2010989117
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