Scientists from the National University of Singapore have developed a new sensor. The sensor, which gives much better results than traditional soft materials, came first with its flexibility.
Robots that make real-time health monitoring are usually made of soft electronics. However, the use of such materials also poses various difficulties. There may be continuity problems in the performance of soft and elastic materials. This variation in durability is also known as hysteresis.
A group of scientists led by Assistant Professor Doctor Benjamin Tee from the National University of Singapore has developed a new sensor material with less hysteresis properties. This new material developed also paves the way for more accurate wearable health technologies.
High sensitivity, low hysteresis sensor
According to the news in Techxplore, soft materials encounter various hysteresis problems when used as pressure sensors. The properties of the soft sensor materials can vary between repetitive touches. Of course, this negatively affects the reliability of the data.
Scientists from the National University of Singapore have developed a material that is highly sensitive but capable of virtually hysteresis-free performance. The team developed a process to break metal thick films inside ring-shaped models in flexible material called polydimethylsiloxane (PDMS).
The researchers integrated PDMS film with electrodes and substrates for the piezoresistive sensor. He then determined the hallmarks of the sensor’s performance. Constantly developing mechanical tests, the team concluded that the design innovation they developed improved the sensor’s performance. The materials that the team called TRACE (Tactile Resistive Annulary Cracked E-Skin) yielded five times better results than traditional soft materials.
Asst. Assoc. Dr. Tee stated that the TRACE sensor can be used in robotics or wearable health technology devices to detect surface texture. The new goal of the team is to improve the suitability of the material for different wearable applications and to develop sensor-based artificial intelligence applications.