Underwater Pressure Sensors, Next Big Things in Wearable Electronics

Scientists in South Korea successfully developed a hand-drawn and flexible pressure sensor that can control mobile devices from underwater.

FREMONT, CA: Scientists in South Korea have successfully developed a flexible and waterproof sensor that could unlock contemporary applications for wearable devices. The study published in the journal Science and Technology of Advanced Materials shows how a pressure sensor can be employed to control a phone to take pictures and play music when the sensor is entirely underwater. The technology is expected to transform wearable electronic devices in smart textiles, health care, and other specific application domains, such as diving equipment. The researchers who developed the technology are based at the Soongsil University of Seoul.

Within am to develop flexible electronics that will Usher a new era of wearable technology is to monitor health and improve lifestyle, the researchers developed the pressure sensor that engineers could rely upon for underwater applications. To demonstrate the capabilities of the new technology, the researchers incorporated one of the senses into a facial mask. Since the sensor is sensitive enough to detect air movement inside the mask, it could efficiently track and report the rate of breathing of a person in real-time. The tiny movements caused by changes in pressure and electrical resistances are converted into electronic signals. Like other electronic devices, the design of the circuit was hand-drawn onto a conducting material using a marker pen which functions to shield the circuitry when the rest of the material was etched away. The researchers followed this method since it was cheaper than traditional alternatives. A fingerprint-sized circuit was then mounted onto a blend of wet tissue paper and carbon nanotubes which functioned as pressure detectors. The scientists then covered the layer sensor device with tape, making it waterproof.

Due to its circuitry, the device is capable of tracking both the magnitude and location and pressure applied to it. The researchers then employed machine learning technologies to process the signal and found out that census good feel and report applied pressure in the lab with an accuracy of 94%. By connecting the sensor to a Wi-Fi network, the scientists could present underwater how to control the functions in a cell phone, including double taps, long touch patterns, and short touches. The machine learning algorithm, readily available fabrication material, and easy contemporary techniques that are very well demonstrated in the journal are expected to contribute significantly to the development of hand-drawn sensors in the global semiconductor industry.