UCLA researchers in the Department of Electrical Engineering developed a new grouping algorithm for touchscreen finger position detection.
Touchscreen technology plays an important role in the booming mobile devices market. Conventional touchscreens are designed with both horizontal and vertical electrodes. When these sensors are activated by touch a specific channel is activated yielding the desired functionality. However, there can be unexpected responses due to channel coupling effects and body-induced background capacitance causing an unexpected channel response and false detection and diminished finger position accuracy. This can lead to a diminished or frustrating user experience and the development of a new technology to overcome these issues would greatly improve touchscreen technology.
UCLA Prof. Mau-Chung Frank Chang and colleagues have developed a novel grouping algorithm for touchscreen finger position detection. This algorithm eliminates erroneous sensor channel response and false sensor-channel response from body-induced capacitance. While conventional technology may tolerate this input, the market trend towards higher resolution touch sensing and remote three-dimensional sensing require higher-quality sensory data with this erroneous data removed.
Can be applied to existing and future touchscreen technologies
Researchers have implemented the algorithm successfully in current touchscreen and in remote three-dimensional finger sensing technologies.
|United States Of America||Published Application||20190146609||05/16/2019||2016-520|
Additional Patent Pending
touchscreen, grouping algorithm, touchscreen sensitivity, touchscreen accuracy, three-dimensional touchscreen, remote three-dimensional sensing, finger sensing, finger detection, touchscreen finger detection, body induced background capacitance, backgroun