講演情報
[7p-P04-22]Spider Web-Inspired Pressure Sensor Array
〇Ketong Gao1, Haruki Nakamura1, Yan Xuan1, Atsushi Nitta1, Kuniharu Takei1 (1.Hokkaido Univ.)
キーワード：
sensor、machine learning
Flexible and stretchable pressure sensors are attractive attention in human-machine interaction to perceive touch signals and enable command input on a variety of objects including non-planar and soft surfaces. In fact, stretchable pressure sensors have been widely studied by developing stretchable film and sensor materials. However, even if stretchable material is used for a film, softness is often limited to conformably cover a non-planar and soft object. Furthermore, to detect high resolution pressure mapping, the number of electrodes drastically increase, resulting in that the sensor is complicated. To address these challenges, this study propose a spider web-inspired pressure sensor design and pressure mapping powered by machine learning.