School of Physics, Hefei University of Technology, Hefei 230009, PR China.
School of Microelectronics, Hefei University of Technology, Hefei 230009, PR China.
Int J Biol Macromol. 2023 Mar 15;231:123568. doi: 10.1016/j.ijbiomac.2023.123568. Epub 2023 Feb 7.
Flexible sensors have attracted extensive attention in the field of human-computer interaction. However, it is still a challenging task to realize accuracy gesture recognition with flexible sensor, which requires sensor not only have high sensitivity, but also have appropriate strain detection range. Here, a high gauge factor flexible sensor (gauge factor ∼ 1296 under 12-20 % strain) based on crack structure is reported. The sensor is made of a biodegradable and stretchable gelatin composite combined with fabric bases, with good repeatability (6000 cycles) and a fast response (60 ms). Because of the double-layer structure, it has a suitable detection range (20 % strain). The sensor is manufactured by a screen-printing process, and it has been used to make data gloves and has realized 9 gestures recognition with machine learning algorithm (99.6 % accuracy). In general, this study offers a wearable gestures recognition scheme through the proposed sensor.
柔性传感器在人机交互领域引起了广泛关注。然而,实现具有高精度的柔性传感器的手势识别仍然是一项具有挑战性的任务,这要求传感器不仅具有高灵敏度,而且还具有适当的应变检测范围。在这里,报道了一种基于裂纹结构的高灵敏柔性传感器(在 12-20%应变下的灵敏系数约为 1296)。该传感器由可生物降解和可拉伸的明胶复合材料与织物基底组成,具有良好的重复性(6000 次循环)和快速响应(60 毫秒)。由于采用双层结构,它具有合适的检测范围(20%应变)。该传感器采用丝网印刷工艺制造,已用于制作数据手套,并通过机器学习算法实现了 9 种手势识别(准确率为 99.6%)。总的来说,这项研究通过提出的传感器提供了一种可穿戴的手势识别方案。