Xu Jiandong, Li Xiaoshi, Chang Hao, Zhao Bingchen, Tan Xichao, Yang Yi, Tian He, Zhang Sheng, Ren Tian-Ling
School of Integrated Circuits, Tsinghua University, Beijing 100084, China.
Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
ACS Nano. 2022 Apr 26;16(4):6687-6699. doi: 10.1021/acsnano.2c01310. Epub 2022 Apr 6.
The human-machine interface (HMI) previously relied on a single perception interface that cannot realize three-dimensional (3D) interaction and convenient and accurate interaction in multiple scenes. Here, we propose a collaborative interface including electrooculography (EOG) and tactile perception for fast and accurate 3D human-machine interaction. The EOG signals are mainly used for fast, convenient, and contactless 2D (-axis) interaction, and the tactile sensing interface is mainly utilized for complex 2D movement control and -axis control in the 3D interaction. The honeycomb graphene electrodes for the EOG signal acquisition and tactile sensing array are prepared by a laser-induced process. Two pairs of ultrathin and breathable honeycomb graphene electrodes are attached around the eyes for monitoring nine different eye movements. A machine learning algorithm is designed to train and classify the nine different eye movements with an average prediction accuracy of 92.6%. Furthermore, an ultrathin (90 μm), stretchable (∼1000%), and flexible tactile sensing interface assembled by a pair of 4 × 4 planar electrode arrays is attached to the arm for 2D movement control and -axis interaction, which can realize single-point, multipoint and sliding touch functions. Consequently, the tactile sensing interface can achieve eight directions control and even more complex movement trajectory control. Meanwhile, the flexible and ultrathin tactile sensor exhibits an ultrahigh sensitivity of 1.428 kPa in the pressure range 0-300 Pa with long-term response stability and repeatability. Therefore, the collaboration between EOG and the tactile perception interface will play an important role in rapid and accurate 3D human-machine interaction.
人机界面(HMI)以前依赖于单一的感知界面,无法在多个场景中实现三维(3D)交互以及便捷、准确的交互。在此,我们提出一种包括眼电图(EOG)和触觉感知的协作界面,用于快速、准确的3D人机交互。EOG信号主要用于快速、便捷的非接触式二维(-轴)交互,而触觉传感界面主要用于3D交互中的复杂二维运动控制和-轴控制。用于EOG信号采集和触觉传感阵列的蜂窝状石墨烯电极通过激光诱导工艺制备。两对超薄透气的蜂窝状石墨烯电极附着在眼睛周围,用于监测九种不同的眼球运动。设计了一种机器学习算法来训练和分类这九种不同的眼球运动,平均预测准确率为92.6%。此外,由一对4×4平面电极阵列组装而成的超薄(90μm)、可拉伸(约1000%)且灵活的触觉传感界面附着在手臂上,用于二维运动控制和-轴交互,可实现单点、多点和滑动触摸功能。因此,触觉传感界面可实现八个方向的控制,甚至更复杂的运动轨迹控制。同时,这种灵活超薄的触觉传感器在0-300Pa的压力范围内表现出1.428kPa的超高灵敏度,具有长期响应稳定性和可重复性。因此,EOG与触觉感知界面之间的协作将在快速、准确的3D人机交互中发挥重要作用。