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Electrooculography and Tactile Perception Collaborative Interface for 3D Human-Machine Interaction

delete2022-04-06
delete77
PRE
AI
J
Jiandong Xu
X
Xiaoshi Li
常皓 (Hao Chang)
B
Bingchen Zhao
X
Xichao Tan
Y
Yi Yang
田禾 (He Tian) *
张盛 (Sheng Zhang) *
T
Tian‐Ling Ren *
DOI:10.1021/acsnano.2c01310delete
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Abstract

Abstract

En 中文
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 (XY-axis) interaction, and the tactile sensing interface is mainly utilized for complex 2D movement control and Z-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 mu m), stretchable (similar to 1000%), and flexible tactile sensing interface assembled by a pair of 4 x 4 planar electrode arrays is attached to the arm for 2D movement control and Z-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(-1) 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.
Keywords:
honeycomb graphene
EOG
tactile sensor
laser induction
human-machine interaction

Journal

ACS Nano cover
ACS Nano
IF:
16
Papers:
2.6W
Citations:
25.6W

Organization

T
tsinghua university
Scholars:
11.8W
Papers: 10.0W
Citations: 137