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

Area of Science:

• Materials Science
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Traditional human-machine interfaces (HMIs) lack 3D interaction capabilities and multi-scene accuracy.
• Single-perception interfaces limit the convenience and precision of user interaction.

Purpose of the Study:

• To develop a collaborative interface integrating electrooculography (EOG) and tactile perception for fast, accurate 3D human-machine interaction.
• To enable contactless 2D control via EOG and complex 2D/3D control using tactile sensing.

Main Methods:

• Fabrication of honeycomb graphene electrodes for EOG and tactile sensing using a laser-induced process.
• Utilized two pairs of electrodes around the eyes for nine eye movement detections, classified by a machine learning algorithm (92.6% accuracy).
• Developed an ultrathin, stretchable tactile sensing interface (90 μm, ~1000% stretchability) with a 4x4 planar electrode array for arm-based 2D/3D control.

Main Results:

• Achieved 92.6% average prediction accuracy for nine distinct eye movements using EOG.
• The tactile sensor demonstrated single-point, multipoint, sliding touch, eight-direction control, and complex trajectory control.
• Exhibited ultrahigh sensitivity (1.428 kPa⁻¹) within 0-300 Pa, with excellent long-term stability and repeatability.

Conclusions:

• The synergistic combination of EOG and tactile perception significantly enhances 3D human-machine interaction speed and accuracy.
• The developed graphene-based sensors offer advanced performance characteristics for next-generation interactive systems.
• This collaborative interface holds substantial potential for diverse applications requiring intuitive and precise user control.