Human–Machine Interaction

Frequency-encoded eye tracking smart contact lens for human–machine interaction

Eye tracking techniques enable high-efficient, natural, and effortless human-machine interaction by detecting users’ eye movements and decoding their attention and intentions. Here, a miniature, imperceptible, and biocompatible smart contact lens is proposed for in situ eye tracking and wireless eye-machine interaction.

Employing the frequency encoding strategy, the chip-free and battery-free lens successes in detecting eye movement and closure. Using a time-sequential eye tracking algorithm, the lens has a great angular accuracy of <0.5°, which is even less than the vision range of central fovea. Multiple eye-machine interaction applications, such as eye-drawing, Gluttonous Snake game, web interaction, pan-tilt-zoom camera control, and robot vehicle control, are demonstrated on the eye movement model and in vivo rabbit.

Furthermore, comprehensive biocompatibility tests are implemented, demonstrating low cytotoxicity and low eye irritation. Thus, the contact lens is expected to enrich approaches of eye tracking techniques and promote the development of human-machine interaction technology.

Design and characterization of the eye-tracking SCL

Demonstrates the wide application potential of the proposed eye tracking SCL. By detecting the gazing direction, the SCL can calculate the real-time gazing point on the virtual screen, enabling the interaction with software, such as giving a like when appreciating Vincent van Gogh’s famous artwork The Starry Night. Robots also can be eye-controlled through the user-defined eye command input and execute multiple missions like vehicle movement and camera rotation.

With miniaturization and portability, the eye tracking system can be used in daily life and bring negligible burden to the user. 4 RF tags, integrated at the peripheral region of SCL, provided the backscattering signal for eye motion detection. The coil-shaped RF tags had different resonant frequency due to well-designed distinct structural parameters based on the mechanism of resistance-inductance-capacitance (RLC) resonator. The return loss (S11) curve, measured by a vector network analyzer (VNA) through a reading coil, provided insights into the response of the tags through wireless detection. The recognition of eye movement and closure was enabled by it. The equivalent impedance at the terminals of the reading coil is as follow.

human–machine interaction, user experience, artificial intelligence, machine learning, robotics, natural language processing, human-centered design, wearable technology, cognitive ergonomics, user interface, virtual reality, augmented reality, haptic feedback, automation, adaptive systems, brain–computer interface, multimodal interaction, intelligent agents, usability testing, human factors

#HumanMachineInteraction, #UXDesign, #ArtificialIntelligence, #MachineLearning, #Robotics, #NaturalLanguageProcessing, #HCI, #WearableTech, #UserInterface, #VirtualReality, #AugmentedReality, #HapticFeedback, #Automation, #AdaptiveSystems, #BrainComputerInterface, #MultimodalInteraction, #IntelligentSystems, #Usability, #HumanCenteredDesign, #CognitiveErgonomics

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