Biomimetic Mineralization-Based Smart Glasses: Achieving High-Precision Eye-Controlled Human-Computer Interaction

Biomimetic Mineralization-Based Smart Glasses: Achieving High-Precision Eye-Controlled Human-Computer InteractionA research team led by Song Yanlin and Su Meng from the Green Printing Laboratory at the Institute of Chemistry, Chinese Academy of Sciences, has achieved a significant breakthrough in the research of controllable printing of multi-dimensional and multifunctional micro-nano sensor devices. Recently, the team successfully fabricated large-grain perovskite films on a glass substrate using a biomimetic mineralization strategy

Biomimetic Mineralization-Based Smart Glasses: Achieving High-Precision Eye-Controlled Human-Computer Interaction

• A research team led by Song Yanlin and Su Meng from the Green Printing Laboratory at the Institute of Chemistry, Chinese Academy of Sciences, has achieved a significant breakthrough in the research of controllable printing of multi-dimensional and multifunctional micro-nano sensor devices. Recently, the team successfully fabricated large-grain perovskite films on a glass substrate using a biomimetic mineralization strategy. They then integrated a perovskite photoelectric detector into a smart glasses system, realizing eye-controlled human-computer interaction. This innovative research has been published in the top international journal Advanced Materials.

The team cleverly employed a biomimetic mineralization strategy, introducing a sodium polyacrylate interfacial layer to effectively passivate the defects in the perovskite film and promote the growth of high-quality perovskite films. This strategy significantly improved the performance of the perovskite photoelectric sensor. Under 500 Lux illumination, the sensor achieved a near 300-fold on/off ratio and exhibited a high photoresponsivity of 22.09 A/W. These excellent performance indicators laid a solid foundation for building a high-performance eye tracking system.

For practical application, the researchers integrated a high-performance perovskite photoelectric sensor array into wearable smart glasses. Through optimization with advanced convolutional neural network algorithms, the smart glasses can accurately identify eye movements. Experimental results show that under a test condition with an angular resolution of 5, the eye movement recognition accuracy of the smart glasses reached 99.86%. Even more impressively, the recognition accuracy for nine different eye commands reached 99.08%. This means the system can accurately interpret subtle eye movements and translate them into executable commands.

To verify the practical controllability of the system, the researchers designed a model car control experiment. The results showed that the operator could precisely control the direction and speed of the model car in complex scenarios by simply controlling their eye trajectory, fully demonstrating the system's excellent human-computer interaction capabilities. This marks significant progress in the field of eye-controlled human-computer interaction.

This research overcomes the bottlenecks of existing eye-tracking technologies. It is well known that humans obtain more than 70% of their information through vision, and the eyes, as key sensory organs for biological information acquisition, contain rich behavioral information in their movement trajectories. However, most current eye-tracking devices rely on complex sensing systems, with cumbersome image processing and large device sizes, limiting their widespread practical application. While invasive solutions based on contact lenses offer portability, they have limited measurement accuracy and may cause user discomfort.

In contrast, perovskite photoelectric sensors fabricated using the biomimetic mineralization strategy offer significant advantages in terms of cost-effectiveness, ease of operation, and high accuracy. It not only addresses many problems of existing eye-tracking technologies but also provides new possibilities for developing lighter, more comfortable, and more accurate eye-tracking devices. The system's high-precision recognition capability and good controllability open up unlimited possibilities for future smart glasses, virtual reality, and augmented reality applications. For example, it can be used to assist disabled people in operating devices, improve medical diagnostic efficiency, and enhance gaming and entertainment experiences.

The smart glasses system developed by the team, with its excellent performance and ease of operation, is expected to revolutionize the field of human-computer interaction. High-precision eye-tracking technology will empower various application scenarios, contributing to the construction of a more intelligent and user-friendly future world. This research not only represents a major scientific and technological breakthrough but also brings new hope for improving human lives and promoting social progress. It has broad application prospects in healthcare, gaming and entertainment, assistive technologies, and many other fields, warranting further in-depth research and development. Through continuous improvement and optimization, this technology is expected to be applied in more fields and ultimately benefit a wider population.

This perovskite photoelectric sensor integrated smart glasses system, based on the biomimetic mineralization strategy, not only achieves a technological breakthrough but more importantly provides a new direction for the transformation of future human-computer interaction methods. With its high precision, high efficiency, and convenience, it provides strong support for building a more natural and intuitive human-computer interaction experience, injecting new vitality into future technological development. As the technology matures, this research result is believed to have a profound impact on people's lifestyles and will make an indispensable contribution to building a more intelligent and humane future world. Its application prospects are broad and deserve continuous attention and further research. The publication of this research result undoubtedly injects new impetus into related technological research and development and industrialization processes, and provides new ideas and directions for further exploring more advanced human-computer interaction technologies. Future research directions can focus on further improving the sensitivity and stability of the sensor, as well as exploring lighter and more comfortable wearing methods to meet the needs of more users. This will drive human-computer interaction technology towards a more intelligent and humane direction, creating a better life for people.

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