Data Glove with Self-Compensation Mechanism Based on High-Sensitive Elastic Fiber-Optic Sensor

Area of Science:

• Materials Science
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Virtual reality (VR) interaction technology relies on effective human-computer interfaces.
• Data gloves are crucial for VR, necessitating sensitive and flexible sensor designs.
• Existing sensors often lack sensitivity, flexibility, or cost-effectiveness.

Purpose of the Study:

• To develop a low-cost, high-sensitivity, and flexible sensor for data gloves.
• To integrate self-compensating and self-calibration functionalities into the sensor system.
• To enhance the performance of data gloves for applications like gesture capture and motion monitoring.

Main Methods:

• Fabrication of a tunable and stretchable elastic optical fiber using an economical method.
• Integration of the optical fiber sensor in a U-shape configuration (5 mm bending radius) to maximize sensitivity.
• Incorporation of a reference optical fiber for improved system stability and accuracy.
• Customizable sensor installation for adaptability to different hand shapes.

Main Results:

• The U-shaped fiber design demonstrated up to a 7-fold increase in deformation response sensitivity compared to straight fibers.
• The elastic optical fiber exhibited excellent flexibility and stability under various deformations (stretching, bending, indentation).
• The self-calibrating sensor system showed improved accuracy and stability.
• Gesture capture tests confirmed rapid response and accurate manipulator tracking.

Conclusions:

• The proposed low-cost data glove, featuring a self-compensating elastic optical fiber sensor, offers superior sensitivity and stability.
• The design's flexibility, self-calibration, and ease of customization make it highly suitable for advanced human-computer interaction.
• This technology holds significant potential for applications in motion monitoring, telemedicine, and immersive VR experiences.