Simultaneous Isotropic Omnidirectional Hypersensitive Strain Sensing and Deep Learning-Assisted Direction Recognition...

Area of Science:

• Materials Science
• Biomedical Engineering
• Sensor Technology

Background:

• Human tactile sense relies on omnidirectional strain sensing and direction recognition.
• Existing strain sensors primarily detect uniaxial strain, limiting applications in multiaxial environments.
• There is a need for advanced sensors capable of isotropic omnidirectional strain sensing and direction recognition for complex applications.

Purpose of the Study:

• To develop the first device with simultaneous isotropic omnidirectional hypersensitive strain sensing and direction recognition (IOHSDR) capabilities.
• To mimic human finger's tactile sensing for enhanced strain detection.
• To enable precise direction recognition for 360° stretching.

Main Methods:

• Designed a novel heterogeneous substrate incorporating the involute of a circle, mimicking 3D human fingers.
• Achieved isotropic behavior in the radial direction and anisotropic property in the involute direction for hypersensitive strain sensing.
• Utilized a deep learning-based model for strain direction recognition.

Main Results:

• The IOHSDR device achieved 99.58% accuracy in recognizing 360° stretching directions.
• Demonstrated a high gauge factor of 634.12 and an ultralow detection limit of 0.01%.
• Exhibited outstanding durability, exceeding 15,000 cycles, and proven applications in radial artery pulse and throat vibration monitoring.

Conclusions:

• The IOHSDR device offers simultaneous isotropic omnidirectional hypersensitive strain sensing and precise direction detection.
• This technology unlocks new possibilities for advanced wearable health monitoring devices.
• The sensor's performance surpasses current limitations of uniaxial strain sensors.