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Supramolecular Wood-Based Human-Computer Interaction Interface for Text Recognition.

Yuting Jiang1, Yongyue Zhang2, Zongying Fu1

  • 1Research Institute of Wood Industry, Chinese Academy of Forestry, Beijing 100091, China.

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|February 19, 2026
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Summary
This summary is machine-generated.

Researchers developed a wood-based hydrogel sensor that accurately recognizes handwriting, including complex Chinese characters. This breakthrough enhances human-computer interaction (HCI) with robust, stretchable, and sensitive anisotropic sensors.

Keywords:
anisotropic sensinghigh-performance sensorshuman−computer interactiontext recognitionwood-based hydrogel

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Area of Science:

  • Materials Science
  • Biomaterials Engineering
  • Human-Computer Interaction

Background:

  • Conventional isotropic sensing interfaces struggle with complex directional features in handwriting, especially Chinese characters.
  • Anisotropic materials offer potential for improved directional sensing capabilities.

Purpose of the Study:

  • To develop a mechanically robust, stretchable, and sensitive hydrogel interface for accurate handwriting recognition.
  • To leverage the anisotropic properties of natural wood for advanced human-computer interaction (HCI) applications.

Main Methods:

  • Utilized the intrinsic anisotropic architecture of natural wood to create a wood-based soft hydrogel (WSH-HCI).
  • Incorporated aligned cellulose nanofiber channels and a PVA-cellulose hydrogen-bonding network.
  • Tested tensile strength, multidirectional signal discrimination, and handwriting recognition accuracy.

Main Results:

  • The WSH-HCI exhibited a tensile strength of 25 MPa along the fiber axis (6.5× higher than transverse).
  • Achieved stable multidirectional signal discrimination and up to 96% accuracy in Chinese basic-stroke recognition.
  • Successfully demonstrated real-time recognition of English letters and Chinese characters.

Conclusions:

  • The developed wood-based anisotropic hydrogel sensor offers a viable pathway for high-performance handwriting recognition.
  • This technology advances intelligent human-computer interaction through improved sensor capabilities.
  • Preserved aligned cellulose nanofiber channels and hydrogen bonding are key to the sensor's performance.