Supramolecular Wood-Based Human–Computer Interaction Interface for Text Recognition
Source abstract
Abstract
Text recognition is a cornerstone of human-computer interaction (HCI), yet conventional isotropic sensing interfaces are intrinsically constrained in resolving the complex directional features of handwriting, particularly the intricate stroke orientations of Chinese characters. Here, leveraging the intrinsic anisotropic architecture of natural wood, we developed a mechanically robust, highly stretchable, and sensitive hydrogel-based interface capable of accurately distinguishing diverse handwriting trajectories. The resulting wood-based soft hydrogel used for human-computer interaction (WSH-HCI) achieves 25 MPa tensile strength along the fiber axis─6.5× higher than in the transverse direction─while maintaining stable multidirectional signal discrimination and up to 96% accuracy in Chinese basic-stroke recognition. These performances arise from preserved aligned cellulose nanofiber channels and a strong PVA-cellulose hydrogen-bonding network. Demonstrations include real-time recognition of English letters and Chinese characters. This work provides a viable pathway toward high-performance anisotropic hydrogel sensors for advanced handwriting recognition and intelligent human-computer interactions.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Interactive and Immersive Displays · Handwritten Text Recognition Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Research Institute of Wood Industry
Chinese Academy of Forestry
College of Materials Science and Engineering
Nanjing Forestry University
Funding
Yunnan Provincial Academician Workstation · National Natural Science Foundation of China (NSFC)
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