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September 10, 2025SensorsOpen Access

A Smart Textile-Based Tactile Sensing System for Multi-Channel Sign Language Recognition

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The system demonstrates a classification accuracy of 94.66% in recognizing American Sign Language gestures.
Tactile sensing captures subtle wrist and finger motions, overcoming limitations of traditional vision-based methods.
The design utilizes triboelectric yarns, enabling operation independent of lighting conditions and occlusions.
Experimental validation shows effective recognition of complex gestures, enhancing applications in human-computer interaction.

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Implication

Wearable tactile sensing system achieves 94.66% accuracy in recognizing American Sign Language gestures, indicating its potential in communication aids.

Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/68c1afb954b1d3bfb60e7172 https://doi.org/10.3390/s25154602

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Implication

Wearable tactile sensing system achieves 94.66% accuracy in recognizing American Sign Language gestures, indicating its potential in communication aids.

A Smart Textile-Based Tactile Sensing System for Multi-Channel Sign Language Recognition

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Discussion

Implication

Cite This Study

A Smart Textile-Based Tactile Sensing System for Multi-Channel Sign Language Recognition

Key Points

Discussion

Implication

Cite This Study

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