Structure‐Dependent Resonant Frequency Engineering of Textile Tactile Sensors Toward Rapid and Precise Braille Recognition Surpassing Human Sensation

A resonant frequency engineering strategy is proposed to modulate the sensibility of piezoresistive textile‐based tactile sensor. It achieves simultaneous detection of static pressure and dynamic vibrations across an unprecedented bandwidth of 5–600 Hz, surpassing human sensation, therefore enables rapid and precise braille recognition. An instantaneous braille‐to‐audio conversion system is further built as learning aid for visually impaired individuals. ABSTRACT Artificial tactile perception emulating slow‐(SA) and fast‐adapting (FA) mechanoreceptors is crucial for visually impaired individuals as an advanced auxiliary learning electronic system. However, existing sensors, particularly single‐mode ones, struggle to simultaneously detect static pressure and high‐frequency vibrations due to their inherent response limitations. Herein, for the first time, we report a textile‐based bionic tactile sensor (TBTS) that, solely via piezoresistive mechanism, achieves high sensitivity and fast response across an ultrabroad frequency range (5–600 Hz), surpassing human vibrotactile range (<500 Hz). Finite element analysis (FEA) reveals that such superior capability originates from the resonant frequency engineering of 3D woven structure in sensing fabric. Under the assist of machine learning, an instantaneous braille‐to‐audio conversion system comprising a TBTS‐integrated commercial glove, signal processer and a smartphone interface is built, realizing rapid and precise braille recognition with an operational frequency significantly higher than skilled human reading speeds (5–10 Hz), achieving 100.0% accuracy for characters and 97.5% for Chinese multi‐character sentences, and enabling real‐time audio feedback. This work establishes a new paradigm for assistive technology, paving the way for next‐generation smart wearables that offer immediate aids in braille education and navigation. A resonant frequency engineering strategy is proposed to modulate the sensibility of piezoresistive textile-based tactile sensor. It achieves simultaneous detection of static pressure and dynamic vibrations across an unprecedented bandwidth of 5–600 Hz, surpassing human sensation, therefore enables rapid and precise braille recognition. An instantaneous braille-to-audio conversion system is further built as learning aid for visually impaired individuals. ABSTRACT Artificial tactile perception emulating slow-(SA) and fast-adapting (FA) mechanoreceptors is crucial for visually impaired individuals as an advanced auxiliary learning electronic system. However, existing sensors, particularly single-mode ones, struggle to simultaneously detect static pressure and high-frequency vibrations due to their inherent response limitations. Herein, for the first time, we report a textile-based bionic tactile sensor (TBTS) that, solely via piezoresistive mechanism, achieves high sensitivity and fast response across an ultrabroad frequency range (5–600 Hz), surpassing human vibrotactile range (<500 Hz). Finite element analysis (FEA) reveals that such superior capability originates from the resonant frequency engineering of 3D woven structure in sensing fabric. Under the assist of machine learning, an instantaneous braille-to-audio conversion system comprising a TBTS-integrated commercial glove, signal processer and a smartphone interface is built, realizing rapid and precise braille recognition with an operational frequency significantly higher than skilled human reading speeds (5–10 Hz), achieving 100.0% accuracy for characters and 97.5% for Chinese multi-character sentences, and enabling real-time audio feedback. This work establishes a new paradigm for assistive technology, paving the way for next-generation smart wearables that offer immediate aids in braille education and navigation. Advanced Science, EarlyView.