Inspired by human skin, bionic tactile sensing is effectively promoting development and innovation in many fields with its flexible and efficient perception capabilities. Optical fiber, with its ability to perceive and transmit information and its flexible characteristics, is considered a promising solution in the field of tactile bionics. In this work, one optical fiber tactile sensing system based on a flexible PDMS-embedded optical fiber ring resonator (FRR) is designed for braille recognition, and the Pound-Drever-Hall (PDH) demodulation scheme is adopted to improve the detection sensitivity. Theoretical simulations and experimental verifications show that by adopting a bionic sliding approach and a Multilayer Perceptron Neural Network, a single FRR with a hardness gradient design can detect eight different tactile pressures in braille characters with an accuracy of 98.57%. Furthermore, after training and testing, the MLP-LSTM model classifies time series signals, thereby achieving completely accurate encoding of braille keywords and braille poems. The advantages of the optical fiber tactile sensing system in this study are that the high-quality factor FRR can detect subtle differences in braille dots, it is not affected by changes in optical power due to its relies on PDH frequency demodulation, and the application of machine learning algorithms can enhance the robustness to slight pressure errors and simplify the recognition process. This solution opens up what we believe is a new optical approach for bionic tactile perception and has important potential value in promoting human-computer interaction, smart medical care, and other fields.
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