Humans detect tactile stimuli through a combination of pressure and vibration signals using different types of cutaneous receptor. The development of artificial tactile perception systems is of interest in the development of robotics and prosthetics, and artificial receptors, nerves and skin have been created. However, constructing systems with human-like capabilities remains challenging. Here, we report an artificial neural tactile skin system that mimics the human tactile recognition process using particle-based polymer composite sensors and a signal-converting system. The sensors respond to pressure and vibration selectively, similarly to slow adaptive and fast adaptive mechanoreceptors in human skin, and can generate sensory neuron-like output signal patterns. We show in an ex vivo test that undistorted transmission of the output signals through an afferent tactile mouse nerve fibre is possible, and in an in vivo test that the signals can stimulate a rat motor nerve to induce the contraction of a hindlimb muscle. We use our tactile sensing system to develop an artificial finger that can learn to classify fine and complex textures by integrating the sensor signals with a deep learning technique. The approach can also be used to predict unknown textures on the basis of the trained model.
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The data supporting the findings of this study are provided in the Supplementary Information. Additional relevant data are available from the corresponding author upon reasonable request.
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This study was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF grants 2020R1C1C1007589, 2018R1A6A3A01011866 and 2019M3C1B8077201), a Korea Medical Device Development Fund grant funded by the Korean government (Ministry of Science and ICT, Ministry of Trade, Industry and Energy, Ministry of Health & Welfare, Ministry of Food and Drug Safety) (NTIS no. 9991006805), the National R&D Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (2021M3H4A1A03048648 and 2021M3F3A2A01037365), the Smart Project Program through the KAIST–Khalifa Joint Research Center (KK-JRC), the KAIST College of Engineering Global Initiative Convergence Research Program and the KAIST Post-AI Research Project. This work was supported by a Korea University Grant.
The authors declare no competing interests.
Peer review information Nature Electronics thanks John Ho, Bozhi Tian and Gordon Cheng for their contribution to the peer review of this work.
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Supplementary text, Figs. 1–30 and Table 1.
Demonstration of human-like artificial neural T-skin system, which includes a T-skin device with sensor board, a neural stimulator for converting to neural signals, the stimulation system of mouse skin and normal transmission in neurons.
In vivo response test for T-skin system. A vibration with a certain frequency (1, 2, 10, 20, 100, 500 Hz) is applied to the sensor and the contraction of the hindlimb muscle of the rat is investigated.
Zip file including raw data of the experiments in spreadsheet form.
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Chun, S., Kim, JS., Yoo, Y. et al. An artificial neural tactile sensing system. Nat Electron 4, 429–438 (2021). https://doi.org/10.1038/s41928-021-00585-x