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A Tongue-Computer Tactile Interface Mediated by the Magnetoelectric-Driven Tribovoltaic Sensors.

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Τίτλος: A Tongue-Computer Tactile Interface Mediated by the Magnetoelectric-Driven Tribovoltaic Sensors.
Συγγραφείς: Zhao J; Beijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.; School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, P. R. China., Tang C; Beijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.; School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, P. R. China., Zhou M; Beijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.; School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, P. R. China., Yu D; College of Engineering, China Agricultural University, Beijing, P. R. China., Chen M; Beijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China., Wang S; Beijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China., Hu Q; Beijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China., Jiang Z; Beijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.; School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, P. R. China., Wang ZL; Beijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.; School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, P. R. China., Pu X; Beijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.; School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, P. R. China., Li L; Beijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, P. R. China.; School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, P. R. China.
Πηγή: Advanced materials (Deerfield Beach, Fla.) [Adv Mater] 2026 Mar; Vol. 38 (14), pp. e22639. Date of Electronic Publication: 2026 Feb 05.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Wiley-VCH Country of Publication: Germany NLM ID: 9885358 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1521-4095 (Electronic) Linking ISSN: 09359648 NLM ISO Abbreviation: Adv Mater Subsets: MEDLINE
Imprint Name(s): Publication: Sept. 3, 1997- : Weinheim : Wiley-VCH
Original Publication: Deerfield Beach, FL : VCH Publishers, 1989-
Ιατρικοί όροι (MeSH): Tongue*/physiology , Touch* , User-Computer Interface*, Humans ; Neural Networks, Computer ; Long Short Term Memory ; Soft Computing
Περίληψη: Current human-computer interaction (HCI) technologies often suffer from wearing discomfort, noise sensitivity, user fatigue, and privacy concerns, particularly for users with physical disabilities or those requiring high-precision control. In this study, we address the aforementioned challenges by designing an interactive tongue-computer interface (ITCI) that enables precise, hands-free interaction through subtle tongue movements. The ITCI utilizes an array of direct current tribovoltaic tactile sensors enhanced by the magnetoelectric effect, achieving a peak current density of 10.72 A m-2, a charge density of 718 mC m-2, and a sensitivity of 90 µA N-1. integration with a bidirectional long short-term memory (BiLSTM) neural network yields a recognition accuracy of 99.98%, supporting diverse interactive applications, including smart wheelchair control, robotic manipulation, and immersive gaming. This self-powered, noninvasive interface enhances user autonomy and privacy, offering a robust platform for intelligent, energy-efficient, and hands-free human-machine interaction.
(© 2026 Wiley‐VCH GmbH.)
References: S. N. Flesher, J. E. Downey, J. M. Weiss, et al., “A Brain‐Computer Interface That Evokes Tactile Sensations Improves Robotic Arm Control,” Science 372 (2021): 831–836, https://doi.org/10.1126/science.abd0380.
T. Reid and J. Gibert, “Inclusion in Human–Machine Interactions,” Science 375 (2022): 149–150, https://doi.org/10.1126/science.abf2618.
M. Wairagkar, N. S. Card, T. Singer‐Clark, et al., “An Instantaneous Voice‐Synthesis Neuroprosthesis,” Nature 644 (2025): 145–152, https://doi.org/10.1038/s41586‐025‐09127‐3.
P. Slade, C. Atkeson, J. M. Donelan, et al., “On Human‐in‐the‐Loop Optimization of Human–Robot Interaction,” Nature 633 (2024): 779–788, https://doi.org/10.1038/s41586‐024‐07697‐2.
K. Yao, Q. Zhuang, Q. Zhang, et al., “A Fully Integrated Breathable Haptic Textile,” Science Advances 10 (2024): adq9575, https://doi.org/10.1126/sciadv.adq9575.
Y. Luo, C. Liu, Y. J. Lee, et al., “Adaptive Tactile Interaction Transfer via Digitally Embroidered Smart Gloves,” Nature Communications 15 (2024): 868, https://doi.org/10.1038/s41467‐024‐45059‐8.
J. Cao, X. Liu, J. Qiu, et al., “Anti‐Friction Gold‐Based Stretchable Electronics Enabled by Interfacial Diffusion‐Induced Cohesion,” Nature Communications 15 (2024): 1116, https://doi.org/10.1038/s41467‐024‐45393‐x.
J. P. Lee, H. Jang, Y. Jang, et al., “Encoding of Multi‐Modal Emotional Information via Personalized Skin‐Integrated Wireless Facial Interface,” Nature Communications 15 (2024): 530, https://doi.org/10.1038/s41467‐023‐44673‐2.
Y. Liu, S. Jia, C. K. Yiu, et al., “Intelligent Wearable Olfactory Interface for Latency‐Free Mixed Reality and Fast Olfactory Enhancement,” Nature Communications 15 (2024): 4474, https://doi.org/10.1038/s41467‐024‐48884‐z.
O. A. Araromi, M. A. Graule, K. L. Dorsey, et al., “Ultra‐Sensitive and Resilient Compliant Strain Gauges for Soft Machines,” Nature 587 (2020): 219–224, https://doi.org/10.1038/s41586‐020‐2892‐6.
P. Jin, J. Zou, T. Zhou, and N. Ding, “Eye Activity Tracks Task‐Relevant Structures During Speech and Auditory Sequence Perception,” Nature Communications 9 (2018): 5374, https://doi.org/10.1038/s41467‐018‐07773‐y.
F. R. Willett, D. T. Avansino, L. R. Hochberg, J. M. Henderson, and K. V. Shenoy, “High‐Performance Brain‐to‐Text Communication via Handwriting,” Nature 593 (2021): 249–254, https://doi.org/10.1038/s41586‐021‐03506‐2.
J. Pei, L. Deng, S. Song, et al., “Towards Artificial General Intelligence with Hybrid Tianjic Chip Architecture,” Nature 572 (2019): 106–111, https://doi.org/10.1038/s41586‐019‐1424‐8.
M. Wang, Z. Yan, T. Wang, et al., “Gesture Recognition Using a Bioinspired Learning Architecture That Integrates Visual Data with Somatosensory Data from Stretchable Sensors,” Nature Electronics 3 (2020): 563–570, https://doi.org/10.1038/s41928‐020‐0422‐z.
M. Mohammadi, H. Knoche, M. Thøgersen, et al., “Eyes‐Free Tongue Gesture and Tongue Joystick Control of a Five DOF Upper‐Limb Exoskeleton for Severely Disabled Individuals,” Frontiers in Neuroscience 15 (2021): 739279, https://doi.org/10.3389/fnins.2021.739279.
M. Mohammadi, H. Knoche, M. Gaihede, B. Bentsen, and L. N. S. Andreasen Struijk, “A High‐Resolution Tongue‐based Joystick to Enable Robot Control for Individuals with Severe Disabilities,” in 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR) (IEEE, 2019): 1043–1048, https://doi.org/10.1109/ICORR.2019.8779434.
M. Mohammadi, H. Knoche, B. Bentsen, M. Gaihede, and L. N. S. Andreasen Struijk, “A Pilot Study on a Novel Gesture‐Based Tongue Interface for Robot and Computer Control,” in 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE) (IEEE, 2020): 906–913, https://doi.org/10.1109/BIBE50027.2020.00154.
B. Hou, D. Yang, X. Ren, L. Yi, and X. Liu, “A Tactile Oral Pad Based on Carbon Nanotubes for Multimodal Haptic Interaction,” Nature Electronics 7 (2024): 777–787, https://doi.org/10.1038/s41928‐024‐01234‐9.
B. Hou, L. Yi, C. Li, et al., “An Interactive Mouthguard Based on Mechanoluminescence‐powered Optical Fibre Sensors for Bite‐controlled Device Operation,” Nature Electronics 5 (2022): 682–693, https://doi.org/10.1038/s41928‐022‐00841‐8.
H. Luo, J. Du, P. Yang, et al., “Human–Machine Interaction via Dual Modes of Voice and Gesture Enabled by Triboelectric Nanogenerator and Machine Learning,” ACS Applied Materials & Interfaces 15 (2023): 17009–17018, https://doi.org/10.1021/acsami.3c00566.
W. Ding, A. C. Wang, C. Wu, H. Guo, and Z. L. Wang, “Human–Machine Interfacing Enabled by Triboelectric Nanogenerators and Tribotronics,” Advanced Materials Technologies 4 (2019): 1800487, https://doi.org/10.1002/admt.201800487.
X. Cao, Y. Xiong, J. Sun, X. Xie, Q. Sun, and Z. L. Wang, “Multidiscipline Applications of Triboelectric Nanogenerators for the Intelligent Era of Internet of Things,” Nano‐Micro Letters 15 (2023): 14, https://doi.org/10.1007/s40820‐022‐00981‐8.
G. Xu, H. Wang, G. Zhao, et al., “Self‐Powered Electrotactile Textile Haptic Glove for Enhanced Human‐Machine Interface,” Science Advances 11 (2025): adt0318, https://doi.org/10.1126/sciadv.adt0318.
Y. Liu, J. Wang, T. Liu, et al., “Triboelectric Tactile Sensor for Pressure and Temperature Sensing in High‐Temperature Applications,” Nature Communications 16 (2025): 383, https://doi.org/10.1038/s41467‐024‐55771‐0.
J. Shi, Z. Zhao, Y. Gao, et al., “A High‐Voltage‐Specialized Direct‐Current Triboelectric Nanogenerator for Air Purification,” Small 20 (2024): 2311930, https://doi.org/10.1002/smll.202311930.
J. Zhang, Y. Gao, D. Liu, J.‐S. Zhao, and J. Wang, “Discharge Domains Regulation and Dynamic Processes of Direct‐Current Triboelectric Nanogenerator,” Nature Communications 14 (2023): 3218, https://doi.org/10.1038/s41467‐023‐38815‐9.
Y. Gao, L. He, D. Liu, et al., “Spontaneously Established Reverse Electric Field to Enhance the Performance of Triboelectric Nanogenerators via Improving Coulombic Efficiency,” Nature Communications 15 (2024): 4167, https://doi.org/10.1038/s41467‐024‐48456‐1.
J. Meng, Z. H. Guo, C. Pan, et al., “Flexible Textile Direct‐Current Generator Based on the Tribovoltaic Effect at Dynamic Metal‐Semiconducting Polymer Interfaces,” ACS Energy Letters 6 (2021): 2442–2450, https://doi.org/10.1021/acsenergylett.1c00288.
S. Afrin, E. Haque, B. Ren, and J. Z. Ou, “Liquid Elementary Metals and Alloys: Synthesis, Characterization, Properties, and Applications,” Applied Materials Today 31 (2023): 101746, https://doi.org/10.1016/j.apmt.2023.101746.
R. Yu, Y. Chi, J. Zheng, et al., “Dynamic Electric Discharge Paths in Liquid Metal Marble Arrays,” Advanced Materials 36 (2024): 2408933, https://doi.org/10.1002/adma.202408933.
A. R. Jacob, D. P. Parekh, M. D. Dickey, and L. C. Hsiao, “Interfacial Rheology of Gallium‐Based Liquid Metals,” Langmuir 35 (2019): 11774–11783, https://doi.org/10.1021/acs.langmuir.9b01821.
W. Ge, R. Wang, X. Zhu, et al., “Recent Progress in Eutectic Gallium Indium (EGaIn): Surface Modification and Applications,” Journal of Materials Chemistry A 12 (2024): 657–689, https://doi.org/10.1039/D3TA04798A.
T. Daeneke, K. Khoshmanesh, N. Mahmood, et al., “Liquid Metals: Fundamentals and Applications in Chemistry,” Chemical Society Reviews 47 (2018): 4073–4111, https://doi.org/10.1039/C7CS00043J.
M. Kim, H. Lim, and S. H. Ko, “Liquid Metal Patterning and Unique Properties for Next‐Generation Soft Electronics,” Advanced Science 10 (2023): 2205795, https://doi.org/10.1002/advs.202205795.
F. Carle, K. Bai, J. Casara, K. Vanderlick, and E. Brown, “Development of Magnetic Liquid Metal Suspensions for Magnetohydrodynamics,” Physical Review Fluids 2 (2017): 013301, https://doi.org/10.1103/PhysRevFluids.2.013301.
L. Cao, D. Yu, Z. Xia, et al., “Ferromagnetic Liquid Metal Putty‐Like Material with Transformed Shape and Reconfigurable Polarity,” Advanced Materials 32 (2020): 2000827, https://doi.org/10.1002/adma.202000827.
H. Wang, S. Li, Y. Zhang, et al., “A Self‐Powered, Shapeable, and Wearable Sensor for Effective Hazard Prevention and Biomechanical Monitoring,” SmartSys 1 (2025): 3, https://doi.org/10.1002/sys3.3.
S. Li, Y. Wu, W. Asghar, et al., “Wearable Magnetic Field Sensor with Low Detection Limit and Wide Operation Range for Electronic Skin Applications,” Advanced Science 11 (2024): 2304525, https://doi.org/10.1002/advs.202304525.
J. Kim, J. P. Lee, Y. Jang, J. H. Jeong, Y.‐K. Baek, and J. Kim, “Material‐Level Integration of Magnetic Actuation and Triboelectric Sensing for Adaptive Soft Robotic Platforms,” Advanced Materials (2025): 12553, https://doi.org/10.1002/adma.202512553.
R. Yang and F. Rosei, “High‐Entropy Strategy Boosts Energy Storage in Ferroelectric Polymers,” SmartSys 1 (2025): 70003, https://doi.org/10.1002/sys3.70003.
L. Liu, J. Li, W. Ou‐Yang, et al., “Ferromagnetic‐assisted Maxwell's Displacement Current Based on Iron/Polymer Composite for Improving the Triboelectric Nanogenerator Output,” Nano Energy 96 (2022): 107139, https://doi.org/10.1016/j.nanoen.2022.107139.
T. Wu, X. Wang, X. Cao, and N. Wang, “NdFeB‐based Magnetic Triboelectric Nanogenerator for Enhanced Bioenergy Harvesting and Tactile Perception,” Nano Energy 128 (2024): 109883, https://doi.org/10.1016/j.nanoen.2024.109883.
W. Qiao, Z. Zhao, L. Zhou, et al., “Simultaneously Enhancing Direct‐Current Density and Lifetime of Tribovotaic Nanogenerator via Interface Lubrication,” Advanced Functional Materials 32 (2022): 2208544, https://doi.org/10.1002/adfm.202208544.
Z. Wang, L. Gong, S. Dong, et al., “A Humidity‐enhanced Silicon‐based Semiconductor Tribovoltaic Direct‐current Nanogenerator,” Journal of Materials Chemistry A 10 (2022): 25230, https://doi.org/10.1039/d2ta07637c.
J. Meng, C. Pan, L. Li, et al., “Durable Flexible Direct Current Generation through the Tribovoltaic Effect in Contact‐separation Mode,” Energy & Environmental Science 15 (2022): 5159–5167, https://doi.org/10.1039/d2ee02762c.
J. Meng, C. Lan, C. Pan, J. Yang, X. Pu, and Z. L. Wang, “Boosted Outputs and Robustness of Polymeric Tribovoltaic Nanogenerator through Secondary Doping,” Chemical Engineering Journal 487 (2024): 150412, https://doi.org/10.1016/j.cej.2024.150412.
Z. Zhao, J. Zhang, W. Qiao, et al., “Contact Efficiency Optimization for Tribovoltaic Nanogenerators,” Materials Horizons 10 (2023): 5962–5968, https://doi.org/10.1039/d3mh01369c.
M. Fu, X. Zhang, W. Dong, et al., “Optimizing Na Plating/Stripping by a Liquid Sodiophilic Ga‐Sn‐In Alloy towards Dendrite‐poor Sodium Metal Anodes,” Energy Storage Materials 63 (2023): 103020, https://doi.org/10.1016/j.ensm.2023.103020.
A. Gupta, N. Al‐Shamery, J. Lv, et al., “Stretchable Energy Storage with Eutectic Gallium Indium Alloy,” Advanced Energy Materials 15 (2024): 2403760, https://doi.org/10.1002/aenm.202403760.
S. Sapp, S. Luebben, Y. B. Losovyj, P. Jeppson, D. L. Schulz, and A. N. Caruso, “Work Function and Implications of Doped Poly(3,4‐ethylenedioxythiophene)‐ co ‐poly(ethylene glycol),” Applied Physics Letters 88 (2006): 152107, https://doi.org/10.1063/1.2193399.
Y. Zhou, C. Fuentes‐Hernandez, J. Shim, et al., “A Universal Method to Produce Low–Work Function Electrodes for Organic Electronics,” Science 336 (2016): 327–332, https://doi.org/10.1126/science.1218829.
T. Liu, L. Sun, X. Dong, et al., “Low‐Work‐Function PEDOT Formula as a Stable Interlayer and Cathode for Organic Solar Cells,” Advanced Functional Materials 31 (2021): 2107250, https://doi.org/10.1002/adfm.202107250.
K. Kim, E. C. Chae, G. Son, et al., “Chemically Passivated Polymeric Charge Recombination Layer for Efficient Tandem Organic Solar Cells,” Advanced Energy Materials (2025): 04940, https://doi.org/10.1002/aenm.202504940.
G. Liu, R. Luan, Y. Qi, et al., “Organic Tribovoltaic Nanogenerator with Electrically and Mechanically Tuned Flexible Semiconductor Textile,” Nano Energy 106 (2023): 108075, https://doi.org/10.1016/j.nanoen.2022.108075.
X. Zhao, Y. Zhou, A. Li, et al., “A Self‐Filtering Liquid Acoustic Sensor for Voice Recognition,” Nature Electronics 7 (2024): 924–932, https://doi.org/10.1038/s41928‐024‐01196‐y.
Grant Information: 82072065 National Nature Science Foundation; E2EG6802X2 Fundamental Research Funds for the Central Universities; National Youth Talent Support Program
Contributed Indexing: Keywords: human‐computer interaction; neural network; self‐powered; tactile sensors; tribovoltaic effect
Entry Date(s): Date Created: 20260205 Date Completed: 20260706 Latest Revision: 20260706
Update Code: 20260707
DOI: 10.1002/adma.202522639
PMID: 41641904
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:1521-4095
DOI:10.1002/adma.202522639