{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T05:08:00Z","timestamp":1787029680760,"version":"build-2736575974"},"reference-count":37,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T00:00:00Z","timestamp":1753401600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"New Faculty Research Initiation Program Project","award":["233072024CFJ0401"],"award-info":[{"award-number":["233072024CFJ0401"]}]},{"name":"Vice-Chancellors Early Career Researcher Development Award","award":["233072024CFJ0401"],"award-info":[{"award-number":["233072024CFJ0401"]}]},{"name":"Research Grants of The Royal Society","award":["233072024CFJ0401"],"award-info":[{"award-number":["233072024CFJ0401"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Sign language recognition plays a crucial role in enabling communication for deaf individuals, yet current methods face limitations such as sensitivity to lighting conditions, occlusions, and lack of adaptability in diverse environments. This study presents a wearable multi-channel tactile sensing system based on smart textiles, designed to capture subtle wrist and finger motions for static sign language recognition. The system leverages triboelectric yarns sewn into gloves and sleeves to construct a skin-conformal tactile sensor array, capable of detecting biomechanical interactions through contact and deformation. Unlike vision-based approaches, the proposed sensor platform operates independently of environmental lighting or occlusions, offering reliable performance in diverse conditions. Experimental validation on American Sign Language letter gestures demonstrates that the proposed system achieves high signal clarity after customized filtering, leading to a classification accuracy of 94.66%. Experimental results show effective recognition of complex gestures, highlighting the system\u2019s potential for broader applications in human-computer interaction.<\/jats:p>","DOI":"10.3390\/s25154602","type":"journal-article","created":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T09:35:11Z","timestamp":1753436111000},"page":"4602","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Smart Textile-Based Tactile Sensing System for Multi-Channel Sign Language Recognition"],"prefix":"10.3390","volume":"25","author":[{"given":"Keran","family":"Chen","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9732-5486","authenticated-orcid":false,"given":"Longnan","family":"Li","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China"},{"name":"Bristol Robotics Laboratory, University of the West of England, Bristol BS16 1QY, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4709-141X","authenticated-orcid":false,"given":"Qinyao","family":"Peng","sequence":"additional","affiliation":[{"name":"Bristol Robotics Laboratory, University of the West of England, Bristol BS16 1QY, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengyuan","family":"He","sequence":"additional","affiliation":[{"name":"Bristol Robotics Laboratory, University of the West of England, Bristol BS16 1QY, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liyun","family":"Ma","sequence":"additional","affiliation":[{"name":"Hamlyn Centre for Robotic Surgery, Department of Mechanical Engineering, Imperial College London, London SW7 2AZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinxin","family":"Li","sequence":"additional","affiliation":[{"name":"College of Textiles, Donghua University, Shanghai 200051, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenyu","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Automation, South China University of Technology, Guangzhou 510641, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"40979","DOI":"10.1109\/ACCESS.2022.3161440","article-title":"Technological solutions for sign language recognition: A scoping review of research trends, challenges, and opportunities","volume":"10","author":"Joksimoski","year":"2022","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Antad, S.M., Chakrabarty, S., Bhat, S., Bisen, S., and Jain, S. 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