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Conventional systems, however, rely on physically stacked discrete sensors and von Neumann architectures, causing data redundancy and impaired wearability. Here, we present an in\u2010sensor\u2010computing dual\u2010modal neural fiber (ID neural fiber) that overcomes this fundamental limitation. The ID neural fiber achieves an unprecedented position resolution of &lt;\u00a05\u00a0mm and a pressure detection limit of 0.6\u00a0N, combined with exceptional robustness\u2013sustaining 300 times load\u2010bearing capacity and exhibiting &lt;\u00a08% performance fluctuation under bending. Coupled with flexibility, waterproofing, and reconfigurability, the ID neural fiber can be seamlessly integrated into textiles for reliable operation in harsh environments, including underwater robotic control. Crucially, the ID neural fiber enables in\u2010sensor computing that dramatically increases the information density and allows synchronized feature fusion through programmable logic gates, enabling efficient real\u2010time intention recognition. To capture touch habits, an intelligent system with the ID neural fiber achieves a remarkable identification accuracy of 98.21%. This work establishes a new material\u2013architecture paradigm that unifies ultrarobustness, dual\u2010modality, and in\u2010sensor computing, setting the stage for next\u2010generation wearable human\u2013machine interfaces with both comfort and intelligence.<\/jats:p>","DOI":"10.1002\/adma.75412","type":"journal-article","created":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T07:50:06Z","timestamp":1791964206000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Ultrarobust Dual\u2010Modal Neural Fiber With In\u2010Sensor Computing"],"prefix":"10.1002","author":[{"given":"Huasen","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Electronic Science Xiamen University  Xiamen 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Artificial Intelligence Xiamen University  Xiamen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gantang","family":"Su","sequence":"additional","affiliation":[{"name":"Department of Electronic Science Xiamen University  Xiamen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1473-2224","authenticated-orcid":false,"given":"Zhong","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Electronic Science Xiamen University  Xiamen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingliang","family":"Liao","sequence":"additional","affiliation":[{"name":"Academy For Advanced Interdisciplinary Science and Technology Key Laboratory of Advanced Materials and Devices for Post\u2010Moore Chips Ministry of Education University of Science and Technology Beijing  Beijing China"},{"name":"Beijing Key Laboratory for Advanced Energy Materials and Technologies School of Materials 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