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However, gold\u2010standard diagnostic approaches for aspiration\u2014videofluoroscopic swallowing studies (VFSS) and fiberoptic endoscopic evaluation of swallowing (FEES)\u2014involve radiation, invasive procedures, or operational complexity, and cannot provide continuous aspiration monitoring. Here, we develop a skin\u2010interfaced wireless biomechanical system with tailored machine learning algorithms to detect aspiration in a continuous, user\u2010friendly, non\u2010invasive, and automated manner. The system detects post\u2010swallow choking coughs as an indicator of aspiration, and evaluates a nursing\u2010home cohort including aspiration elderly (n = 14) and non\u2010aspiration elderly (n = 64). Leave\u2010one\u2010out cross\u2010validation yields an average accuracy of 92% across four activity types, with a sensitivity of 91% in aspiration recognition. Additional testing on unseen aspiration patients supports patient\u2010level generalization. Reliability analysis and confidence calibration enhance the interpretability of the machine learning classification model, and underpin clinical deployment. The approach provides a compact, user\u2010friendly solution for continuous and dynamic aspiration monitoring in both home and institutional settings, holding promise for improving elderly healthcare.<\/jats:p>","DOI":"10.1002\/adhm.202505765","type":"journal-article","created":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T21:27:51Z","timestamp":1773005271000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Skin\u2010Interfaced Wireless Biomechanical System for Detecting Aspiration in Elderly Populations"],"prefix":"10.1002","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3632-1315","authenticated-orcid":false,"given":"Shaotong","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering College of Future Technology Peking University  Beijing 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Biomedical Engineering College of Future Technology Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering College of Future Technology Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering College of Future Technology Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiran","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering College of Future Technology Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruyue","family":"Zhong","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering College of Future Technology Peking 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