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The sensor has a variety of advantages, including high sensitivity, high linearity, fast response and recovery, and high isotropy. Experiments and simulation synergistically verified that the sensor array can acquire high-precise and feature-rich pulse waves from the wrist without precise positioning. By combining high-quality pulse waves with a well-trained deep learning model, we can monitor blood pressure and cardiac function parameters. As a proof of concept, we further constructed an intelligent wearable system for real-time and long-term monitoring of blood pressure and cardiac function, which may contribute to personalized health management, precise and early diagnosis, and remote treatment.<\/jats:p>","DOI":"10.1126\/sciadv.adh0615","type":"journal-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T17:59:32Z","timestamp":1691776772000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":224,"title":["Monitoring blood pressure and cardiac function without positioning via a deep learning\u2013assisted strain sensor array"],"prefix":"10.1126","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7495-0869","authenticated-orcid":true,"given":"Shuo","family":"Li","sequence":"first","affiliation":[{"name":"Key Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua 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