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Here, we introduce a novel two\u2010stage amplification strategy employing a Zn\/Cu bimetallic zeolitic imidazolate framework (Cu\u2011ZIF\u20118) to simultaneously engineer \u03b2\u2011phase alignment and establish percolated conductive networks within electrospun PVDF nanofibers. Incorporating 3 wt% Cu\u2011ZIF\u20118 boosts \u03b2\u2011phase content by 21%, functioning as a dynamic nucleating agent that suppresses \u03b1\u2011phase crystallization and promotes all\u2011trans chain conformation. Coupled with copper\u2011ion\u2011facilitated charge transport, the pressure sensor achieves an exceptional sensitivity of 23.37\u00a0mV\/kPa, a fast response time of \u223c42.89\u00a0ms, and robust cyclic stability over 5000\u00a0cycles, enabling high\u2011fidelity detection of multiple physiological signals (including arterial pulse signals). To translate signals into actionable diagnostics, we further integrate a hybrid deep\u2011learning architecture combining Convolutional Neural Networks with Bidirectional Long Short\u2011Term Memory (CNN\u2011BiLSTM) to predict non\u2010invasive blood pressure (BP) from pulse waveforms. Trained on multi\u2010subject pulse waveform datasets, the model predicts BP with remarkable accuracy, attaining mean absolute errors of 0.69\u00b13.95\u00a0mmHg (systolic) and 0.25\u00b12.21\u00a0mmHg (diastolic), surpassing conventional regression models. By unifying tailored material design with embedded artificial intelligence, this work establishes PVDF\/Cu\u2011ZIF\u20118 composites as a versatile platform for next\u2011generation smart wearables capable of continuous health monitoring.<\/jats:p>","DOI":"10.1002\/admt.71248","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T07:07:58Z","timestamp":1789542478000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dual\u2010Function Enhancement of PVDF Nanofibers via Bimetallic MOF for Wearable Pressure Sensor and AI\u2010Driven Non\u2010Invasive Blood Pressure Prediction"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2454-5836","authenticated-orcid":false,"given":"Rafi u Shan","family":"Ahmad","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering College of Biomedicine City University of Hong Kong  Hong Kong China"},{"name":"Hong Kong Center of Cerebro\u2010Cardiovascular Health Engineering (COCHE)  Sha Tin Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed Elhousseini","family":"Hilal","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering College of Biomedicine City University of Hong Kong  Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2310-0058","authenticated-orcid":false,"given":"Weibin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering College of Biomedicine City University of Hong Kong  Hong Kong China"},{"name":"Hong Kong Center of Cerebro\u2010Cardiovascular Health Engineering (COCHE)  Sha Tin Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5568-3185","authenticated-orcid":false,"given":"Syed Bilal","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Department of Materials Science and Engineering City University of Hong Kong  Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1884-4557","authenticated-orcid":false,"given":"Wasim Ullah","family":"Khan","sequence":"additional","affiliation":[{"name":"School of Information Engineering Yango University  Fuzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5484-8192","authenticated-orcid":false,"given":"Iyappan","family":"Gunasekaran","sequence":"additional","affiliation":[{"name":"Hong Kong Center of Cerebro\u2010Cardiovascular Health Engineering (COCHE)  Sha Tin Hong Kong 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