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Abstract
Continuous monitoring of arterial blood pressure (BP) outside of a clinical setting is crucial for preventing and diagnosing hypertension related diseases. However, current continuous BP monitoring instruments suffer from either bulky systems or poor user-device interfacial performance, hampering their applications in continuous BP monitoring. Here, we report a thin, soft, miniaturized system (TSMS) that combines a conformal piezoelectric sensor array, an active pressure adaptation unit, a signal processing module, and an advanced machine learning method, to allow real wearable, continuous wireless monitoring of ambulatory artery BP. By optimizing the materials selection, control/sampling strategy, and system integration, the TSMS exhibits improved interfacial performance while maintaining Grade A level measurement accuracy. Initial trials on 87 volunteers and clinical tracking of two hypertension individuals prove the capability of the TSMS as a reliable BP measurement product, and its feasibility and practical usability in precise BP control and personalized diagnosis schemes development.
Continuous monitoring of arterial blood pressure is limited by bulky connecting systems and poor interfacial contact. Here, Li et al. report a wearable thin, soft, miniaturized system that integrates sensing, active pressure adaptation, and signal processing for improved performance and accuracy.
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1 City University of Hong Kong, Department of Biomedical Engineering, Hong Kong, China (GRID:grid.35030.35) (ISNI:0000 0004 1792 6846); Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China (GRID:grid.35030.35)
2 City University of Hong Kong, Department of Biomedical Engineering, Hong Kong, China (GRID:grid.35030.35) (ISNI:0000 0004 1792 6846)
3 Jilin University, School of Mechanical and Aerospace Engineering, Changchun, China (GRID:grid.64924.3d) (ISNI:0000 0004 1760 5735)
4 City University of Hong Kong, Department of Biomedical Engineering, Hong Kong, China (GRID:grid.35030.35) (ISNI:0000 0004 1792 6846); University of Electronic Science and Technology of China (UESTC), State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Optoelectronic Science and Engineering, Chengdu, China (GRID:grid.54549.39) (ISNI:0000 0004 0369 4060)
5 Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China (GRID:grid.35030.35); Hong Kong Baptist University, Department of Mathematics, Hong Kong, China (GRID:grid.221309.b) (ISNI:0000 0004 1764 5980)
6 The first medical center of Chinese PLA General Hospital, Department of vascular and endovascular surgery, Beijing, China (GRID:grid.414252.4) (ISNI:0000 0004 1761 8894)
7 City University of Hong Kong, Department of Biomedical Engineering, Hong Kong, China (GRID:grid.35030.35) (ISNI:0000 0004 1792 6846); Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China (GRID:grid.35030.35); City University of Hong Kong Shenzhen Research Institute, Shenzhen, China (GRID:grid.464255.4)