FlexiPulse : A machine-learning-enabled flexible pulse sensor for cardiovascular disease diagnostics
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Article number | 101690 |
Journal / Publication | Cell Reports Physical Science |
Volume | 4 |
Issue number | 12 |
Online published | 20 Nov 2023 |
Publication status | Published - 20 Dec 2023 |
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DOI | DOI |
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Publisher's Copyright Statement
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85177217541&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(ecf11624-fe5d-4d4d-8fd0-8c5b0a5c0289).html |
Abstract
Recently, the flexible pulse sensor has emerged as a promising candidate for real-time and population-wide monitoring of cardiovascular health. However, most current technologies are prohibitively expensive, lack clinical validation, or are not designed to diagnose cardiovascular disease (CVD) events. Here, we present the development of FlexiPulse, a low-cost, clinically validated, intelligent, flexible pulse detection system for CVD monitoring and diagnostics. The porous graphene-based FlexiPulse is prepared by eco-friendly and economical laser direct-engraving techniques and is feasible for mass production. FlexiPulse achieves high accuracy (>93%), as confirmed by clinical techniques, enabling it to precisely detect subtle changes in cardiovascular status. Furthermore, incorporating machine-learning algorithms in FlexiPulse allows it to perform independent clinical assessments of actual CVD events, including atrial fibrillation and atrial septal defect, with an average accuracy of 98.7%. We believe that FlexiPulse has the potential to promote remote monitoring and in-home care, thereby advancing precision medicine and personalized healthcare significantly. © 2023 The Authors.
Citation Format(s)
FlexiPulse: A machine-learning-enabled flexible pulse sensor for cardiovascular disease diagnostics. / Ma, Zhiqiang; Hua, Haojun; You, Changxin et al.
In: Cell Reports Physical Science, Vol. 4, No. 12, 101690, 20.12.2023.
In: Cell Reports Physical Science, Vol. 4, No. 12, 101690, 20.12.2023.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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