.png){kind=icon}
.png){kind=icon}
Return
Wearable Flexible Sensors for Cardiovascular Disease Monitoring
.png){kind=icon}
PRE
AI
DOI：10.1002/adma.202512939.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Wearable flexible sensors have emerged as a cornerstone of next-generation bioelectronics, enabling skin-conformal, continuous, and high-fidelity monitoring of cardiovascular diseases (CVDs). This review elucidates the structure-function relationships that govern sensing performance, highlighting how material innovation, structure engineering, and device architectures synergistically balance sensitivity, mechanical robustness, and biocompatibility. Key cardiovascular physiological signals, including electrical, mechanical, hemodynamic, and biochemical modalities, are systematically summarized and correlated with representative sensing mechanisms such as piezoresistive, capacitive, triboelectric, electrochemical, and optical transduction. The integration of machine learning (ML) and data-driven modeling is further discussed, highlighting its potential to enable personalized diagnostics, multimodal fusion, and adaptive prediction of cardiovascular risks. Despite substantial progress, critical challenges remain in long-term operational stability, scalable manufacturing, cross-population generalizability, and clinical validation. To address these limitations, a unified design paradigm integrating materials engineering, multimodal sensing strategies, and algorithmic intelligence is proposed. This review aims to guide the development of next-generation wearable platforms that are not only mechanically compliant and functionally robust but also algorithmically interpretable and clinically translatable, laying the groundwork for intelligent, reliable, and precision-oriented CVD monitoring systems.
Keywords:
cardiovascular disease
flexible sensors
machine learning
wearable
Journal
IF:
26.8
Papers:
3.4W
Citations:
46.0W
Organization
View more organizations