Wearable Flexible Sensors for Cardiovascular Disease Monitoring
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.
Authors
- Jinjun Shao (ORCID: https://orcid.org/0000-0001-6446-8073)
- Xinyu Xie (ORCID: https://orcid.org/0000-0001-8582-0857)
- Yichen Cai (ORCID: https://orcid.org/0000-0002-5414-3627)
- Xiaochen Dong (ORCID: https://orcid.org/0000-0001-7327-8060)
- Huahui Bian
- Xinyu Qu (ORCID: https://orcid.org/0000-0001-5927-7838)
- Bocong Zhang
- Bowen Zhou
- Qian Wang
Institutions
- Jiangsu Normal University (CN)
- Nanjing Tech University (CN)
- Soochow University (CN)
- Second Affiliated Hospital of Soochow University (CN)
Publication Details
- Journal
- Advanced Materials
- Published
- 2026-06-17
- DOI
- https://doi.org/10.1002/adma.202512939
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Jiangsu Province