Evidence mapPaperPMID 42307141Full record

ReviewAdvanced materials (Deerfield Beach, Fla.)2026

Wearable Flexible Sensors for Cardiovascular Disease Monitoring.

Xinyu Xie, Xinyu Qu, Bowen Zhou, Bocong Zhang, Qian Wang, Huahui Bian, Jinjun Shao, Yichen Cai, Xiaochen Dong

Abstract readReview
In one paragraph

Review in Advanced materials (Deerfield Beach, Fla.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Wearable Flexible Sensors for Cardiovascular Disease Monitoring.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Xinyu XieState Key Laboratory of Flexible Electronics (LoFE) & Institute of Advanced Materials (IAM), School of Flexible Electronics (Future Technologies), Nanjing Tech University, Nanjing, China.
Xinyu QuState Key Laboratory of Flexible Electronics (LoFE) & Institute of Advanced Materials (IAM), School of Flexible Electronics (Future Technologies), Nanjing Tech University, Nanjing, China.
Bowen ZhouState Key Laboratory of Flexible Electronics (LoFE) & Institute of Advanced Materials (IAM), School of Flexible Electronics (Future Technologies), Nanjing Tech University, Nanjing, China.
Bocong ZhangState Key Laboratory of Flexible Electronics (LoFE) & Institute of Advanced Materials (IAM), School of Flexible Electronics (Future Technologies), Nanjing Tech University, Nanjing, China.
Qian WangState Key Laboratory of Flexible Electronics (LoFE) & Institute of Advanced Materials (IAM), School of Flexible Electronics (Future Technologies), Nanjing Tech University, Nanjing, China.
Huahui BianDepartment of Nuclear Accident Medical Emergency, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Jinjun ShaoState Key Laboratory of Flexible Electronics (LoFE) & Institute of Advanced Materials (IAM), School of Flexible Electronics (Future Technologies), Nanjing Tech University, Nanjing, China.ORCID https://orcid.org/0000-0001-6446-8073
Yichen CaiState Key Laboratory of Flexible Electronics (LoFE) & Institute of Advanced Materials (IAM), School of Flexible Electronics (Future Technologies), Nanjing Tech University, Nanjing, China.
Xiaochen DongState Key Laboratory of Flexible Electronics (LoFE) & Institute of Advanced Materials (IAM), School of Flexible Electronics (Future Technologies), Nanjing Tech University, Nanjing, China.ORCID https://orcid.org/0000-0001-7327-8060

Funding

Gusu Talent Program GSWS2022042National Natural Science Foundation of China 62288102Natural Science Foundation of Jiangsu Province BZ2024040Nuclear Medicine Research Project of the Discipline Construction Support Project (Phase II) of the General Hospital of Nuclear Industry XKTJ-HTD2025002Research Innovation Plan for Graduate Students in Jiangsu Province SJCX24_0559
6 · The paper itself

Abstract

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.

Indexed as

Biosensing TechniquesCardiovascular DiseasesWearable Electronic DevicesDigital HealthHumansMachine LearningMonitoring, Physiologiccardiovascular diseaseflexible sensorsmachine learningwearable

Identifiers

PMID42307141
PMCPMC13393999

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.