Evidence map›Paper›PMID 37566652›Full record

ArticleScience advances2023

Monitoring blood pressure and cardiac function without positioning via a deep learning-assisted strain sensor array.

Shuo Li, Haomin Wang, Wei Ma, Lin Qiu, Kailun Xia, Yong Zhang, Haojie Lu, Mengjia Zhu, Xiaoping Liang, Xun-En Wu and 2 more

Abstract read
In one paragraph

Article in Science advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing 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

51 citing papers in PubMed.

  1. Advances in Cellulose-Based Materials for Bionic Sensors.Macromolecular rapid communications · 2026
    Review
  2. Review
  3. Wearable Flexible Sensors for Cardiovascular Disease Monitoring.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  9. Article
  10. Article
  11. A Smart Headband for Multimodal Physiological Monitoring in Human Exercises.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  12. Review
  13. Review
  14. Review
  15. Materials and System Design for Self-Decision Bioelectronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  16. Article
  17. Article
  18. Review
  19. [Research progress on flexible wearable sensors for health monitoring].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025
    Review
  20. Article
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

12 authors.

Shuo LiKey Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, PR China.ORCID 0009-0003-7495-0869
Haomin WangKey Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, PR China.
Wei MaDepartment of Cardiovascular Disease, Peking University First Hospital, Beijing 100084, PR China.ORCID 0000-0003-1305-3980
Lin QiuDepartment of Cardiovascular Disease, Peking University First Hospital, Beijing 100084, PR China.
Kailun XiaKey Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, PR China.
Yong ZhangKey Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, PR China.
Haojie LuKey Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, PR China.
Mengjia ZhuKey Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, PR China.
Xiaoping LiangKey Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, PR China.
Xun-En WuKey Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, PR China.
Huarun LiangKey Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, PR China.
Yingying ZhangKey Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, PR China.ORCID 0000-0002-8448-3059

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Continuous and reliable monitoring of blood pressure and cardiac function is of great importance for diagnosing and preventing cardiovascular diseases. However, existing cardiovascular monitoring approaches are bulky and costly, limiting their wide applications for early diagnosis. Here, we developed an intelligent blood pressure and cardiac function monitoring system based on a conformal and flexible strain sensor array and deep learning neural networks. The sensor has a variety of advantages, including high sensitivity, high linearity, fast response and recovery, and high isotropy. Experiments and simulation synergistically verified that the sensor array can acquire high-precise and feature-rich pulse waves from the wrist without precise positioning. By combining high-quality pulse waves with a well-trained deep learning model, we can monitor blood pressure and cardiac function parameters. As a proof of concept, we further constructed an intelligent wearable system for real-time and long-term monitoring of blood pressure and cardiac function, which may contribute to personalized health management, precise and early diagnosis, and remote treatment.

Indexed as

Deep LearningWearable Electronic DevicesBlood PressureHeart RateMonitoring, Physiologic

Identifiers

PMID37566652
PMCPMC10421034

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.