Evidence map›Paper›PMID 36014147›Full record

ReviewMicromachines2022

Cuffless Blood Pressure Monitoring: Academic Insights and Perspectives Analysis.

Shiyun Li, Can Zhang, Zhirui Xu, Lihua Liang, Ye Tian, Long Li, Huaping Wu, Sheng Zhong

Abstract readReview
In one paragraph

Review in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

8 authors.

Shiyun LiCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.
Can ZhangCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.
Zhirui XuCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.
Lihua LiangCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.
Ye TianCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.ORCID 0000-0002-4068-7201
Long LiCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.ORCID 0000-0002-7365-2494
Huaping WuCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.
Sheng ZhongCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.

Funding

Department of Education of Zhejiang Province Y202043208National Natural Science Foundation of China 11972323National Natural Science Foundation of China 12002308Zhejiang Provincial Natural Science Foundation LR20A020002Zhejiang Provincial Natural Science Foundation LZY21E030002
6 · The paper itself

Abstract

In recent decades, cuffless blood pressure monitoring technology has been a point of research in the field of health monitoring and public media. Based on the web of science database, this paper evaluated the publications in the field from 1990 to 2020 using bibliometric analysis, described the developments in recent years, and presented future research prospects in the field. Through the comparative analysis of keywords, citations, H-index, journals, research institutions, national authors and reviews, this paper identified research hotspots and future research trends in the field of cuffless blood pressure monitoring. From the results of the bibliometric analysis, innovative methods such as machine learning technologies related to pulse transmit time and pulse wave analysis have been widely applied in blood pressure monitoring. The 2091 articles related to cuffless blood pressure monitoring technology were published in 1131 journals. In the future, improving the accuracy of monitoring to meet the international medical blood pressure standards, and achieving portability and miniaturization will remain the development goals of cuffless blood pressure measurement technology. The application of flexible electronics and machine learning strategy in the field will be two major development directions to guide the practical applications of cuffless blood pressure monitoring technology.

Indexed as

blood pressure monitoringcufflesspulse transit timepulse wave

Identifiers

PMID36014147
PMCPMC9415520

What Socratic holds

Textmetadata
LicenceCC BY
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.