Evidence map›Paper›PMID 39957176›Full record

ArticleJournal of traditional Chinese medicine = Chung i tsa chih ying wen pan2025

Research and development of the pulse acquisition system and the pulse biomimetic reproduction system.

Y I Kai, M A Yunjing, Guo Shen, Liu Heng, X U Bin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan, 2025. 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. 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

5 authors.

Y I Kaithe First Clinical College, Liaoning University of Traditional Chinese Medicine, Shenyang 110000, China.
M A YunjingResearch and Development Department, Shenyang Traditional Chinese Medicine Intelligent Medical Equipment Industry Technology Research Institute, Shenyang 110000, China.
Guo ShenResearch and Development Department, Shenyang Traditional Chinese Medicine Intelligent Medical Equipment Industry Technology Research Institute, Shenyang 110000, China.
Liu HengResearch and Development Department, Shenyang Traditional Chinese Medicine Intelligent Medical Equipment Industry Technology Research Institute, Shenyang 110000, China.
X U Binthe First Clinical College, Liaoning University of Traditional Chinese Medicine, Shenyang 110000, China.

Funding

Construction of Liaoning Traditional Chinese Medicine Industry Technology Innovation Research Institute National Key Research and Development Plan Special Project 2019JH2/10300040Key R & D Plan of Liaoning Province 202000357-JH13/103
6 · The paper itself

Abstract

The paper is an introduction to the front-end pulse acquisition and the back-end pulse biomimetic reproduction system. This system is capable of faithfully replicating the complete pulse waveform collected at the front end. Traditional Chinese Medicine (TCM) practitioners analyze and diagnose the pulse patterns at the replication end. Meanwhile, the obtained pulse waveforms are analyzed and learnt by a neural network based on key diagnostic points in TCM pulse taking, which enables the determination of the corresponding relationships between different pulse waveforms and various pulse patterns in TCM pulse taking. With the support of clinical samples, an auxiliary diagnostic system for TCM pulse patterns ensures the accuracy of pulse pattern replication.

Indexed as

BiomimeticsMedicine, Chinese TraditionalPulseHumansNeural Networks, Computermedicine, Chinese traditionalpulse acquisition systempulse biomimetic reproduction systempulse taking

Identifiers

PMID39957176
PMCPMC11764930

What OpenQuestion holds

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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 OpenQuestion graph.