Evidence map›Paper›PMID 38867942›Full record

ArticleMicrosystems & nanoengineering2024

Wearable multichannel-active pressurized pulse sensing platform.

Yunlong Zhao, Qingxia Sun, Shixuan Mei, Libo Gao, Xikuan Zhang, Zekun Yang, Xueli Nan, Haiyan Zhang, Chenyang Xue, Junyang Li

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

10 authors.

Yunlong Zhao *Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, 361102 Xiamen, China.ORCID 0000-0002-5553-9009
Qingxia Sun *Department of Electronic Engineering, Ocean University of China, 266000 Qingdao, China.
Shixuan MeiSchool of Automation and Software Engineering, Shanxi University, 030006 Taiyuan, China.
Libo GaoPen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, 361102 Xiamen, China.ORCID 0000-0002-5964-2337
Xikuan ZhangKey Laboratory of Instrumentation Science and Dynamic Measurement Ministry of Education, North University of China, 030051 Taiyuan, China.
Zekun YangKey Laboratory of Instrumentation Science and Dynamic Measurement Ministry of Education, North University of China, 030051 Taiyuan, China.
Xueli NanSchool of Automation and Software Engineering, Shanxi University, 030006 Taiyuan, China.
Haiyan ZhangScience and Technology on Vacuum Technology and Physics Laboratory, Lanzhou Institute of Physics, Chinese Academy of Space Technology, 730000 Lanzhou, China.
Chenyang XuePen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, 361102 Xiamen, China.
Junyang LiDepartment of Electronic Engineering, Ocean University of China, 266000 Qingdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the modernization of traditional Chinese medicine (TCM), creating devices to digitalize aspects of pulse diagnosis has proved to be challenging. The currently available pulse detection devices usually rely on external pressure devices, which are either bulky or poorly integrated, hindering their practical application. In this work, we propose an innovative wearable active pressure three-channel pulse monitoring device based on TCM pulse diagnosis methods. It combines a flexible pressure sensor array, flexible airbag array, active pressure control unit, advanced machine learning approach, and a companion mobile application for human-computer interaction. Due to the high sensitivity (460.1 kPa

Indexed as

Electrical and electronic engineering

Identifiers

PMID38867942
PMCPMC11166975

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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.