Evidence map›Paper›PMID 37687808›Full record

ArticleSensors (Basel, Switzerland)2023

Design and Development of a Hair-like Sensor with Bridge-Type Flexible Amplification Mechanisms.

Yongzhen Li, Pei Cao, Peng Zhang, Hua Yang, Xiaofeng Zhu, Ruihua Guo

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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. 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

6 authors.

Yongzhen LiInstitute for Smart Ageing, Beijing Academy of Science and Technology, Beijing 100089, China.
Pei CaoInstitute for Smart Ageing, Beijing Academy of Science and Technology, Beijing 100089, China.
Peng ZhangNational Center for Occupational Safety and Health, National Health Commission of the People's Republic of China, Beijing 102308, China.
Hua YangInstitute for Smart Ageing, Beijing Academy of Science and Technology, Beijing 100089, China.
Xiaofeng ZhuInstitute for Smart Ageing, Beijing Academy of Science and Technology, Beijing 100089, China.
Ruihua GuoInstitute for Smart Ageing, Beijing Academy of Science and Technology, Beijing 100089, China.ORCID 0000-0002-6209-2006

Funding

1120236481KF002-3 1120236481KF002-3Beijing Academy of Science and Technology Budding Talent Program BGS202211BeiJing Academy of Science and Techology-Reform and Development 1020239718KF001-20Beijing Natural Science Foundation 3224063
6 · The paper itself

Abstract

Compared with lever-type amplification mechanisms, bridge-type flexible amplification mechanisms have advantages in terms of amplification ratio and structural compactness. Therefore, they can effectively replace the lever-type amplification mechanism in the existing hair-like sensors and realize the development of miniature hair-like sensors with high sensitivity. With that in mind, a highly sensitive hair-like sensor based on a bridge-type amplification mechanism with distributed flexibility is presented to measure the airflow rate. First, the structural composition and operating principle of the hair-like sensor are described. Then, detailed design and analysis of the hair-like sensor are carried out, focusing on the design of the hair post structure, amplification mechanism, and resonator. Furthermore, the designed hair-like sensor is processed and prepared, and some experimental studies are conducted. The experimental results demonstrate that the developed hair-like sensor can measure the airflow rate with high sensitivity up to 8.56 Hz/(m/s)

Indexed as

airflow ratebridge-type amplification mechanismhair-like sensorresonator

Identifiers

PMID37687808
PMCPMC10490522

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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.