Evidence map›Paper›PMID 36144026›Full record

ArticleMicromachines2022

Mathematical Model for Skin Pain Sensation under Local Distributed Mechanical Compression for Electronic Skin Applications.

Dongcan Ji, Yingli Shi, Jiayun Chen, Zhao Zhao, Guozhong Zhao

Abstract read
In one paragraph

Article 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. Article
  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

5 authors.

Dongcan JiInstitute of Solid Mechanics, Beihang University (BUAA), Beijing 100191, China.
Yingli ShiSchool of Materials and Energy, University of Electronic Science and Technology of China (USETC), Chengdu 610054, China.ORCID 0000-0002-1912-1967
Jiayun ChenInstitute of Solid Mechanics, Beihang University (BUAA), Beijing 100191, China.ORCID 0000-0003-3734-3165
Zhao ZhaoInstitute of Solid Mechanics, Beihang University (BUAA), Beijing 100191, China.
Guozhong ZhaoState Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian 116024, China.

Funding

the Opening fund of the State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology GZ19117
6 · The paper itself

Abstract

Skin pain resulting from mechanical compression is one of the most common pains in daily life and the indispensable information for electronic skin to perceive external signals. The external mechanical stimuli are transduced into impulses and transmitted via nerve fiber, and finally, the sensation is perceived via the procession of the nerve system. However, the mathematical mechanism for pain sensation due to mechanical stimuli remains unclear. In this paper, a mathematical model for skin pain sensation under compression is established, in which the Flament solution, the revised Hodgkin-Huxley model, and the mathematical model gate control theory are considered simultaneously. The proposed model includes three parts: a mechanical model of skin compression, a model of transduction, and a model of modulation and perception. It is demonstrated that the pain sensation degree increases with the compression amplitude and decreases with deeper nociceptor location in the skin. With the help of the proposed model, the quantitative relationship between compression pain sensation and external mechanical stimuli is revealed, which has a significant benefit in promoting the design and mechanism research of electronic skin with pain perception function.

Indexed as

electronic skingate control theorymechanical compressionrevised Hodgkin–Huxley modelskin pain sensation

Identifiers

PMID36144026
PMCPMC9500653

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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.