Evidence map›Paper›PMID 42143123›Full record

ArticleScientific reports2026

Application of a PSO-FAHP-based evaluation system for office chair design demand analysis.

Mingzhu Li, Xinyue Peng, Fangyuan Chang, Tao Peng, Xingyan Chen, Wuyi Qiang, Tao Tao

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

7 authors.

Mingzhu LiFurniture Institute, Central South University of Forestry and Technology, Changsha, 410004, China.
Xinyue PengFurniture Institute, Central South University of Forestry and Technology, Changsha, 410004, China.
Fangyuan ChangShanghai Jiao Tong University, Shanghai, 200240, China.
Tao PengZhejiang University Hangzhou, Hangzhou, 310027, Zhejiang, China.
Xingyan ChenFurniture Institute, Central South University of Forestry and Technology, Changsha, 410004, China. cxykhhijj@163.com.
Wuyi QiangFurniture Institute, Central South University of Forestry and Technology, Changsha, 410004, China.
Tao TaoFurniture Institute, Central South University of Forestry and Technology, Changsha, 410004, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Existing studies on office chair evaluation often emphasize either general furniture attributes or isolated performance indicators, limiting their usefulness for systematic design decision-making. To address this issue, this study proposes a demand-oriented evaluation framework for office chair products by integrating particle swarm optimization (PSO) with the fuzzy analytic hierarchy process (FAHP). Based on Maslow's hierarchy of needs, office chair user requirements were identified and organized using the KJ method to establish a hierarchical evaluation index system. FAHP was applied to determine criterion weights under fuzzy judgment conditions, and PSO was used to improve matrix consistency and weighting stability. A fuzzy comprehensive evaluation was then conducted for four selected representative office chair alternatives. The results showed that safety requirements had the highest weight, followed by basic functional and engineering requirements, while aesthetic and innovation-related requirements were less important. Among the four alternatives, Design Case A obtained the highest score under the selected criteria, weights, evaluators, and scoring scale. The findings suggest that office chair evaluation depends primarily on lower-order requirements related to use, support, and reliability, rather than on higher-order experiential attributes. The proposed PSO-FAHP framework offers a practical method for office chair assessment and a structured basis for requirement-oriented design decision-making.

Indexed as

Design evaluationFuzzy analytic hierarchy processMulti-criteria decision-makingOffice chair designParticle swarm optimizationUser requirements

Identifiers

PMID42143123
PMCPMC13370018

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LicenceCC BY-NC-ND
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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.