Evidence map›Paper›PMID 40431979›Full record

ArticleSensors (Basel, Switzerland)2025

Fabric Tactile Prediction Method Based on Spider Diagram.

Ruifeng Xie, Shuyang Ding, Zeyu Cheng, Luowei Ma, Yanzhu Yang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ruifeng XieCollege of Mechanical Engineering, Donghua University, Shanghai 201620, China.
Shuyang DingCollege of Mechanical Engineering, Donghua University, Shanghai 201620, China.ORCID 0000-0001-9970-4013
Zeyu ChengCollege of Mechanical Engineering, Donghua University, Shanghai 201620, China.
Luowei MaCollege of Mechanical Engineering, Donghua University, Shanghai 201620, China.
Yanzhu YangCollege of Mechanical Engineering, Donghua University, Shanghai 201620, China.

Funding

National Natural Science Foundation of China 51905090
6 · The paper itself

Abstract

The detection and quantification of fabric tactile sensations are crucial in textile production and marketing as they are closely linked to textile comfort and serve as key criteria for consumers when selecting fabrics. Previous studies have predominantly focused on measuring the physical properties of fabrics, often neglecting correlations between these parameters and tactile sensations. This oversight complicates customers' ability to assess the tactile experience of fabrics during online purchasing. This study first obtained subjective evaluations of three types of fabric tactile sensations through experiments involving volunteer participants. Subsequently, five objective physical properties that characterize fabric tactile properties were proposed and experimentally tested on 15 fabric samples categorized by yarn weight, weave pattern, and material. A fabric tactile spider diagram was created by normalizing the values of the five physical properties across the 15 fabric samples. The grading of the physical properties was then performed based on the proposed evaluation index. These spider diagrams were compared with the subjective evaluation results to analyze the physical properties that most significantly influenced subjective perception, ultimately leading to the development of a highly reliable fabric touch prediction model.

Indexed as

TextilesTouchAdultFemaleHumansMaleYoung Adultfabric physical propertiesfabric touchpredictive modelingtextiles

Identifiers

PMID40431979
PMCPMC12115606

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.