Evidence map›Paper›PMID 37447578›Full record

ArticlePolymers2023

Wearable Smart Fabric Based on Hybrid E-Fiber Sensor for Real-Time Finger Motion Detection.

Erhan Zhuo, Ziwen Wang, Xiaochen Chen, Junhao Zou, Yuan Fang, Jiekai Zhuo, Yicheng Li, Jun Zhang, Zidan Gong

Abstract read
In one paragraph

Article in Polymers, 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. 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

9 authors.

Erhan ZhuoSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Ziwen WangSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Xiaochen ChenSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Junhao ZouSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Yuan FangSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Jiekai ZhuoSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Yicheng LiSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Jun ZhangLaboratory for Artificial Intelligence in Design, School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong 999077, China.
Zidan GongSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.ORCID 0000-0003-4521-8524

Funding

Shenzhen Stability Support Project Grant No. 20220717161452001the Natural Science Foundation of Top Talent of SZTU GDRC202107, Grant No. 2022024555101048University-Enterprise Cooperative Research Fund with Han's Laser 20211064010037, Grant No. 2021030555401037; 20211061040022, Grant No. 2021015555104022
6 · The paper itself

Abstract

Wearable electronic sensors have attracted considerable interest in hand motion monitoring because of their small size, flexibility, and biocompatibility. However, the range of motion and sensitivity of many sensors are inadequate for complex and precise finger motion capture. Here, organic and inorganic materials were incorporated to fabricate a hybrid electronic sensor and optimized and woven into fabric for hand motion detection. The sensor was made from flexible porous polydimethylsiloxane (PDMS) filled with multiwalled carbon nanotubes (MWCNTs). The weight ratios of MWCNTs and geometric characteristics were optimized to improve the hybrid electronic sensor, which showed a high elongation at the breaking point (i.e., more than 100%) and a good sensitivity of 1.44. The strain-related deformation of the PDMS/MWCNT composite network resulted in a variation in the sensor resistance; thus, the strain level that corresponds to different finger motions is be calculated. Finally, the fabricated and optimized electronic sensor in filiform structure with a 6% MWCNT ratio was integrated with smart fabric to create a finger sleeve for real-time motion capture. In conclusion, a novel hybrid E-fiber sensor based on PDMS and MWCNTs was successfully fabricated in the current study with an optimal M/P ratio and structure, and textile techniques were adopted as new packaging approaches for such soft electronic sensors to create smart fabric for wearable and precise detection with highly enhanced sensing performance. The successful results in the current study demonstrate the great potential of such hybrid soft sensors in smart wearable healthcare management, including motion detection.

Indexed as

E-fiber sensorfinger motion detectionmultiwalled carbon nanotubepolydimethylsiloxanesmart fabric

Identifiers

PMID37447578
PMCPMC10346702

What OpenQuestion holds

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LicenceCC BY
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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.