Evidence map›Paper›PMID 39341931›Full record

ArticleScientific reports2024

Research on dynamic urine volume detection system based on smart flexible textile sensors.

Fan Xiong, Yunfei Li, Chuanle Xie, Zheng Wang, Jinli Zhou, Hongying Yang, Mengzhao Fan, Chaoran Yang, Junjie Zheng, Chenxiao Wang and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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. 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

11 authors.

Fan XiongCollege of Textile, Zhongyuan University of Technology, Zhengzhou, 450007, Henan, China. 6825@zut.edu.cn.ORCID 0000-0003-3802-7068
Yunfei LiCollege of Textile, Zhongyuan University of Technology, Zhengzhou, 450007, Henan, China.
Chuanle XieSchool of Textiles and Fashion, Shanghai University of Engineering Science, Shanghai, 201620, China.
Zheng WangCollege of Textile, Zhongyuan University of Technology, Zhengzhou, 450007, Henan, China.
Jinli ZhouCollege of Textile, Zhongyuan University of Technology, Zhengzhou, 450007, Henan, China.
Hongying YangCollege of Textile, Zhongyuan University of Technology, Zhengzhou, 450007, Henan, China.
Mengzhao FanCollege of Textile, Zhongyuan University of Technology, Zhengzhou, 450007, Henan, China.
Chaoran YangCollege of Textile, Zhongyuan University of Technology, Zhengzhou, 450007, Henan, China.
Junjie ZhengCollege of Textile, Zhongyuan University of Technology, Zhengzhou, 450007, Henan, China.
Chenxiao WangCollege of Textile, Zhongyuan University of Technology, Zhengzhou, 450007, Henan, China.
Cheng GuoCollege of Textile, Zhongyuan University of Technology, Zhengzhou, 450007, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urine leakage volume is an important indicator reflecting the severity of incontinence in patients. Currently, there are limited smart diapers capable of continuous dynamic monitoring of urine volume. This study developed two types of urine volume sensors, resistive and capacitive, which were integrated with traditional diapers to assess urine leakage levels: mild leakage (0-5 mL), moderate leakage (6-12 mL), and severe leakage (above 12 mL). Three patterns of resistive urine volume sensors were designed, and the results showed that the A pattern could accurately determine urine volume and frequency levels. Additionally, three electrode spacing designs were tested for the capacitive urine volume sensors. The results indicated that the sensor with a 1 cm electrode spacing could determine the urine volume range, with each 1 mL increase in urine causing a capacitance rise of approximately 1.5-1.8 pF, with an error of about ± 0.5 mL per increment. Both resistive and capacitive methods showed high accuracy in monitoring urine volume and frequency. This study validated the feasibility of smart flexible fabric sensors in detecting urine volume and frequency, providing a potential solution for better assessing and managing the condition of incontinence patients.

Indexed as

TextilesElectrodesEquipment DesignHumansUrinary IncontinenceUrineCapacitance methodResistance methodUrinary incontinenceUrinary volume monitoringUrination frequencyWearable fabric

Identifiers

PMID39341931
PMCPMC11439066

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.