Evidence map›Paper›PMID 39040071›Full record

ArticleiScience2024

SolunumWear: A smart textile system for dynamic respiration monitoring across various postures.

Gozde Cay, Dhaval Solanki, Md Abdullah Al Rumon, Vignesh Ravichandran, Kofoworola Omotolani Fapohunda, Kunal Mankodiya

Abstract read
In one paragraph

Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

6 authors.

Gozde CayDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA.
Dhaval SolankiDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA.
Md Abdullah Al RumonDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA.
Vignesh RavichandranDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA.
Kofoworola Omotolani FapohundaDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA.
Kunal MankodiyaDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We introduce SolunumWear, a multi-sensory e-textile system designed for respiration in daily life settings, addressing the gap in continuous, real-world respiration event monitoring. Leveraging a textile pressure sensor belt to capture chest movements and a wireless data acquisition system, SolunumWear offers a promising solution for both medical and wellness applications. The system's efficacy was evaluated through a human study involving 10 healthy adults (six female and four male) across various breathing rates and postures, demonstrating a strong correlation (R value = 0.836) with the gold-standard system. The study highlights the system's computational and communication efficiencies, with latencies of approximately 4.84 s and 2.13 ms, respectively. These findings highlight the efficacy of SolunumWear as a wireless, wearable technology for respiration monitoring in daily settings. This research contributes to the expanding body of knowledge on smart textile-based health monitoring technologies, demonstrating its potential to provide reliable respiratory data in real-world environments.

Indexed as

applied sciencesBiomedical engineeringmaterials application

Identifiers

PMID39040071
PMCPMC11261107

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.