Evidence map›Paper›PMID 39459113›Full record

ArticleMicromachines2024

Automated Fabrication of Smart Strain Sensing Threads.

Ege Ozgul, Wenxin Zeng, Sameer Sonkusale

Abstract read
In one paragraph

Article in Micromachines, 2024. 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

3 authors.

Ege OzgulDepartment of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
Wenxin ZengDepartment of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.ORCID 0000-0003-0099-8213
Sameer SonkusaleDepartment of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.

Funding

National Science Foundation 1931978National Science Foundation 1935555National Science Foundation 1951104
6 · The paper itself

Abstract

With favorable properties of stretchability, stitchability, and potential to be woven into a fabric, thread-based sensors have gained considerable interest for wearable devices for smart and connected health applications. To facilitate wearable applications, an easy and reliable way to fabricate these thread-based sensors with good performance and consistency is the key while manufacturing these smart threads. In this paper, we propose an automated thread-coating system that can fabricate thread-based strain sensors with controlled parameters. The platform uses integrated sensors for controlled manufacturing of the threads in a highly compact structure that consists of an innovative tension sensor and a closed-loop thermal management system. Using this new system, a sample thread with a gauge factor of 1.47 and tension sensitivity of 32.64 KΩ/N is prepared. Compared with hand-coated thread, the machine-fabricated thread shows much better sensitivity and consistency. The prepared strain sensor is made into a respiration sensor patch and a limb motion patch to demonstrate its application.

Indexed as

automationhuman body monitoringstrain sensorthread sensor

Identifiers

PMID39459113
PMCPMC11509538

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.