Evidence map›Paper›PMID 40407355›Full record

ArticleACS nano2025

Wireless Motion Variability Analysis with Integrated Triboelectric Textiles via Displacement Current.

Yinghong Wu, Sunil Kumar Sailapu, Chiara Spasiano, Carlo Menon

Abstract read
In one paragraph

Article in ACS nano, 2025. 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. 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

4 authors.

Yinghong WuBiomedical and Mobile Health Technology Group, Department of Health Sciences and Technology, ETH Zürich, Lengghalde 5, Zürich 8008, Switzerland.ORCID 0000-0002-2116-5926
Sunil Kumar SailapuBiomedical and Mobile Health Technology Group, Department of Health Sciences and Technology, ETH Zürich, Lengghalde 5, Zürich 8008, Switzerland.ORCID 0000-0002-0923-0879
Chiara SpasianoBiomedical and Mobile Health Technology Group, Department of Health Sciences and Technology, ETH Zürich, Lengghalde 5, Zürich 8008, Switzerland.
Carlo MenonBiomedical and Mobile Health Technology Group, Department of Health Sciences and Technology, ETH Zürich, Lengghalde 5, Zürich 8008, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triboelectric textiles have recently garnered significant attention for their ability to detect and analyze body movements. However, the transmission of wireless signals from natural human motion via integrated triboelectric wearables has been hampered by the reliance on nontextile components, physical interface spacers, and wired connections. Here, we report a wireless biosensing triboelectric wearable system that exploits inherent microgaps within electrospun nanofibers to create a triboelectric textile, seamlessly woven into the garment at various positions. This design enables untethered continuous biosignal monitoring, including those indicative of stride-time variability and joint-time variability analysis from daily activities and exercise. Signals are wirelessly transmitted via displacement current─enhanced by a textile inductor─to an external reader. This innovation enables wireless signal transmission directly from garments without the need for external energy sources. This work advances the development of fully textile-based wireless wearable sensors contributing to next-generation motion tracking, health monitoring, and smart clothing technologies.

Indexed as

Biosensing TechniquesTextilesWearable Electronic DevicesWireless TechnologyHumansMotionNanofibersdisplacement currentmotion variabilitytriboelectric textilewearable technologywireless physiological monitoring

Identifiers

PMID40407355
PMCPMC12164512

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.