Evidence map›Paper›PMID 36557367›Full record

ReviewMicromachines2022

Highly Sensitive Self-Powered Biomedical Applications Using Triboelectric Nanogenerator.

Tapas Kamilya, Jinhyoung Park

Abstract readReview
In one paragraph

Review in Micromachines, 2022. 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. Review
  2. Review
  3. Article
  4. Article
  5. 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

2 authors.

Tapas KamilyaSchool of Mechatronics Engineering, Korea University of Technology and Education, Cheonan-si 1600, Republic of Korea.
Jinhyoung ParkSchool of Mechatronics Engineering, Korea University of Technology and Education, Cheonan-si 1600, Republic of Korea.ORCID 0000-0002-5535-3693

Funding

National Research Foundation of Korea 2018R1D1A1B07040446
6 · The paper itself

Abstract

The triboelectric nanogenerator (TENG) is a promising research topic for the conversion of mechanical to electrical energy and its application in different fields. Among the various applications, self-powered bio-medical sensing application has become popular. The selection of a wide variety of materials and the simple design of devices has made it attractive for the applications of real-time self-powered healthcare sensing systems. Human activity is the source of mechanical energy which gets converted to electrical energy by TENG fitted to different body parts for the powering up of the biomedical sensing and detection systems. Among the various techniques, wearable sensing systems developed by TENG have shown their merit in the application of healthcare sensing and detection systems. Some key studies on wearable self-powered biomedical sensing systems based on TENG which have been carried out in the last seven years are summarized here. Furthermore, the key features responsible for the highly sensitive output of the self-powered sensors have been briefed. On the other hand, the challenges that need to be addressed for the commercialization of TENG-based biomedical sensors have been raised in order to develop versatile sensitive sensors, user-friendly devices, and to ensure the stability of the device over changing environments.

Indexed as

biomedical applicationself-powered sensortriboelectric nanogenerator

Identifiers

PMID36557367
PMCPMC9781368

What OpenQuestion holds

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LicenceCC BY
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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.