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Review
. 2024 Mar 7;10(6):e27399.
doi: 10.1016/j.heliyon.2024.e27399. eCollection 2024 Mar 30.

Two Decades' advancements and Research trends in needle-type Sensor technology: A scientometric analysis

Guangyi Yang  1 , Wenjing Xu  1 , Botan Xu  2 , Yi Yang  3 , Pengwei Li  1 , Aotian Yu  1 , Simin Ning  1 , Qixuan Fu  1 , Rong Zhang  4 , Xiaohan Liu  5
Affiliations
Review

Two Decades' advancements and Research trends in needle-type Sensor technology: A scientometric analysis

Guangyi Yang et al. Heliyon. .

Abstract

Needle-type sensor, characterized by its slender, elongated shape, is a promising sensing method due to its rapid response, high sensitivity, and portability. Recently, the needle-type sensor technology has garnered increasing attention, leading to its accelerated development and extensive use in medical and healthcare, environmental monitoring, and geosciences. However, there remains a need for a comprehensive review of existing research. Here, we utilize scientometric analysis, which is booming recently, to conduct a comprehensive investigation of the needle-type sensor field. This analysis covers various aspects, including annual trends, journals, institutions, countries, disciplines, authors, references, and keywords of 136,667 publications from the Web of Science Core Collection (WoSCC) database spanning from January 1, 2004, to January 1, 2024. Additionally, we identify current hotspots, frontiers, and predict future trends. Eventually, three research hotspots are refined: multidisciplinary materials science, sensor miniaturization and integration, and biomedical engineering, indicating that further investigations may focus on creating biocompatible materials to enhance sensing properties, optimizing sensor structure through miniaturization and integration methods, and improving clinical applications in biomedical engineering. This work may facilitate the development of needle-type sensors.

Keywords: Biomedical engineering; CiteSpace; Knowledge graph; Needle-type sensor; Scientometric.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
Flow chart of the scientometric analysis in this paper.
Fig. 2
Fig. 2
The annual trends of publications and citations. The annual trend of publications (a), and the annual trend of citations (b), respectively.
Fig. 3
Fig. 3
Top 10 journals of publications.
Fig. 4
Fig. 4
Country co-occurrence network.
Fig. 5
Fig. 5
Institution co-occurrence network.
Fig. 6
Fig. 6
Author co-occurrence network with 4 obvious cooperative teams (a-d).
Fig. 7
Fig. 7
Discipline category network.
Fig. 8
Fig. 8
Keyword co-occurrence network.
Fig. 9
Fig. 9
Keywords cluster network. The keywords are divided into 18 clusters of different colors according to the LLR algorithms (a), the timeline and detailed information of each cluster (b). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 10
Fig. 10
Top 25 keywords with the strongest citation burst.
See this image and copyright information in PMC

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