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Bibliometric evaluation of 2000–2019 publications on functional near-infrared spectroscopy.
- Source :
-
NeuroImage . Oct2020, Vol. 220, pN.PAG-N.PAG. 1p. - Publication Year :
- 2020
-
Abstract
- This study aimed to explore and analyze research trends and frontiers on functional near-infrared spectroscopy (fNIRS) in the past 20 years and identify collaboration networks. fNIRS-related publications from 2000 to 2019 were retrieved from the Web of Science database. A total of 1727 publications satisfied the search criteria. Bibliometric visualization analysis of active authors, journals, institutions, countries, references, and keywords were conducted. The number of annual related publications remarkably increased over the years. Fallgatter published the largest number of fNIRS-related papers (83). Neuroimage not only had the largest number of papers published in the first 10 journals (157 articles) but also had the highest impact factor (IF, 2018 = 5.812). The University of Tubingen had the highest number of fNIRS-related publications in the past 20 years. The United States ranked first in terms of comprehensive influence in this field. In recent years, burst keywords (e.g., infant, social interaction, and older adult) and a series of references with citation burst provided clues on research frontiers. • This study analyzed research trends on functional near-infrared spectroscopy (fNIRS) in the past 20 years. • The most recent burst keywords were "infant", "social interaction" and "older adult" in fNIRS. • Neuroimage contributed the highest number of publications on fNIRS research. • FNIRS research had grown remarkably over the past 20 years and had a promising future. [ABSTRACT FROM AUTHOR]
- Subjects :
- *SPECTROMETRY
*OLDER people
*WEB databases
*SCIENCE databases
*SOCIAL interaction
Subjects
Details
- Language :
- English
- ISSN :
- 10538119
- Volume :
- 220
- Database :
- Academic Search Index
- Journal :
- NeuroImage
- Publication Type :
- Academic Journal
- Accession number :
- 146397980
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2020.117121