Mapping the Global Landscape and Thematic Evolution of fNIRS-Gait Research: A Systematic Bibliometric and Network Visualization Analysis
Bioengineering, cilt.13, sa.10, ss.1-26, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 13 Sayı: 10
- Basım Tarihi: 2026
- Doi Numarası: 10.3390/bioengineering13101198
- Dergi Adı: Bioengineering
- Derginin Tarandığı İndeksler: Academic Search Ultimate (EBSCO), Natural Science Collection (ProQuest), Biological Science Database (ProQuest), Scopus, Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest), Science Citation Index Expanded (SCI-EXPANDED), BIOSIS, INSPEC, Directory of Open Access Journals
- Sayfa Sayıları: ss.1-26
- Ankara Üniversitesi Adresli: Evet
Özet
Abstract
Background: Functional near-infrared spectroscopy (fNIRS) has emerged as an essential optical neuroimaging modality in human locomotion, yet a comprehensive computational mapping of its structural and thematic evolution remains absent. This study provides a systematic, data-driven scientometric evaluation of the global fNIRS-gait research landscape across a quarter-century (2002–April 2026). Methods: A refined corpus of 348 peer-reviewed documents from the Web of Science Core Collection was computationally analyzed using VOSviewer and Bibliometrix. Results: The literature exhibits a 12.53% compound annual growth rate, shifting from stationary motor imagery toward ecologically valid overground walking. The United States leads global outputs, supported by European collaborative corridors and Chinese national infrastructures. Healthy aging (27.30%), Parkinson’s disease (10.92%), and stroke (9.20%) represent the primary clinical subdomains, centering on prefrontal cortex hyper-activation during dual-task walking (20.11%). Frontiers have migrated toward multimodal Mobile Brain/Body Imaging (MoBI) integrating virtual reality, exoskeletons, and machine learning. However, technical integration is hindered by severe signal processing heterogeneity and unstandardized short-separation channel regressions. Conclusions: Establishing standardized preprocessing pipelines and short-separation regressions may prove pivotal for transitioning mobile neuroimaging into objective, closed-loop clinical neurorehabilitation.