EEGLAB is a widely used software for analyzing electroencephalography (EEG) datasets, with over 20 years of global use. This bibliometric study investigates EEGLAB publications in the Asia-Pacific and Arabian regions, focusing on Scopus and Web of Science (WoS) indexed sources, to understand regional contributions and trends in EEG research across 80 countries and territories.
Methods
Bibliometric analysis was conducted using the Bibliometrix package in R, focusing on citations from WoS and Scopus indexed sources. The study covers data from the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) and West Asia (ESCWA), including 58 ESCAP countries and 22 ESCWA countries, with data collected until March 2024. Bibliometric indices such as Lotka's law, Bradford's law, co-citation networks, and in-depth historiography were analyzed to explore global and regional trends.
Results
EEGLAB's main article has received 22 298 citations on Google Scholar, with 14 958 (67.1%) citations in WoS and 15 827 (70.1%) in Scopus. The top ten WoS countries by citations are China, Australia, Japan, Republic of Korea, India, Iran, Russian Federation, Singapore, New Zealand, and Malaysia/Türkiye. Recent research themes include emotion recognition, driver distraction detection, deep learning, schizophrenia detection, and the cognitive impacts of COVID-19. China and the USA are the leading international collaborators.
Conclusions
Approximately 35% of WoS documents and 41% of authors are from the ESCAP and ESCWA regions. The average citation per document in these regions is half of the global average. The study highlights EEGLAB's growing role in EEG research and collaborative trends.
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