Global research on artificial intelligence-enhanced human electroencephalogram analysis

Abstract

The application of artificial intelligence (AI) technologies in assisting human electroencephalogram (EEG) analysis has become an active scientific field. This study aims to present a comprehensive review of the research field of AI-enhanced human EEG analysis. Using bibliometrics and topic modeling, research articles concerning AI-enhanced human EEG analysis collected from the Web of Science database during the period 2009-2018 were analyzed. After examining 2053 research articles published around the world, it was found that the annual number of articles had significantly grown from 78 to 468, with the USA and China being the most influential and prolific. The results of the keyword analysis showed that ''electroencephalogram,'' ''brain-computer interface,'' ''classification,'' ''support vector machine,'' ''electroencephalography,'' and ''signal'' were the most frequently used. The results of topic modeling and evolution analyses highlighted several important issues, including epileptic seizure detection, brain-machine interface, EEG classification, mental disorders, emotion, and alcoholism and anesthesia. The findings suggest that such visualization and analysis of the research articles could provide a comprehensive overview of the field for communities of practice and inquiry worldwide.

Overview of global publications on machine learning in diabetic retinopathy from 2011 to 2021: Bibliometric analysis

“…The publication pattern reveals that India and China have been the most productive countries. The two densely populated developing countries contributed to nearly half of the relevant publications, which is uncommon in other bibliometric studies on the topic of AI technologies in medicine ( 17 , 25 ), as developed countries such as the USA or England are usually the main force. In addition, there are 5 developing countries in the top 10 countries ranked by publication count, all with considerable academic output.…”

“…The Hirsch-index (H-index) was used originally to reflect the academic impact of a researcher, which describes that a researcher has published h number of articles, and each of the h articles has at least h times of citations ( 23 , 24 ). Currently, the H-index is commonly used for assessing the academic influence of countries/institutions/journals in the bibliometric analysis ( 25 ). The growth rate of publications was calculated as follows:…”

A scholarly network of AI research with an information science focus: Global North and Global South perspectives

“…For example, de Sousa et al [9] conducted a systematic literature review to identify research topics and trends relating to AI in the public sector. Chen et al [10,11] performed a bibliometric analysis to investigate AI-related applications in the medical field, such as an AI-enhanced electroencephalogram method for conducting human brain research. Other educators have combined bibliometric and content analysis to explore mainstream AI-assisted education research [12,13].…”

“…In the present study, a co-citation network analysis was conducted to compare the GN and GS with respect to scholarly networks of AI research in the IS domain during the period from 2010 to 2020. Furthermore, to allow for research trend comparisons with the findings of other studies [10][11][12][13], the research period for this study was divided into two intervals (i.e., 2010-2015 and 2016-2020). Overall, the present study provides a fresh perspective on the global research dynamics of the scholarly network of AI research in the IS field.…”

Improving healthcare outcomes using multimedia big data analytics

“…To further show the gain in performance and effectiveness of the framework, an occlusion sensitivity analysis was performed that shows the contribution of the cortical area for classification. Chen et al analyzed the recent research on EEG and the impact of technology in achieving the objectives [ 4 ].…”