SEED-G: Simulated EEG Data Generator for Testing Connectivity Algorithms is a research paper published in Sensors (2021). On theSindex it has a DataRank of 0.494. It has been cited 26 times.
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Base Score Contribution
0.494
From this paper's citation signal
Citation Network Contribution
0
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This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →Sapienza, University of Rome "Progetti di Ateneo"
Grant: RM120172B8899B8C
Sapienza, University of Rome "Progetti di Ateneo"
Grant: RM11715C82606455
Sapienza, University of Rome "Progetti di Ateneo"
Grant: RP11816436CDA44C
Sapienza, University of Rome "Progetti di Ateneo"
Grant: RM11916B88C3E2DE
BitBrain award 2020
Grant: 2962- B2B
National Institutes of Health
Grant: 5R33AT009306-05
Optimization of brain-based mechanisms supporting psychosocial aspects of acupuncture therapy - a hyperscanning fMRI study
FWCI
1.90
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
SEED-G: Simulated EEG Data Generator for testing connectivity algorithms
SEED-G: Simulated EEG Data Generator for testing connectivity algorithms