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Cited by 390

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG

Open access
Mullen, Tim, Kothe, Christian, Chi, Yu Mike, Ojeda, Alejandro, Kerth, Trevor, Makeig, Scott, Cauwenberghs, Gert, Tzyy-Ping Jung·2013·2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

Abstract

This report summarizes our recent efforts to deliver real-time data extraction, preprocessing, artifact rejection, source reconstruction, multivariate dynamical system analysis (including spectral Granger causality) and 3D visualization as well as classification within the open-source SIFT and BCILAB toolboxes. We report the application of such a pipeline to simulated data and real EEG data obtained from a novel wearable high-density (64-channel) dry EEG system.

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Crossref · 10.1109/embc.2013.6609968

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Metadata

Authors
Mullen, T., Kothe, C., Chi, Y. M., Ojeda, A., Kerth, T., Makeig, S., Cauwenberghs, G., & Jung, T.-P.
Venue
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Publisher
IEEE
Published
2013-07
Volume
2013
Pages
2184-2187
OpenAlex
W2020346648
Cited by
390
References
2
FWCI
23.81
Type
conference paper
Language
en
Open access
green

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CoChat. (2026). Citation check: Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG. https://app.cochat.ai/papers/10.1109/embc.2013.6609968
The paper
Mullen, T., Kothe, C., Chi, Y. M., Ojeda, A., Kerth, T., Makeig, S., Cauwenberghs, G., & Jung, T.-P. (2013). Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). https://doi.org/10.1109/embc.2013.6609968

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.