• Elaine Huang

Transformer Convolutional Neural Networks for Automated Artifact Detection in Scalp EEG

We're very excited to share the innovative findings on Transformer Convolutional Neural Networks for Automated Artifact Detection in Scalp EEG of which our Co-founder and CSO Dr. Justin Dauwels presented at the 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society held in Glasgow, Scotland earlier this month.


Electroencephalograms (EEGs) often contain artifacts due to muscle activity, eye blinks, and various other causes. Detecting such artifacts is an essential first step toward a correct interpretation of EEGs. Although much effort has been devoted to automating artifact detection, the problem remains challenging and unresolved.


If you are interested in learning more about the methods used and results achieved, please feel free to download the research poster below and reach out to us with any questions or comments!

TransformerCNNforAutomatedArtifactDetectioninScalpEEG
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