In tdeenes/eegR: Analyze EEG Signals
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
The eegR package has been developed to analyze EEG (or MEG) signals. It provides all basic functionalities such as data import, filtering, ICA, channel interpolation, re-referencing, segmenting, time-frequency decomposition, complex visualization and statistical analysis of single-trial and averaged ERPs. However, instead of being a comprehensive tool, it has been developed to serve mainly as a general frame which is highly extendable by other, more specialized analytic methods.
Pre-processing
Under pre-processing, we mean the workflow which starts with the import of a raw EEG (or MEG) file and ends up with segmented, "cleaned" signals for each participant.
... to be continued ...
tdeenes/eegR documentation built on April 19, 2021, 4:17 p.m.
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knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
The eegR package has been developed to analyze EEG (or MEG) signals. It provides all basic functionalities such as data import, filtering, ICA, channel interpolation, re-referencing, segmenting, time-frequency decomposition, complex visualization and statistical analysis of single-trial and averaged ERPs. However, instead of being a comprehensive tool, it has been developed to serve mainly as a general frame which is highly extendable by other, more specialized analytic methods.
Pre-processing
Under pre-processing, we mean the workflow which starts with the import of a raw EEG (or MEG) file and ends up with segmented, "cleaned" signals for each participant.
... to be continued ...
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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