eeglib: A Python module for EEG feature extraction
Luis Cabañero, Ramón Hervás, Iván Gónzalez, Luis Rodríguez-Benítez
Abstract
Electroencephalography (EEG) signals analysis is non-trivial, thus tools for helping in this task are crucial. One typical step in many studies is feature extraction, however, there are not many tools focused on that aspect. In this paper, eeglib: a Python library for EEG feature extraction is presented. It includes the most popular algorithms when working with EEG and can be easily combined with popular Python libraries. This paper also presents a simple workflow for creating features dataset which allows a high degree of customization and that is suitable for both experts and newcomers.
Topics & Concepts
Python (programming language)Computer scienceWorkflowElectroencephalographyFeature extractionPersonalizationArtificial intelligencePattern recognition (psychology)Programming languageDatabaseWorld Wide WebPsychologyPsychiatryBlind Source Separation TechniquesEEG and Brain-Computer InterfacesNeural Networks and Applications