A dataset of features for robotic limb movement classification through EEG signals

Name: A dataset of features for robotic limb movement classification through EEG signals
Creator: Francisco Javier Ramírez-Arias
Published: 2021-10-18T07:20:17.772Z
Keywords: Computer Science, Machine Learning, Feature Extraction, Signal Analysis, Electroencephalography

Ramírez-Arias, Francisco Javier; García-Guerrero, Enrique Efrén; López-Bonilla, Oscar Roberto; Colores-Vargas, Juan Miguel; Galindo-Aldama, Gilberto Manuel; Aguirre-Castro, Oscar Adrián; Inzunza-González, Everardo

doi:10.17632/52mvs9mfw3.1

A dataset of features for robotic limb movement classification through EEG signals

Published: 18 October 2021| Version 1 | DOI: 10.17632/52mvs9mfw3.1

Contributors:

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Description

Each dataset refers to a specific frequency band: Delta, Theta, Alpha, Beta, and Gamma.

Files

Steps to reproduce

Steps to reproduce 1) Load the dataset by using scientific software like Matlab or Python. 2) Do preprocessing. 3) Train a machine learning model. 4) Test and validate the model.

Institutions

Universidad Autonoma de Baja California, Universidad Autonoma de Baja California - Campus Tijuana, Universidad Autonoma de Baja California - Campus Ensenada

A dataset of features for robotic limb movement classification through EEG signals

Description

Files

Steps to reproduce

Institutions

Categories

Licence