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 Ramirez-Arias
Published: 2021-10-13T14:12:58.736Z
Keywords: Computer Science, Machine Learning, Digital Signal Processing, Feature Extraction, Signal Analysis

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

doi:10.17632/x3jbtstc25.3

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

Published: 13 October 2021| Version 3 | DOI: 10.17632/x3jbtstc25.3

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

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

Description

Files

Steps to reproduce

Institutions

Categories

Licence