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Control of Upper and Lower Limb Prostheses using a Real-Time EEG Signal Classification System

Hey everyone!

In this work an experimental methodology was developed using OpenBCI for the acquisition of EEG signals from 24 volunteer subjects. The volunteers are work and research colleagues from ESPOL University.

EEG signal preprocessing techniques are used to eliminate noise components. In addition, feature extraction algorithms were used to extract features from each EEG electrode. Next, some classifiers were trained and those with the highest accuracy were selected. Finally, the best classifiers were used to classify motor tasks in real-time and control two active prostheses.

Source codes:

https://github.com/Human-Machine-Interface

Some related work includes the following:

https://ieeexplore.ieee.org/abstract/document/9399035

https://ieeexplore.ieee.org/document/9096752

https://ieeexplore.ieee.org/abstract/document/8247451

Read more information about the author:

https://orcid.org/0000-0002-2786-4162

https://vasanza.blogspot.com/

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