Comparative Analysis of Deep Learning Models for Optimal EEG-Based Real-Time Servo Motor Control

This study harnesses EEG signals to enable the real-time control of servo motors, utilizing the OpenBCI Community Dataset to identify and assess brainwave patterns related to motor imagery tasks. Specifically, the dataset includes EEG data from 52 subjects, capturing electrical brain activity while...

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Veröffentlicht in:	Eng (Basel, Switzerland) Jg. 5; H. 3; S. 1708 - 1736
Hauptverfasser:	Angelakis, Dimitris, Ventouras, Errikos C., Kostopoulos, Spiros, Asvestas, Pantelis
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.09.2024
Schlagworte:	Accuracy Algorithms Artificial neural networks Brain research Classification Communication Datasets Deep learning deep neural network EEG signals Electrodes Electroencephalography Harnesses Imagery Information processing LSTM Machine learning Memory Multilayer perceptrons Neural networks Outdoor activities Performance measurement Performance prediction Python Real time real-time control Recurrent neural networks Robot control Robotics servo Servocontrol Servomechanisms Servomotors Signal processing Wavelet transforms
ISSN:	2673-4117, 2673-4117
Online-Zugang:	Volltext
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