Motor Imagery Classification Based on a Recurrent-Convolutional Architecture to Control a Hexapod Robot

Motor Imagery Classification Based on a Recurrent-Convolutional Architecture to Control a Hexapod Robot

Advances in the field of Brain-Computer Interfaces (BCIs) aim, among other applications, to improve the movement capacities of people suffering from the loss of motor skills. The main challenge in this area is to achieve real-time and accurate bio-signal processing for pattern recognition, especiall...

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Bibliographic Details
Main Authors: Tat’y Mwata-Velu, Jose Ruiz-Pinales, Horacio Rostro-Gonzalez, Mario Alberto Ibarra-Manzano, Jorge Mario Cruz-Duarte, Juan Gabriel Avina-Cervantes
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Mathematics
Subjects:
brain-computer interface
EEG motor imagery
CNN-LSTM architectures
real-time motion imagery recognition
Online Access:https://www.mdpi.com/2227-7390/9/6/606

Internet

https://www.mdpi.com/2227-7390/9/6/606

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