Deep Fusion Feature Learning Network for MI-EEG Classification

Brain-computer interfaces (BCIs) are used to provide a direct communication between the human brain and the external devices, such as wheelchairs and intelligent apparatus, by interpreting the electroencephalograph (EEG) signals. Recently, motor imagery EEG (MI-EEG) has become an active research fie...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access 2018, Vol.6, p.79050-79059
Hauptverfasser:	Yang, Jun, Yao, Shaowen, Wang, Jin
Format:	Artikel
Sprache:	eng
Schlagworte:	Biological neural networks Convolution convolutional neural networks (CNN) Correlation Datasets Decoding Deep learning Discrete Wavelet Transform Discrete wavelet transforms Electrodes Electroencephalography Feature extraction Human-computer interface Imagery long short-term memory (LSTM) Machine learning Motor imagery electroencephalograph (MI-EEG) brain computer interfaces (BCI) Performance evaluation Representations Signal classification Spatial data System effectiveness Training Wheelchairs
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!