Factors influencing low intension detection rate in a non-invasive EEG-based brain computer interface system
Motor imagery (MI) responses extracted from the brain in the form of EEG signals have been widely utilized for intention detection in brain computer interface (BCI) systems. However, due to the non-linearity and the non-stationarity of EEG signals, BCI systems suffer from low MI prediction rate with...
Saved in:
Main Authors: | Maswanganyi, Clifford (Author), Tu, Chungling (Author), Owolawi, Pius (Author), Du, Shengzhi (Author) |
---|---|
Format: | EJournal Article |
Published: |
Institute of Advanced Engineering and Science,
2020-10-01.
|
Subjects: | |
Online Access: | Get fulltext |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Through a Glass, Darkly: The Influence of the EEG Reference on Inference About Brain Function and Disorders
Published: (2020) -
ERP and EEG Markers of Brain Visual Attentional Processing
Published: (2020) -
Effect of Infra-Low Frequency Neurofeedback on Infra-Slow EEG Fluctuations
by: Grin-Yatsenko, Vera A., et al.
Published: (2018) -
Non-invasive Brain Stimulation in Neurology and Psychiatry
by: Ignacio Obeso
Published: (2017) -
Use of Non-Invasive Brain Stimulation in Stroke
by: Sultan Tarlaci, et al.
Published: (2012)