Tradeoff between User Experience and BCI Classification Accuracy with Frequency Modulated Steady-State Visual Evoked Potentials
Steady-state visual evoked potentials (SSVEPs) have been widely employed for the control of brain-computer interfaces (BCIs) because they are very robust, lead to high performance, and allow for a high number of commands. However, such flickering stimuli often also cause user discomfort and fatigue,...
Main Authors: | Alexander M. Dreyer, Christoph S. Herrmann, Jochem W. Rieger |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2017-07-01
|
Series: | Frontiers in Human Neuroscience |
Subjects: | |
Online Access: | http://journal.frontiersin.org/article/10.3389/fnhum.2017.00391/full |
Similar Items
-
Comparing Steady-State Visually Evoked Potentials Frequency Estimation Methods in Brain-Computer Interface With the Minimum Number of EEG Channels
by: Mehrnoosh Neghabi, et al.
Published: (2019-05-01) -
A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI
by: Piotr Stawicki, et al.
Published: (2017-04-01) -
EEGNet With Ensemble Learning to Improve the Cross-Session Classification of SSVEP Based BCI From Ear-EEG
by: Yuanlu Zhu, et al.
Published: (2021-01-01) -
Comparison of Different Visual Feedback Methods for SSVEP-Based BCIs
by: Mihaly Benda, et al.
Published: (2020-04-01) -
Classification of Bipolar Disorder and Schizophrenia Using Steady-State Visual Evoked Potential Based Features
by: Fatemeh Alimardani, et al.
Published: (2018-01-01)