Staff View: Discriminating mental states by extracting relevant spatial patterns under non-stationary
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Motor imagination is an important area of brain-computer interface. In recent years, the
application of deep learning algorithms has further improved the recognition rate of motor …

This Study proposed Firefly-Support vector machine (FASVM) method to improve the
accuracy of EEG motor imagery signals classification. Redundancy of features in EEG signal …

Use of Motor Imagery in EEG signals is gaining importance to develop Brain Computer
Interface (BCI) applications in various fields ranging from bio-medical to entertainment and …

Cognitive sensing in the brain–computer interface: a comprehensive study - Book chapter -
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Interfaces Cérebro-Máquina baseadas em Imagética Motora (ICM-IM) permitem o controle
de dispositivos independente do uso de nervos e músculos periféricos, a partir da …

Decoding continuous brain intentions is a major challenge for the research and application
of brain-computer interfaces (BCI). Neuronal activity has been experimentally observed …

In this paper, we propose a novel feature extraction method for pattern classification
problem. We propose to map the original data to subspaces for feature extraction and hope …

Achieving consistent accuracy still big challenge in EEG based Motor Imagery classification
since the nature of EEG signal is non-stationary, intra-subject and inter-subject dependent …

Motor imagery brain-computer interface (MI-BCI) is well approved to help people with
movement impairments due to neural disorders. The procedure for MI-BCI to translate MI …