Habituation of P300 in the Use of P300-based Brain-Computer Interface Spellers: Individuals With Amyotrophic Lateral Sclerosis Versus Age-Matched Controls

Relation Between Sensorimotor Rhythm During Motor Attempt/Imagery and Upper-Limb Motor Impairment in Stroke

Motor attempt (MA)/motor imagery (MI)-based brain-computer interface (BCI) is a newly developing rehabilitation technology for motor impairment. This study aims to explore the relationship between electroencephalography sensorimotor rhythm and motor impairment to provide reference for a BCI design. Twenty-eight stroke survivors with varying levels of motor dysfunction and spasticity status in the subacute or chronic stage were enrolled in the study to perform MA and MI tasks. Event-related desynchronization (ERD)/event-related synchronization (ERS) during and immediately after motor tasks were calculated. The Fugl-Meyer assessment scale (FMA) and the modified Ashworth scale (MAS) were applied to characterize upper-limb motor dysfunction and spasticity. There was a positive correlation between FMA total scores and ERS in the contralesional hemisphere in the MI task (P < .05) and negative correlations between FMA total scores and ERD in both hemispheres in the MA task (P < .05). Negative correlations were found between MAS scores of wrist flexors and ERD in the ipsilesional hemisphere (P < .05) in the MA task. It suggests that motor dysfunction may be more correlated to ERS in the MI task and to ERD in the MA task while spasticity may be more correlated to ERD in the MA task.

Investigating the effects of stimulus duration and inter-stimulus interval parameters on P300 based BCI application performance

The main goal of electroencephalography (EEG) based brain-computer interface (BCI) research is to develop a fast and higher classification accuracy (CA) rate method than those of existing ones. Generally, in BCI applications, either motor imagery or event-related P300 based techniques are used for data recording. The stimulus duration (SD) and the inter-stimulus interval (ISI) are crucial two parameters directly affecting the decision speed of the BCI system. In this study, we investigated the performance of the P300 based application in terms of speed and CA for three kinds of protocols which are called fast, medium, and slow included different SD and the ISI values. The training and test data sets were recorded in one week of delay from 8 subjects. The features were extracted by standard deviation, variance, mean, Wavelet Transform and Fourier Transform techniques. Afterwards, they were classified by the k-nearest neighbor algorithm. We obtained 87.08%, 85.41% and 83.95% average CA rate for the fast, medium, and slow protocols, respectively. The obtained results showed that the proposed fast protocol method achieved CA rate between 78.33% and 93.33%. Based on the obtained results, it can be concluded that the fast protocol values can be used for establishing a more accurate and faster P300 based BCI.