Evaluation of temporal, spatial and spectral filtering in CSP-based methods for decoding pedaling-based motor tasks using EEG signals.

Stroke is a neurological syndrome that usually causes a loss of voluntary control of lower/upper body movements, making it difficult for affected individuals to perform Activities of Daily Living (ADLs). Brain-Computer Interfaces (BCIs) combined with robotic systems, such as Motorized Mini Exercise Bikes (MMEB), have enabled the rehabilitation of people with disabilities by decoding their actions and executing a motor task. However, Electroencephalography (EEG)-based BCIs are affected by the presence of physiological and non-physiological artifacts.

Effects of the concentration level, eye fatigue and coffee consumption on the performance of a BCI system based on visual ERP-P300.

Background: A widely used paradigm for Brain-Computer Interfaces (BCI) is based on detecting P300 Event-Related Potentials (ERPs) in response to stimulation and concentration tasks. An open challenge corresponds to maximizing the performance of a BCI by considering artifacts arising from the user's cognitive and physical conditions during task execution.

New Method: In this study, an analysis of the performance of a visual BCI-P300 system was performed under the metrics of Sensitivity (Sen), Specificity (Spe), Accuracy (Acc), and Area-Under the ROC Curve (AUC), considering the main reported factors affecting the neurophysiological behavior of the P300 signal: Concentration Level, Eye Fatigue, and Coffee Consumption.

Comparative analysis of spectral and temporal combinations in CSP-based methods for decoding hand motor imagery tasks.

Background: A widely used paradigm for brain-computer interfaces (BCI) is based on the detection of event-related (des)synchronization (ERD/S) in response to hand motor imagery (MI) tasks. The common spatial pattern (CSP) has been recognized as a powerful algorithm to design spatial filters for ERD/ERS detection. However, a limitation of CSP focus on identification only of discriminative spatial information but not the spectral one.