Study of the human brain potentials variability effects in P300 based brain–computer interface
Citations Over Time
Abstract
The P300-based brain–computer interfaces (P300 BCI) allow the user to select commands by focusing on them. The technology involves electroencephalographic (EEG) representation of the event-related potentials (ERP) that arise in response to repetitive external stimulation. Conventional procedures for ERP extraction and analysis imply that identical stimuli produce identical responses. However, the floating onset of EEG reactions is a known neurophysiological phenomenon. A failure to account for this source of variability may considerably skew the output and undermine the overall accuracy of the interface. This study aimed to analyze the effects of ERP variability in EEG reactions in order to minimize their influence on P300 BCI command classification accuracy. Healthy subjects aged 21–22 years (n = 12) were presented with a modified P300 BCI matrix moving with specified parameters within the working area. The results strongly support the inherent significance of ERP variability in P300 BCI environments. The correction of peak latencies in single EEG reactions provided a 1.5–2 fold increase in ERP amplitude with a concomitant enhancement of classification accuracy (from 71–78% to 92–95%, p < 0.0005). These effects were particularly pronounced in attention-demanding tasks with the highest matrix velocities. The findings underscore the importance of accounting for ERP variability in advanced BCI systems.
Related Papers
- → A Review on Electroencephalogram Based Brain Computer Interface for Elderly Disabled(2019)104 cited
- → Multichannel spectral pattern separation - An EEG processing application -(2009)26 cited
- → Universal neurophysiological interpretation of EEG brain-computer interfaces(2021)4 cited
- Localization of Brain Activity in Electroencephalography Data during Brain-Computer Interface Operation(2011)
- → Translation of Brain Activity Patterns of a user into Commands using Electroencephalography (EEG)(2021)