Real-time detection of brain events in EEG

@article{Vidal1977RealtimeDO,
  title={Real-time detection of brain events in EEG},
  author={Jacques J. Vidal},
  journal={Proceedings of the IEEE},
  year={1977},
  volume={65},
  pages={633-641}
}
  • J. Vidal
  • Published 1 May 1977
  • Computer Science
  • Proceedings of the IEEE
Evoked responses or event related potentials in human EEG have been mostly studied with off-line analog recording and averaging. [] Key Method The classification is done in real-time by treating the experiments as a signal detection problem in which the computer, in the position of impartial observer, assigns classes to incoming epochs accogding to a predetermined decision rule. Since data collection and processing are interleaved, each classification outcome can be a factor in experiment control as well as…

Figures from this paper

Advanced signal processing techniques for single trial electroencephalography signal classification for brain computer interface applications
TLDR
Two single trial P300 response classification methods were designed and showed better performance than that of the single trial stepwise linear discriminant analysis (SWLDA), which has been considered as the most accurate and practical technique working with P300-BCI Speller.
Methods for Detection of ERP Waveforms in BCI Systems
TLDR
This thesis summarizes the current state of the art of methods for detection of event-related potential waveforms in brain-computer interface systems and recommends an inovative method based on adaptive filtering as the oportunity for inovation.
Analysis of tagging latency when comparing event-related potentials
TLDR
Number of technical aspects which can influence latency such as the refresh rate of the screen or the display of a stimulus at different screen location are presented and a few propositions are suggested to estimate and correct this latency.
A Minimal System for the Study of Relationships between Brain Processes and Psychological Events
TLDR
It is shown how the brain function correlated to cognitive processes may be understood if it is similar to the artificial system which was utilized in the acquisition and information processing system.
A brain-computer interface using motion-onset visual evoked potential.
TLDR
A novel brain–computer interface based on motion-onset visual evoked potentials (mVEPs) and the stepwise linear discriminant analysis is adopted to assess the target detection accuracy of a five-class BCI, suggesting that the proposed mVEP-based BCI could achieve a high information transfer rate in online implementation.
Online Classifier Adaptation in Brain-Computer Interfaces
TLDR
Preliminary offline and online experiments on methods of adapting the classifier while it is being used by the subject are discussed, focusing on the initial training period when the task that the subject is trying to achieve is known and thus supervised adaptation methods can be used.
Single-trial processing of event-related potentials using outlier information
TLDR
It is demonstrated that consistent single-trial motor related information can be successfully extracted using the outlier processing method, and the OPM has been effective in extracting motor-related information from single- trial EEG.
Extracting error-related potentials from motion imagination EEG in noninvasive brain-computer interface
TLDR
This study studied the BCI system that was based on the left-right hand motion imagination (MI) from the offline analysis and online application, and designed and analyzed follow-up study plans that extract the error-related potentials (ErrPs) online in real-time used for cancelling the error command sent by BCI.
Classification and Detection of Single Evoked Brain Potentials Using Time-Frequency Amplitude Features
TLDR
The classification and detection of event-related brain potentials was investigated using signal processing and statistical pattern recognition techniques and features from the time-frequency plane were transformed from the original data sets based upon a two-step classification/feature selection procedure.
Classifier Adaptation in Brain-Computer Interfaces
TLDR
Preliminary offline and online experiments on methods of adapting the classifier while it is being used by the subject are discussed, focusing on the initial training period when the task that the subject is trying to achieve is known and thus supervised adaptation methods can be used.
...
...

References

SHOWING 1-10 OF 28 REFERENCES
INTERACTION BETWEEN THE VISUAL EVOKED RESPONSE AND TWO SPONTANEOUS BIOLOGICAL RHYTHMS: THE EEG ALPHA CYCLE AND THE CARDIAC AROUSAL CYCLE *
TLDR
The interaction between two spontaneous biological rhythms and the visual evoked response is described, and renewed interest in the possibility that photic stimuli might have quite different effects depending upon alpha phase at stimulation can be justified.
Ongoing occipital rhythms and the VER. I. Stimulation at peaks of the alpha-rhythm.
TLDR
Findings suggest that much of the variability in VER recordings may be due to alpha-activity which has been insufficiently attenuated by averaging, and a component occurring in al GVER's which is independent of the alpha-rhythm.
Somatosensory response to stimulus trains in patients with multiple sclerosis.
Factor analysis of evoked potentials.
A multivariate approach to the analysis of average evoked potentials.
  • E. Donchin
  • Mathematics
    IEEE transactions on bio-medical engineering
  • 1966
TLDR
An approach to the quantitative analysis of average evoked potential data is presented and it is assumed to be a sample from a multivariate normal distribution that can be applied to test hypotheses about the similarity or difference of evokes obtained under different conditions.
Composite wavefront decomposition via multidimensional digital filtering of array data
TLDR
The spectral estimation, digital filtering, and the multiwave maximum likelihood estimator developments are demonstrated by the processing of a set of simulated planewaves of various bearings, velocities, and frequencies, as well as by processing electroencephalographic data monitored via an array of scalp electrodes.
BMD : biomedical computer programs
TLDR
This book is very referred for you because it gives not only the experience but also lesson, it is about this book that will give wellness for all people from many societies.
Toward direct brain-computer communication.
  • J. Vidal
  • Computer Science
    Annual review of biophysics and bioengineering
  • 1973
...
...