ERP
17 papers with code • 0 benchmarks • 0 datasets
Classification of examples recorded under the Event-Related Potential (ERP) paradigm, as part of Brain-Computer Interfaces (BCI).
A number of ERP datasets can be downloaded using the MOABB library: ERP datasets list
Benchmarks
These leaderboards are used to track progress in ERP
Most implemented papers
A Plug&Play P300 BCI Using Information Geometry
This paper presents a new classification methods for Event Related Potentials (ERP) based on an Information geometry framework.
Early Abandoning and Pruning for Elastic Distances including Dynamic Time Warping
This threshold, provided by the similarity search process, also allows to early abandon the computation of a distance itself.
Changepoint Detection in Noisy Data Using a Novel Residuals Permutation-Based Method (RESPERM): Benchmarking and Application to Single Trial ERPs
Here, we present a new method for detecting a single changepoint in a linear time series regression model, termed residuals permutation-based method (RESPERM).
Towards Fast Single-Trial Online ERP based Brain-Computer Interface using dry EEG electrodes and neural networks: a pilot study
Speeding up the spelling in event-related potentials (ERP) based Brain-Computer Interfaces (BCI) requires eliciting strong brain responses in a short span of time, as much as the accurate classification of such evoked potentials remains challenging and imposes hard constraints for signal processing and machine learning techniques.
Improved robust weighted averaging for event-related potentials in EEG
The areas of improvement include significantly lower averaging error (45% lower RMSE and 37% lower maximum difference than for original implementation) and increased robustness to local minima, strong outliers and corrupted epochs common to real-life EEG signals, especially from low-cost devices.
Automated Pipeline for EEG Artifact Reduction (APPEAR) Recorded during fMRI
In this work, we introduced an open-access toolbox with a fully automatic pipeline for reducing artifacts from EEG data collected simultaneously with fMRI (refer to APPEAR).
Evaluation of convolutional neural networks using a large multi-subject P300 dataset
Convolutional neural networks (CNN) have been compared with baseline traditional models, i. e. linear discriminant analysis (LDA) and support vector machines (SVM) for single trial classification using a large multi-subject publicly available P300 dataset of school-age children (138 males and 112 females).
Interpretable Summaries of Black Box Incident Triaging with Subgroup Discovery
The need of predictive maintenance comes with an increasing number of incidents reported by monitoring systems and equipment/software users.
Pseudocylindrical Convolutions for Learned Omnidirectional Image Compression
limuhit/pseudocylindrical_convolution
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We first describe parametric pseudocylindrical representation as a generalization of common pseudocylindrical map projections.
360° Optical Flow using Tangent Images
Our method leverages gnomonic projection to locally convert ERP images to perspective images, and uniformly samples the ERP image by projection to a cubemap and regular icosahedron vertices, to incrementally refine the estimated 360{\deg} flow fields even in the presence of large rotations.
