Mahmoud Eid
Have been working in Brain-computer interfacing projcets involving EEG signals and machine/deep learning for 10 years and developed a toolbox for the analyses of EEGs as well as classification models, this toolbox is called lively vectors:
latest project demo:
https://youtu.be/Lc7IN0ot0Q4
Can be used for EEG analyses and other multivariate data, can be used with videos, speech, data from sensors, etc.
Can be given custom-built pipeline steps and perform them, it includes visualisation with statistical outcomes.
Includes segmentation, filtering, and cleaning of signals and rejection of noisy samples/trials/channels automatically and via visual inspection.
Includes different methods for feature extraction.
Includes different analyses such as: time domain analyses ( ERP analysis ), frequency domain analysis, time frequency analysis (TF analysis), spatial filtering, source separation, intertrial phase consistency (ITPC), cross-correlation and signal alignment, phase amplitude coupling (PAC), representative similarity analysis (RSA), LDA beamforming, and more.
Includes classification:Linear discriminant analysis (LDA), support vector machine (SVM), random forests, Riemannian geometry-based classifiers . Neural networks (NNs), Recurrent neural networks (RNNs), Convolutional neural networks (CNNs) for classification and feature extraction, Temporal convolutional networks (TCN) and more classifiers.
Includes sleep analyses:Detects slow oscillations (SOs), sleep spindles, theta activity and other activities that can be provided in a custom file, thus it could detect new activities/patterns if their specifications are provided.
Includes statistical analyses:Provides correction for multiple comparisons in 1d and 2d with cluster-based permutation tests and also correction in space. Includes parametric and non-parametric tests for significance. Visualises correlations with statistics. Visualises statistical results with p-values.
Calls some functions from fieldtrip toolbox, and some functions from few toolboxes that are relevant for some analyses.