MotorImagery {mlmts}

MotorImagery

Description

Multivariate time series (MTS) involving imagined movements performed by a subject with either the left small finger or the tongue. The time series of the electrical brain activity were stored during the corresponding trials

Usage

data(MotorImagery)

Format

A list with two elements, which are:

data

A list with 378 MTS.

classes

A numeric vector indicating the corresponding classes associated with the elements in data.

Details

Each element in data is a matrix formed by 3000 rows (time points) indicating time recordings in EEG and 64 columns (variables) indicating EEG electrodes. The first 278 elements correspond to the training set, whereas the last 100 elements correspond to the test set. The numeric vector classes is formed by integers from 1 to 2, indicating that there are 2 different classes in the database. Each class is associated with the label 'finger' or 'tongue' (the imagined movements). For more information, see Bagnall et al. (2018). To access this dataset, execute the code "install.packages("ueadata2", repos="https://anloor7.github.io/drat")" and use the following syntax: "ueadata2::MotorImagery".

References

Bagnall A, Dau HA, Lines J, Flynn M, Large J, Bostrom A, Southam P, Keogh E (2018). “The UEA multivariate time series classification archive, 2018.” arXiv preprint arXiv:1811.00075.

Ruiz AP, Flynn M, Large J, Middlehurst M, Bagnall A (2021). “The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances.” Data Mining and Knowledge Discovery, 35(2), 401–449.

Bagnall A, Lines J, Vickers W, Keogh E (2022). “The UEA & UCR Time Series Classification Repository.” www.timeseriesclassification.com.