FingerMovements {mlmts}

FingerMovements

Description

Multivariate time series (MTS) indicating the finger movements of a subject while typing at a computer keyboard.

Usage

data(FingerMovements)

Format

A list with two elements, which are:

data

A list with 416 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 50 rows (time points) indicating EEG observations and 28 columns (variables) indicating EEG channel. The first 316 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 a different side (left and right). For more information, see Bagnall et al. (2018). Run "install.packages("ueadata1", repos="https://anloor7.github.io/drat")" to access this dataset and use the syntax "ueadata1::FingerMovements".

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.