StandWalkJump {mlmts}

StandWalkJump

Description

Multivariate time series (MTS) involving short duration ECG signals recorded from a healthy 25-year-old male performing different physical activities

Usage

data(StandWalkJump)

Format

A list with two elements, which are:

data

A list with 27 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 2500 rows (time points) indicating readings in a spectrogram and 4 columns (variables) indicating frequency band from the spectrogram. The first 12 elements correspond to the training set, whereas the last 15 elements correspond to the test set. The numeric vector classes is formed by integers from 1 to 3, indicating that there are 3 different classes in the database. Each class is associated with the label 'standing', 'walking' or 'jumping'. For more information, see Bagnall et al. (2018).

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.