moabb.datasets.Zhou2016#
- class moabb.datasets.Zhou2016[source]#
Motor Imagery dataset from Zhou et al 2016.
PapersWithCode leaderboard: https://paperswithcode.com/dataset/zhou2016-moabb
Dataset summary
#Subj
#Chan
#Classes
#Trials
Trial length
Freq
#Session
#Runs
Total_trials
4
14
3
160
5s
250Hz
3
2
11496
Dataset from the article A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface [1]. This dataset contains data recorded on 4 subjects performing 3 type of motor imagery: left hand, right hand and feet.
Every subject went through three sessions, each of which contained two consecutive runs with several minutes inter-run breaks, and each run comprised 75 trials (25 trials per class). The intervals between two sessions varied from several days to several months.
A trial started by a short beep indicating 1 s preparation time, and followed by a red arrow pointing randomly to three directions (left, right, or bottom) lasting for 5 s and then presented a black screen for 4 s. The subject was instructed to immediately perform the imagination tasks of the left hand, right hand or foot movement respectively according to the cue direction, and try to relax during the black screen.
References
- 1
Zhou B, Wu X, Lv Z, Zhang L, Guo X (2016) A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface. PLoS ONE 11(9). https://doi.org/10.1371/journal.pone.0162657
- data_path(subject, path=None, force_update=False, update_path=None, verbose=None)[source]#
Get path to local copy of a subject data.
- Parameters
subject (int) – Number of subject to use
path (None | str) – Location of where to look for the data storing location. If None, the environment variable or config parameter
MNE_DATASETS_(dataset)_PATH
is used. If it doesn’t exist, the “~/mne_data” directory is used. If the dataset is not found under the given path, the data will be automatically downloaded to the specified folder.force_update (bool) – Force update of the dataset even if a local copy exists.
update_path (bool | None Deprecated) – If True, set the MNE_DATASETS_(dataset)_PATH in mne-python config to the given path. If None, the user is prompted.
verbose (bool, str, int, or None) – If not None, override default verbose level (see
mne.verbose()
).
- Returns
path – Local path to the given data file. This path is contained inside a list of length one, for compatibility.
- Return type
Examples using moabb.datasets.Zhou2016
#
Benchmarking with MOABB showing the CO2 footprint
Examples of how to use MOABB to benchmark pipelines.
Cross-Session on Multiple Datasets
Cache on disk intermediate data processing states
Fixed interval windows processing
Select Electrodes and Resampling
Tutorial 2: Using multiple datasets
Tutorial 3: Benchmarking multiple pipelines