EEG dataset of 7-day Motor Imagery BCI

Citation Author(s):: Qing Zhou
Submitted by:: Qing Zhou
Last updated:: Fri, 12/04/2020 - 06:55
DOI:: 10.21227/f1c7-7x89
Data Format:: npz

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Categories:

Keywords:

Motor Imagery;EEG;BCI;

CITE

Abstract

In this dataset, we performed a seven-day motor imagery (MI) based BCI experiment without feedback training on 20 healthy subjects. The MI tasks include left hand, right hand, feet and idle task.

Instructions:

20 healthy subjects (11 males, mean age: 23.2±1.47 years, all right-handed) participated in this study. The recruited subjects were asked to participate seven sessions within two weeks. Each session lasted around 40 minutes and was organized into 6 runs. Subjects could have a short break between runs. During each run, subjects had to perform 40 trials (4 different MI-tasks, 10 trials per task, presented in random order), each trial lasting 9s. The direction of the arrow informed the subjects which task to perform, i.e., the left arrow corresponding to MI of the left hand, the right arrow corresponding to MI of the right hand, down corresponding to MI of both feet, up corresponding to the idle task.

I'm a master student and my team is working on a small machine learning project for authentication using EEG. This dataset has a good amount of information over a span of different days and trials, it is suitable for the task.

Michele Romani Sat, 12/19/2020 - 09:12 Permalink

I'm a research scholar working on EEG limb movement classification. I am searching for a multiclass EEG dataset for my research. This dataset which is collected at different time stamps would help me in doing my research.

bhagyasree K Wed, 03/17/2021 - 11:37 Permalink

I am a PhD student in artificial intelligence, and my research focuses on EEG classification and motor imagery for BCIs. I would be grateful if I could access the data set collected by you. In any case, I want to express my sincere gratitude to you and your colleagues for your efforts. ghezi661@gmail.com

sayyed mahdi ghezi Mon, 09/04/2023 - 18:21 Permalink

This database is recommended.

So far, the study that achieved the highest accuracy rate using this data is:

https://doi.org/10.1080/10255842.2024.2355490

titled: "Authentication with a one-dimensional CNN model using EEG-based brain-computer interface"

yas yas Wed, 07/31/2024 - 11:43 Permalink