DavidVivancos/MindBigData2022

MindBigData 2022 is a large-scale EEG signal dataset comprising three primary datasets and their sub-datasets. The data were collected using various EEG devices such as MindWave, EPOC1, Muse1, Insight1, etc., with detailed sampling rates and channel information. The dataset is split into 80% training and 20% testing, containing both labels and EEG recordings. Each sub-dataset has specific device and sampling‑rate configurations. Specifically: 1. MindBigData MNIST of Brain Digits – four sub-datasets based on MindWave, EPOC1, Muse1, and Insight1; 2. MindBigData Imagenet of the Brain – two sub-datasets based on Insight1 EEG signals and spectrograms; 3. MindBigData Visual MNIST of Brain Digits – three sub-datasets based on Muse2, Cap64, and Cap64 Morlet devices.

Updated 1/7/2023

hugging_face

Description

MindBigData 2022 A Large Dataset of Brain Signals

1. MindBigData MNIST of Brain Digits

Data source: http://mindbigdata.com/opendb/index.html
Data split: 80% Train, 20% Test
Data processing: EEG signals are resampled to match the original headset sampling rate, include head information, and the simplified data contain only labels and EEG recordings
Sub‑datasets:
- MindWave1: 1 EEG Channel, 1024 samples × Channel
- EPOC1: 14 EEG Channels, 256 samples × Channel
- Muse1: 4 EEG Channels, 440 samples × Channel
- Insight1: 5 EEG Channels, 256 samples × Channel

2. MindBigData Imagenet of the Brain

Data source: http://mindbigdata.com/opendb/imagenet.html
Data split: 80% Train, 20% Test
Data processing: Includes ILSVRC2013 class labels, one‑hot name list, RGB pixel values resampled to 150×150, and EEG data
Sub‑datasets:
- Insight1 EEG: 5 EEG Channels, 384 samples per channel
- Insight1 Spectrogram: 64×64‑pixel spectrograms replace EEG

3. MindBigData Visual MNIST of Brain Digits

Data source: http://mindbigdata.com/opendb/visualmnist.html
Data split: 80% Train, 20% Test
Data processing: Includes labels, original MNIST pixels of 28×28, and EEG data
Sub‑datasets:
- Muse2: 5 EEG Channels, 3 PPG Channels, 3 ACC Channels, 3 GYR Channels, 512 samples × Channel
- Cap64: 64 EEG Channels, 400 samples × Channel
- Cap64 Morlet: 64 EEG Channels, 400 samples × Channel, uses Morlet PNG images as EEG output

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Topics

Neuroscience

Machine Learning

Source

Organization: hugging_face

Created: Unknown

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