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# MindBigData 2022 A Large Dataset of Brain Signals |
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> Supporting datasets for paper [ arXiv:2212.14746](https://arxiv.org/abs/2212.14746) |
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> There are 3 Main datasets with subdatasets: |
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**1.- MindBigData MNIST of Brain Digits** |
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> based on http://mindbigdata.com/opendb/index.html |
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> But all datasets splitted to 80% Train 20% Test (also proportional in the 11 classes) |
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> EEG's Resampled to match original headsets sampling rate |
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> Included headers. |
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> and simplified to contain only label & EEG data as rows named in headers as ChannelName-SampleNum, ie for channel FP1 and MindWave will be FP1-0 FP1-1 ..... FP1-1023 since there are 1024 samples. |
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> There are 4 subdatasets: |
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> For MindWave with 1 EEG Channel and 1024 samples x Channel |
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> For EPOC1 with 14 EEG Channels and 256 samples x Channel |
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> For Muse1 with 4 EEG Channels and 440 samples x Channel |
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> For Insight1 with 5 EEG Channels and 256 samples x Channel |
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**1.1.- MindBigData MNIST of Brain digits MindWave1** |
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https://huggingface.co/datasets/DavidVivancos/MindBigData2022_MNIST_MW |
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**1.2.- MindBigData MNIST of Brain digits EPOC1** |
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https://huggingface.co/datasets/DavidVivancos/MindBigData2022_MNIST_EP |
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**1.3.- MindBigData MNIST of Brain digits Muse1** |
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https://huggingface.co/datasets/DavidVivancos/MindBigData2022_MNIST_MU |
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**1.4.- MindBigData MNIST of Brain digits Insight1** |
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https://huggingface.co/datasets/DavidVivancos/MindBigData2022_MNIST_IN |
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**2.- MindBigData Imagenet of the Brain** |
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> based on http://mindbigdata.com/opendb/imagenet.html |
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> But all datasets splitted to 80% Train 20% Test (also proportional in all the classes) |
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> EEG's Resampled to match original headsets sampling rate |
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> Included headers. |
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> contains label as the ILSVRC2013 category, and a hotencoded name lists, the RGB pixel values of the image seen resampled to 150pixels by 150 pixels & EEG data as rows named in headers as ChannelName-SampleNum, |
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> There are 2 subdatasets: |
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> One with the Insight 1 EEG signals at 384 samples per channel (5 channels) |
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> One with the Spectrogram image 64x64px instead of the EEG as described in the paper |
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**2.1.- MindBigData Imagenet of the Brain Insight1 EEG** |
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https://huggingface.co/datasets/DavidVivancos/MindBigData2022_Imagenet_IN |
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**2.2.- MindBigData Imagenet of the Brain Insight1 Spectrogram** |
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https://huggingface.co/datasets/DavidVivancos/MindBigData2022_Imagenet_IN_Spct |
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**3.- MindBigData Visual MNIST of Brain Digits** |
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> based on http://mindbigdata.com/opendb/visualmnist.html |
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> But all datasets splitted to 80% Train 20% Test (also proportional in the 11 classes) |
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> Included headers. |
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> and simplified to contain only label, the original MNIST pixels of the digit seen 28x28pixels & EEG data as rows named in headers as ChannelName-SampleNum, ie for channel TP9 and Muse2 will be TP9-0 TP9-1 ..... TP9-511 since there are 512 samples. |
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> There are 3 subdatasets: |
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> For Muse2 with 5 EEG Channels, 3 PPG Channels, 3 ACC Channels & 3 GYR Channels and 512 samples x Channel |
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> For Cap64 with 64 EEG Channels and 400 samples x Channel |
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> For Cap64 with 64 EEG Channels and 400 samples x Channel but with Morlet png images as EEG outputs |
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**3.1.- MindBigData Visual MNIST of Brain digits Muse2** |
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https://huggingface.co/datasets/DavidVivancos/MindBigData2022_VisMNIST_MU2 |
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**3.2.- MindBigData Visual MNIST of Brain digits Cap64** |
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https://huggingface.co/datasets/DavidVivancos/MindBigData2022_VisMNIST_Cap64 |
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**3.3.- MindBigData Visual MNIST of Brain digits Cap64 Morlet** |
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https://huggingface.co/datasets/DavidVivancos/MindBigData2022_VisMNIST_Cap64_Morlet |
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