MindBigData 2022 A Large Dataset of Brain Signals

Supporting datasets for paper arXiv:2212.14746 There are 3 Main datasets with subdatasets:

1.- MindBigData MNIST of Brain Digits

based on http://mindbigdata.com/opendb/index.html But all datasets splitted to 80% Train 20% Test (also proportional in the 11 classes) EEG's Resampled to match original headsets sampling rate Included headers. 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. There are 4 subdatasets:

For MindWave with 1 EEG Channel and 1024 samples x Channel

For EPOC1 with 14 EEG Channels and 256 samples x Channel

For Muse1 with 4 EEG Channels and 440 samples x Channel

For Insight1 with 5 EEG Channels and 256 samples x Channel

1.1.- MindBigData MNIST of Brain digits MindWave1 https://huggingface.co./datasets/DavidVivancos/MindBigData2022_MNIST_MW

1.2.- MindBigData MNIST of Brain digits EPOC1 https://huggingface.co./datasets/DavidVivancos/MindBigData2022_MNIST_EP

1.3.- MindBigData MNIST of Brain digits Muse1 https://huggingface.co./datasets/DavidVivancos/MindBigData2022_MNIST_MU

1.4.- MindBigData MNIST of Brain digits Insight1 https://huggingface.co./datasets/DavidVivancos/MindBigData2022_MNIST_IN

2.- MindBigData Imagenet of the Brain

based on http://mindbigdata.com/opendb/imagenet.html But all datasets splitted to 80% Train 20% Test (also proportional in all the classes) EEG's Resampled to match original headsets sampling rate Included headers. 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, There are 2 subdatasets:

One with the Insight 1 EEG signals at 384 samples per channel (5 channels)

One with the Spectrogram image 64x64px instead of the EEG as described in the paper

2.1.- MindBigData Imagenet of the Brain Insight1 EEG https://huggingface.co./datasets/DavidVivancos/MindBigData2022_Imagenet_IN

2.2.- MindBigData Imagenet of the Brain Insight1 Spectrogram https://huggingface.co./datasets/DavidVivancos/MindBigData2022_Imagenet_IN_Spct

3.- MindBigData Visual MNIST of Brain Digits

based on http://mindbigdata.com/opendb/visualmnist.html But all datasets splitted to 80% Train 20% Test (also proportional in the 11 classes) Included headers. 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. There are 3 subdatasets:

For Muse2 with 5 EEG Channels, 3 PPG Channels, 3 ACC Channels & 3 GYR Channels and 512 samples x Channel

For Cap64 with 64 EEG Channels and 400 samples x Channel

For Cap64 with 64 EEG Channels and 400 samples x Channel but with Morlet png images as EEG outputs

3.1.- MindBigData Visual MNIST of Brain digits Muse2 https://huggingface.co./datasets/DavidVivancos/MindBigData2022_VisMNIST_MU2

3.2.- MindBigData Visual MNIST of Brain digits Cap64 https://huggingface.co./datasets/DavidVivancos/MindBigData2022_VisMNIST_Cap64

3.3.- MindBigData Visual MNIST of Brain digits Cap64 Morlet https://huggingface.co./datasets/DavidVivancos/MindBigData2022_VisMNIST_Cap64_Morlet