Update README.md

README.md

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-license: odbl
-There are 3 main “MindBigData” databases: 
-1.- “The MNIST of Brain Digits” for EEG signals with several headsets captured while looking at “font” based digits shown in a screen from 0 to 9.  
-2.- “The ImageNet of the Brain” for EEG signals captured while looking at ImageNet images. 
-3.- “The Visual MNIST of Brain Digits” for EEG signals captured while looking at the original MNIST handwritten digits (real pixels) shown in a screen also from 0 to 9.  
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+# MindBigData 2022 A Large Dataset of Brain Signals
+> Supporting datasets for paper [ arXiv:2212.14746](https://arxiv.org/abs/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 2 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
+> 
+**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
+