DOI: 10.57760/sciencedb.01034
title: Visual Colour EEG Dataset
title: Visual Colour EEG Dataset

description: Although there is more research about BCI Visual, but little about human’s visual colour. We provide a new EEG dataset of BCI Visual Colour. There is no such type dateset up-to-today. We hope this dataset can help and reuse for other researchers with there basic works in Neural Science and Computer Science. These dataset consist of 14 healthy subjects. Our purpose of establishing this dataset is to create a standard small sample of visual colour EEG to provide scholars in related fields for research. The standard small sample dataset includes the recognition of the basic colour RGB that humans perceive. Each subject in the dataset contains three sets of data: RG, RB, and GB. In each set of data, 3 rounds of visual stimulation experiments were included. Each stimulus experiment consists of 35 random stimulus interactions in two different colours. Therefore, there are a total of 630 stimuli in each subject's data. Note that when calling data, a data packet usually consists of two .bdf files. One is the main record data file named data.bdf, and there is a label file named event.bdf. When calling data, it is necessary to call two files at the same time. The event.bdf file is the main reference basis for time series analysis of all data, and it is as important as the data.bdf file. The code for calling the .bdf file has been written in the other two classifier codes. We hope that this data can provide researchers in the field of neuroscience with a certain effect on the basic research of visual EEG signals and visual nerves in the field of colour perception. At the same time, we also hope that this dataset can be provided to researchers in the field of computer science to bring some research on the application of classifiers. We selected support vector machines and FNN neural networks on the classifier to analyze these dataset and achieved good results. But we not only hope that the analysis of this dataset will only stay on the above two analysis methods. We expect that more colleagues can use more other classifiers and data analysis methods to further process and use our dataset, so that our dataset can get better reusability. The ultimate goal of our release of this set of dataset is to hope that this set of dataset can become a standard sample for decoding human visual colour perception. At the same time, we hope that more machine learning algorithms can be obtained on the basis of repeated use of dataset, so as to give the field of neuroscience and computers The scientific field brings further research.
description: Although there is more research about BCI Visual, but little about human’s visual colour. We provide a new EEG dataset of BCI Visual Colour. There is no such type dateset up-to-today. We hope this dataset can help and reuse for other researchers with there basic works in Neural Science and Computer Science. These dataset consist of 14 healthy subjects. Our purpose of establishing this dataset is to create a standard small sample of visual colour EEG to provide scholars in related fields for research. The standard small sample dataset includes the recognition of the basic colour RGB that humans perceive. Each subject in the dataset contains three sets of data: RG, RB, and GB. In each set of data, 3 rounds of visual stimulation experiments were included. Each stimulus experiment consists of 35 random stimulus interactions in two different colours. Therefore, there are a total of 630 stimuli in each subject's data. Note that when calling data, a data packet usually consists of two .bdf files. One is the main record data file named data.bdf, and there is a label file named event.bdf. When calling data, it is necessary to call two files at the same time. The event.bdf file is the main reference basis for time series analysis of all data, and it is as important as the data.bdf file. The code for calling the .bdf file has been written in the other two classifier codes. We hope that this data can provide researchers in the field of neuroscience with a certain effect on the basic research of visual EEG signals and visual nerves in the field of colour perception. At the same time, we also hope that this dataset can be provided to researchers in the field of computer science to bring some research on the application of classifiers. We selected support vector machines and FNN neural networks on the classifier to analyze these dataset and achieved good results. But we not only hope that the analysis of this dataset will only stay on the above two analysis methods. We expect that more colleagues can use more other classifiers and data analysis methods to further process and use our dataset, so that our dataset can get better reusability. The ultimate goal of our release of this set of dataset is to hope that this set of dataset can become a standard sample for decoding human visual colour perception. At the same time, we hope that more machine learning algorithms can be obtained on the basis of repeated use of dataset, so as to give the field of neuroscience and computers The scientific field brings further research.