The cookie is used to store the user consent for the cookies in the category "Analytics". This cookie is set by GDPR Cookie Consent plugin. These cookies ensure basic functionalities and security features of the website, anonymously. Rev.Necessary cookies are absolutely essential for the website to function properly. E, 64, 061907Īndrzejak RG, Lehnertz K, Rieke C, Mormann F, David P, Elger CE (2001) Indications of nonlinear deterministic and finite dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state, Phys. Although there are 5 classes most authors have done binary classification, namely class 1 (Epileptic seizure) against the rest.Īndrzejak RG, Lehnertz K, Rieke C, Mormann F, David P, Elger CE (2001) Indications of nonlinear deterministic and finite dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state, Phys.
Our motivation for creating this version of the data was to simplify access to the data via the creation of a. Only subjects in class 1 have epileptic seizure. So now we have 23 x 500 = 11500 pieces of information(row), each information contains 178 data points for 1 second(column), the last column represents the label y :ĥ - eyes open, means when they were recording the EEG signal of the brain the patient had their eyes openĤ - eyes closed, means when they were recording the EEG signal the patient had their eyes closedģ - Yes they identify where the region of the tumor was in the brain and recording the EEG activity from the healthy brain areaĢ - They recorder the EEG from the area where the tumor was locatedĪll subjects falling in classes 2, 3, 4, and 5 are subjects who did not have epileptic seizure. We divided and shuffled every 4097 data points into 23 chunks, each chunk contains 178 data points for 1 second, and each data point is the value of the EEG recording at a different point in time. So we have total 500 individuals with each has 4097 data points for 23.5 seconds. Each data point is the value of the EEG recording at a different point in time. The corresponding time-series is sampled into 4097 data points. Each file is a recording of brain activity for 23.6 seconds. The original dataset from the reference consists of 5 different folders, each with 100 files, with each file representing a single subject/person. The version of the dataset hosted by our repository has been removed. Click here to try out the new site.ĭownload: Data Folder, Data Set DescriptionĪbstract: This dataset is a pre-processed and re-structured/reshaped version of a very commonly used dataset featuring epileptic seizure detection. Check out the beta version of the new UCI Machine Learning Repository we are currently testing! Contact us if you have any issues, questions, or concerns.
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