Mount Adora Epilepsy EEG Dataset: Clinical Recordings for Seizure Detection Studies

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Main Authors: Ferdaush, Rafat, paul, arnob
Format: Recurso digital
Language:English
Published: Zenodo 2025
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author Ferdaush, Rafat
paul, arnob
author_facet Ferdaush, Rafat
paul, arnob
contents <p>This  is a  EEG dataset of 212  epileptic-Normal patients. 101 of them are females, 111 of them are males. From the 110 of the EEG data(50 from female, 60 from male). Rest of the patients are non epileptic. In this dataset two folder was given. One of the folder is " Raw EEG" which contains Unprocessed EEG Data. For raw EEG signal, total number of channel is 23, two of them are NON EEG.Sampling Frequency is 128 Hz.<br>Actual Cleaned and preprocessed EEG data is given to another folder called"Final cleaned". For preprocessing, we first rename channel name based on the standard. Then we remove Two Non EEG channel: EKG and MK. Then we use bandpass filter and ICA to remove all the artifact.<br>All the epileptic spike is given to another csv file name "Epilpetic Spike Duration"</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_17011827
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Mount Adora Epilepsy EEG Dataset: Clinical Recordings for Seizure Detection Studies
Ferdaush, Rafat
paul, arnob
Epilepsy, EEG, Seizure detection, Biomedical signals, Machine learning, Mount Adora Hospital
<p>This  is a  EEG dataset of 212  epileptic-Normal patients. 101 of them are females, 111 of them are males. From the 110 of the EEG data(50 from female, 60 from male). Rest of the patients are non epileptic. In this dataset two folder was given. One of the folder is " Raw EEG" which contains Unprocessed EEG Data. For raw EEG signal, total number of channel is 23, two of them are NON EEG.Sampling Frequency is 128 Hz.<br>Actual Cleaned and preprocessed EEG data is given to another folder called"Final cleaned". For preprocessing, we first rename channel name based on the standard. Then we remove Two Non EEG channel: EKG and MK. Then we use bandpass filter and ICA to remove all the artifact.<br>All the epileptic spike is given to another csv file name "Epilpetic Spike Duration"</p>
title Mount Adora Epilepsy EEG Dataset: Clinical Recordings for Seizure Detection Studies
topic Epilepsy, EEG, Seizure detection, Biomedical signals, Machine learning, Mount Adora Hospital
url https://doi.org/10.5281/zenodo.17011827