Published December 30, 2024 | Version v1
Dataset Open

SWEC-ETHZ iEEG Seizure Detection Dataset for Bangalore Neuromorphic BNEW Workshop 2025

Authors/Creators

  • 1. Institut für Neuroinformatik

Description

Dataset for analog iEEG signals for detection of Epileptic seizures from SWEC-ETH Dataset
(Curated for Bangalore Neuromorphic Conference 2025)

This dataset contains analog signals recorded during pre-surgical evaluations of patients at the Sleep-Wake-Epilepsy-Center (SWEC) of the University Department of Neurology at the Inselspital Bern. The analog signals are sourced from the SWEC-ETHZ iEEG Database

This database contains 3 patients from the short-term set and 5 Hours of Data for Patient 18 from the long-term Dataset.

Short-Term Dataset

The iEEG signals were recorded intracranially by strip, grid, and depth electrodes. After 16-bit analog-to-digital conversion, the data were digitally band-pass filtered between 0.5 and 150 Hz using a fourth-order Butterworth filter prior to analysis and written onto disk at a rate of 512 Hz. Forward and backward filtering was applied to minimize phase distortions. All the iEEG recordings were visually inspected by an EEG board-certified experienced epileptologist (K.S.) for identification of seizure onsets and endings and exclusion of channels continuously corrupted by artifacts. Each recording consists of 3 minutes of preictal segments (i.e., immediately before the seizure onset), the ictal segment (ranging from 10 s to 1002 s), and 3 minutes of postictal time (i.e., immediately after seizure ending).

The dataset is provided in 3 folders, named with the ID of the patients (e.g., shortterm/ID2/). Each folder contains a number of .mat files as recorded seizures (e.g., Sz1.mat, Sz2.mat, …) for the target patient. In each .mat file, the recording is stored in a variable called EEG as a TxM array where T is the number of sampling points and M is the number of iEEG electrodes. Seizure always starts at 3 minutes from the beginning of recording (i.e., the sampling point of 512*3*60=92160), and ends 3 minutes before the end of recording (i.e., sampling point of T-92160).

Patient ID Age Electrodes Number of Seizures Min Seizure Duration (in sec) Max Seizure Duration (in sec) Affected Area MRI
ID2 19 42 4 96 301 TLE pos.
ID3 25 98 2 73 125 TLE neg.
ID16 31 59 6 67 117 TLE pos.

Long-Term Dataset

The iEEG signals were recorded intracranially by strip, grid, and depth electrodes. After 16-bit analog-to-digital conversion, the iEEG signals were median-referenced and digitally band-pass filtered between 0.5 and 120 Hz using a fourth-order Butterworth filter prior to analysis and written onto disk at a rate 1024 Hz. Forward and backward filtering was applied to minimize phase distortions. All the iEEG recordings were visually inspected by an EEG board-certified and experienced epileptologist (K.S.) for identification of seizure onsets and endings and exclusion of channels continuously corrupted by artifacts.

The dataset is provided as continuous recoding of each patient is segmented to a set of .mat files, each of which contains exactly one hour of recording (e.g., ID18_100h.mat, ID18_183h.mat,…,ID01_187h.mat). Every file is less than 1 GB. In each .mat file, the recording is stored in a variable called EEG as a TxM array where T is the number of iEEG electrodes (42 for ID18) and M is the number of sampling points for one hour. The folder also contains an additional file (e.g., ID18_info.mat) defining the sampling frequency, beginning and end of the seizures (beginning and end of the seizures are computed in seconds).

Patient ID Hr Type  Seizure Duration
(in sec)
ID18 100 control NA
ID18 183 inter-ictal NA
ID18 184 ictal 230.84
ID18 186 inter-ictal NA
ID18 187 ictal 300.65
ID18 info metadata --

 

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Additional details

Related works

Cites
Dataset: http://ieeg-swez.ethz.ch/ (URL)
Is published in
Publication: 10.1109/TBME.2019.2919137 (DOI)
Publication: 10.23919/DATE.2019.8715186 (DOI)

Dates

Issued
2025-01-05
Curated