BEED: Bangalore EEG Epilepsy Dataset
Donated on 3/10/2025
The Bangalore EEG Epilepsy Dataset (BEED) is a comprehensive EEG collection for epileptic seizure detection and classification. Recorded at a neurological research centre in Bangalore, India, it features high-fidelity EEG signals captured using the standard 10-20 electrode system at a 256 Hz sampling rate. BEED contains 16,000 segments of 20-second EEG recordings evenly distributed across four categories: Healthy Subjects (0), Generalized Seizures (1), Focal Seizures (2), and Seizure Events (3), where seizure activity occurs with events like eye blinking, nail biting, or staring. Each category includes data from 20 adult subjects (ages 21-55) with equal gender representation. The dataset comprises 16 EEG channels (X1-X16) corresponding to different brain regions, with a binary label (y) indicating seizure presence (1) or absence (0). BEED supports machine learning in seizure detection, epilepsy analysis, and EEG research with its balanced, high-resolution data.
Dataset Characteristics
Tabular, Multivariate
Subject Area
Health and Medicine
Associated Tasks
Classification
Feature Type
Integer
# Instances
8000
# Features
17
Dataset Information
Has Missing Values?
No
Introductory Paper
By Najmusseher; P.K. Nizar Banu. 2024
Published in International Journal of Computing and Digital Systems
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| X1 | Feature | Integer | no | ||
| X2 | Feature | Integer | no | ||
| X3 | Feature | Integer | no | ||
| X4 | Feature | Integer | no | ||
| X5 | Feature | Integer | no | ||
| X6 | Feature | Integer | no | ||
| X7 | Feature | Integer | no | ||
| X8 | Feature | Integer | no | ||
| X9 | Feature | Integer | no | ||
| X10 | Feature | Integer | no |
0 to 10 of 17
Additional Variable Information
Dataset Details Dataset Characteristics: Multivariate Feature Type: Integer Subject Area: Health and Medicine Instances: 8,000 (2,000 per category) Classes: 4 Format: CSV Features: 16 (EEG channels) Associated Tasks: Classification No missing Values Data Structure • Subjects: 80 individuals (20 per file across four folders) • Time Points: 200 per subject • Explanatory Variables (X1–X16): 16 features representing EEG signal characteristics • Response Variable (y) (Column 17): Categorizes the EEG recordings into four distinct classes: o 3 – Recording of seizure events (including activities such as eye blinking or constant staring) o 2 – Recording of focal seizures o 1 – Recording of generalized seizures o 0 – Recording of healthy subjects (control group without epileptic seizures)
Dataset Files
| File | Size |
|---|---|
| BEED_Data.csv | 394.9 KB |
Reviews
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset beed_bangalore_eeg_epilepsy_dataset = fetch_ucirepo(id=1134) # data (as pandas dataframes) X = beed_bangalore_eeg_epilepsy_dataset.data.features y = beed_bangalore_eeg_epilepsy_dataset.data.targets # metadata print(beed_bangalore_eeg_epilepsy_dataset.metadata) # variable information print(beed_bangalore_eeg_epilepsy_dataset.variables)
., N. & BANU P K, N. (2024). BEED: Bangalore EEG Epilepsy Dataset [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5K33B.
Keywords
Creators
NAJMUSSEHER .
najmusseher@res.christuniversity.in
CHRIST (Deemed to be University), Central Campus, Bangalore
NIZAR BANU P K
nizar.banu@christuniversity.in
CHRIST (Deemed to be University), Central Campus, Bangalore
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.