EpiEEG-60: A Balanced Epileptic Seizure and Normal EEG Dataset

Description

This dataset contains raw Electroencephalogram (EEG) recordings collected from 60 distinct individuals. The cohort is equally divided into two groups: 30 neurologically normal subjects and 30 abnormal subjects clinically diagnosed with epilepsy. The dataset is intended to support research in automated seizure detection, neurological signal processing, and machine learning classification tasks. #Participants and Demographics# Total Subjects: 60 Groups: 30 Normal, 30 Epilepsy Demographics: The participants include both male and female subjects with an age range of 17 to 70 years. Validation: All recordings were manually labeled and verified by an expert neurologist from the National Institute of Neuroscience and Hospital (NINS). #Data Acquisition Details# Instrumentation: Signals were acquired using a Nihon Kohden EEG system. Sampling Rate: 500 Hz. Recording Duration: Approximately 30 ± 2 minutes per subject. Channel Configuration: Each recording comprises 43 channels, including standard EEG (electroencephalogram), EOG (electro-oculogram), MISC (miscellaneous reference), and BIO (physiological) channels. Filtering: Default acquisition settings included a 0–250 Hz bandwidth filter. #File Formats and Structure# The dataset is organized using a structured directory hierarchy. The main directory, Ready_data, contains two subdirectories: Normal and Abnormal. Inside these, subject-specific folders (e.g., Patient_01, Patient_02) contain the recording sessions. Each recording session includes seven proprietary Nihon Kohden files necessary for full decoding and interpretation: .EEG: Contains the continuous, digitized raw EEG voltage waveforms. .21E: Header file providing essential acquisition parameters (channel indexing, sensitivity, sampling frequency) required for parsing the .EEG file. .EVT: Event annotation file storing time-stamped markers for clinical events (e.g., "Eyes Open," "Hyperventilation," "Seizure Onset"). .CMT: Electrode configuration file defining channel labels and 10–20 system positions. .CN2: Channel-specific settings (amplifier configuration, calibration factors). .LOG: System log recording session history and hardware status. .TRD: Trend data files containing compressed signal views. #Usage Notes# These files are binary and typically require specialized libraries for processing. Python users can utilize MNE-Python (using the read_raw_nihon function) to load the data, as the .21E and .EEG files function together to reconstruct the signal. The .EVT files are critical for extracting epochs related to specific stimuli or clinical states.

Institutions

• Bangladesh University of Business and Technology

  Dhaka District, Dhaka
• National Institute of Neurosciences & Hospital

  Dhaka, Sher-E-Bangla Nagar

Categories

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