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EEG Eye State Classification
Patient Health Records & Digital Health
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About
This dataset captures Electroencephalography (EEG) data from a Neuroheadset, specifically designed to classify eye states. It comprises 117 seconds of continuous EEG measurements using the Emotiv EEG Neuroheadset. The primary aim is to predict whether eyes are open or closed based on the recorded brain activity. The eye state was manually labelled post-measurement by analysing video frames, providing a clear target variable for supervised learning tasks. This dataset offers valuable insights into neurophysiological responses associated with visual states. The data values are presented in chronological order.
Columns
- AF3: Numeric sensor reading from the AF3 electrode.
- F7: Numeric sensor reading from the F7 electrode.
- F3: Numeric sensor reading from the F3 electrode.
- FC5: Numeric sensor reading from the FC5 electrode.
- T7: Numeric sensor reading from the T7 electrode.
- P7: Numeric sensor reading from the P7 electrode.
- O1: Numeric sensor reading from the O1 electrode.
- O2: Numeric sensor reading from the O2 electrode.
- P8: Numeric sensor reading from the P8 electrode.
- T8: Numeric sensor reading from the T8 electrode.
- FC6: Numeric sensor reading from the FC6 electrode.
- F4: Numeric sensor reading from the F4 electrode.
- F8: Numeric sensor reading from the F8 electrode.
- AF4: Numeric sensor reading from the AF4 electrode.
- eyeDetection: Categorical target variable, indicating the eye state:
- 0 represents the eye-open state.
- 1 represents the eye-closed state.
Distribution
The dataset is provided in the ARFF format (Attribute-Relation File Format) and is approximately 1.7 MB in size. It consists of a single file containing chronological EEG measurements. The exact number of rows or records is not specified, but the data represents a continuous 117-second measurement.
Usage
This dataset is ideal for a range of machine learning applications, particularly in binary classification. Potential use cases include:
- Developing predictive models for eye state detection from EEG signals.
- Neurofeedback systems where real-time eye state monitoring is crucial.
- Applications in human-computer interaction that respond to eye states.
- Research into drowsiness detection or attention monitoring based on brain activity.
- Educational purposes for demonstrating EEG data analysis and classification algorithms.
Coverage
The data originates from one continuous EEG measurement using an Emotiv EEG Neuroheadset, lasting for a duration of 117 seconds. The data availability is limited to this specific single measurement session, and there are no geographic or demographic variations detailed. The dataset is static and is not expected to be updated.
License
CC0: Public Domain
Who Can Use It
This dataset is highly suitable for:
- Data scientists and machine learning engineers looking to build and test classification algorithms.
- Neuroscience researchers interested in analysing brainwave patterns related to eye movements and states.
- Students and academics for educational projects and research in biomedical signal processing.
- Developers of Brain-Computer Interface (BCI) technologies.
Dataset Name Suggestions
- EEG Eye State Classification
- Neuroheadset Eye State Data
- Human EEG Eye Activity
- Emotiv EEG Eye State Records
Attributes
Original Data Source: EEG Eye State Classification
QUALITY