Neuroheadstate Eye State Classification Dataset

1) Data Introduction

• The Neuroheadstate Eye-State Classification dataset aims to classify and differentiate between eye-open and eye-closed states using data from an EEG Neuroheadset. It includes 14 channels of EEG data collected while recording eye states, providing a comprehensive dataset for developing machine learning models for eye-state prediction.

2) Data Utilization

(1) Neuroheadstate Eye-State data has characteristics that: • The dataset includes detailed EEG recordings from 14 electrodes placed on different scalp areas, allowing for in-depth analysis of brainwave patterns associated with eye states. (2) Neuroheadstate Eye-State data can be used to: • Machine Learning and AI Development: Useful for developing and testing models that can accurately predict eye states based on EEG signals. • Research: Supports academic studies and technological advancements in neural networks, human-computer interaction, and bioinformatics.