webxos/BCI-grid-movement-v1

BCI Grid Movement Intent Dataset

UNDER DEVELOPMENT for TESTING purposes

This dataset was generated with the gym located in /gym/ folder of this repo.

The dataset contains synchronized movement intent data collected from a grid training environment designed for simulated BCI research. Dataset for multi-label classification of WASD movement intents from 12 simulated EEG channels in grid environment. This BCI Intent Data Study (conceptual early design) is for training machine learning models for neural signal decoding without needing large scale real hardware BCI datasets, addressing data scarcity and privacy issues around BCI intent studies.

Simulated data for synthetic Intent testing, does not use real Neuralink/BCI hardware signals.

RL/ML user input intent data:

ML: Supervised decoding of motor intents (e.g., DNNs, classifiers) for cursor/game control, stroke rehab, ADHD treatment.

RL: Adaptive decoders in RLBMIs; deep RL for robot training, intent mapping via rewards/trial-error; simulators with RL agents for policy optimization.

Dataset Summary

• Session ID: bci_grid_1767325222455
• Total Samples: 5,000
• Training Samples: 4,000
• Test Samples: 1,000
• Neural Channels: 12 simulated EEG channels
• Sampling Rate: 100 Hz
• Movement Intent: WASD key press detection
• Environment: 50x50 grid with dynamic enemy targeting

Supported Tasks

• Movement Intent Prediction: Classify WASD movement intent from neural signals
• Neural Signal Analysis: Study neural patterns during movement
• BCI System Development: Train and test BCI algorithms
• Real-time Intent Decoding: Develop real-time BCI interfaces

Data Fields

• timestamp: UNIX timestamp in milliseconds
• session_time: Time since session start in milliseconds
• neural_channels: Array of 12 float64 values representing neural signals
• movement_intent: Array of 4 boolean values [W, A, S, D] indicating key presses
• fire_intent: Integer (0/1) indicating shooting intent
• enemy_active: Integer (0/1) indicating if enemy is present
• current_streak: Current consecutive hits
• level: Current game level
• accuracy: Current shooting accuracy
• mouse_activity: Mouse movement magnitude
• player_position: [x, y, z] coordinates in grid
• player_velocity: Current movement speed
• distance_traveled: Total distance moved

Data Splits

Split	Examples	Percentage
Train	4,000	80%
Test	1,000	20%

Citation

@misc{bci_grid_movement,
  title={BCI Grid Movement Intent Dataset},
  author={webXOS},
  year=2026,
  note={Movement intent data from BCI grid training environment}
}

License

MIT License