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task_video_edited.mp4
- Clone the repository by running
git clone https://github.com/masoudrahimi39/visual-working-memory-game.git- Install dependencies:
python='3.8', pygame='2.1.2', Pandas, NumPy, Matplotlibby running below:pip install pygame='2.1.2', Pandas, NumPy, Matplotlib
- Run
main_game.py
This project serves multiple purposes:
- Entertainment: Play the game for fun and test your visual working memory abilities.
- Gameplay and Eye Tracker Data Collection: The game collects and saves the player's gameplay data, along with eye tracker data when enabled, providing valuable insights for research and analysis.
- Adjustable Parameters: All Python functions and classes have clear and concise docstrings, making it easy to modify and extend the game's functionalities.
- Rule-Based Difficulty Adjustment: The game incorporates a rule-based difficulty adjustment system, ensuring that players are appropriately challenged as they progress through the tasks.
- Data Storage: The player's gameplay data is saved in CSV and plk (Pandas DataFrames) files, facilitating data analysis and post-game insights.
- Structured User Journey: The task follows a well-structured user journey, guiding players through different pages, including "Welcome," "Sign Up," "Guiding," "Guiding trials," and "Actual Trials."
- At the beginning, a 6*6 hexagonal grid is displayed for two seconds, with certain hexagons simultaneously highlighted in yellow (known as "targets") while the rest are white.
- After two seconds, all the hexagons become white, and the player must recall and click on the exact locations of the targets.
- Correct and incorrect clicks instantly become green and red, respectively.
- The player's score is the number of correct clicks divided by the total number of targets in the task.
- A score 1 represents a win, whereas other scores represent a loss.