This project focuses on preprocessing and recording EEG data alongside token IDs derived from displayed sentences. It's designed to bridge the gap between neurological signals and text tokens, aiding in the development of speech neuroprostheses.
- EEG Recording: Seamlessly capture EEG data during text display.
- Token ID Mapping: Assign token IDs based on displayed sentence word tokens.
- Synchronization: Ensure tight synchronization between EEG data and corresponding text tokens.
- Python
<version>(e.g., Python 3.8) - Additional dependencies are listed in
requirements.txt.
- Clone this repository:
git clone https://github.com/<your-username>/<Your-Chosen-Repo-Name>.git
- Navigate to the cloned directory:
cd <Your-Chosen-Repo-Name>
- Install required dependencies:
pip install -r requirements.txt
- Start the EEG data streaming (You might need additional setup for this. More details in
<LINK_TO_DETAILED_SETUP>):
<PLACEHOLDER_COMMAND_TO_START_EEG_STREAM>
- Run the main script to start recording and preprocessing:
python main.py
- Issue with EEG Data Stream: Ensure that your EEG device is properly connected and the required drivers/software are installed.
- Token ID Mapping Errors: Ensure that the sentence displayed is correctly formatted and compatible with the tokenization process.
- Integrate with other neuroimaging tools.
- Enhance token ID mapping algorithms for greater accuracy.
- Provide real-time feedback based on recorded EEG data.
Contributions are welcome! Please read the CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.
This project is licensed under the <Your License> License - see the LICENSE.md file for details.
<Any acknowledgments or references you'd like to include><PLACEHOLDER_FOR_ADDITIONAL_ACKNOWLEDGMENTS>