Update README.md

README.md

@@ -30,18 +30,14 @@ size_categories:
 [![Hugging Face](https://img.shields.io/badge/Hugging_Face-🤗_webxos-FFD21E?style=for-the-badge&logo=huggingface&logoColor=white)](https://huggingface.co/webxos)
 [![Follow on X](https://img.shields.io/badge/Follow_@webxos-1DA1F2?style=for-the-badge&logo=x&logoColor=white)](https://x.com/webxos)
 
-## Dataset Card for BCI-FPS MOTOR_IMAGERY Dataset
+# Dataset Card for BCI-FPS MOTOR_IMAGERY Dataset
 
 *UNDER DEVELOPMENT for TESTING*
 
-*This dataset was made using app in the /generator/ folder which is under development testing.*
-
-## Concept: 
-
-*Simulated data for Intent testing, does not use real Neuralink/BCI hardware signals.*
-
-BCI Intent Data Study and Testing (conceptual early design) 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.
+This dataset was made using the app in the /generator/ folder which is under development testing. Simulated data for Intent testing, 
+does not use real Neuralink/BCI hardware signals. BCI Intent Data Study and Testing (conceptual early design) 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.
 
 -Augmenting real-world BCI data with synthetic samples to improve model robustness and diversity, as in GAN-based approaches.
 
@@ -65,10 +61,6 @@ decoding without needing large scale real hardware BCI datasets, addressing data
 - **BCI Calibration**: Providing ground truth data for BCI system calibration
 - **Disability Research**: Supporting development of assistive technologies
 
-## Languages
-
-English (interface and documentation)
-
 ## Data Instances
 
 ```json
@@ -144,13 +136,8 @@ See `metadata.json` for complete schema documentation.
 - **Annotation types**: Motor imagery, visual stimuli, handwriting intent
 - **Who annotated**: System automatically labels based on game state
 
-## Personal and Sensitive Information
-
-No personal information is collected. All data is synthetic/anonymous.
-
-## Social Impact
+## This dataset enables research in:
 
-This dataset enables research in:
 - Neuralink-style brain-computer interfaces
 - Assistive technologies for disabled individuals
 - Human-AI interaction systems
@@ -166,23 +153,6 @@ Synthetic neural data may not perfectly represent biological signals. Results sh
 - Idealized game environment
 - Limited to specific training tasks
 
-## Additional Information
-
-## Dataset Curators
-
-huggingface.co/webXOS
-
 ### Licensing Information
 
-MIT License
-
-## Citation Information
-
-```bibtex
-@misc{bci-fps,
-  title={BCI-FPS motor_imagery Dataset},
-  author={webXOS,
-  year={2026},
-  note={for testing and development purposes}
-}
-```
+MIT License