Hi team OpenBCI! I wasn’t able to find a maintained, self-contained Python example demonstrating OpenBCI streaming → feature extraction → local ML classification in real time.
I’d like to contribute a tutorial using BrainFlow + scikit-learn that:
-
Trains a simple motor imagery classifier (bandpower features + logistic regression)
-
Demonstrates simulated real-time sliding-window inference
-
Is hardware-optional but BrainFlow-ready
Serves as a foundation for future extensions (like for multimodal data pipelines!)
Would this be a useful addition to OpenBCI_Tutorials? Happy to align with any preferred structure before opening a PR.
Hi team OpenBCI! I wasn’t able to find a maintained, self-contained Python example demonstrating OpenBCI streaming → feature extraction → local ML classification in real time.
I’d like to contribute a tutorial using BrainFlow + scikit-learn that:
Trains a simple motor imagery classifier (bandpower features + logistic regression)
Demonstrates simulated real-time sliding-window inference
Is hardware-optional but BrainFlow-ready
Serves as a foundation for future extensions (like for multimodal data pipelines!)
Would this be a useful addition to OpenBCI_Tutorials? Happy to align with any preferred structure before opening a PR.