EEG analysis pipeline for Parkinson’s diagnosis (IMAGE)
Caption
The pipeline illustrates how EEG signals are processed for Parkinson's disease detection. Key features are extracted from brainwave data and transformed into images or movie representations. These are then analyzed using machine learning models to classify emotional responses, high and low valence and arousal, and differentiate patients with Parkinson's disease (PD) from healthy controls (HC).
Credit
Ravikiran Parameshwara et al.
Usage Restrictions
Credit must be given to the creator.
License
CC BY