Accurate Parkinson’s Detection via Emotional Brain Responses
A new study has achieved near-perfect accuracy in detecting Parkinson’s disease by analyzing brain responses to emotional stimuli using EEG and AI. Researchers found that Parkinson’s patients process emotions differently, struggling with recognizing fear, disgust, and surprise and focusing more on emotional intensity than valence.
EEG data from 20 patients and 20 healthy controls was analyzed using machine learning, achieving an F1 score of 0.97 for diagnostic accuracy. This breakthrough offers a non-invasive, objective diagnostic method, potentially revolutionizing early detection and treatment for Parkinson’s disease.
🧠🆔 @neurocognitionandlearning
A new study has achieved near-perfect accuracy in detecting Parkinson’s disease by analyzing brain responses to emotional stimuli using EEG and AI. Researchers found that Parkinson’s patients process emotions differently, struggling with recognizing fear, disgust, and surprise and focusing more on emotional intensity than valence.
EEG data from 20 patients and 20 healthy controls was analyzed using machine learning, achieving an F1 score of 0.97 for diagnostic accuracy. This breakthrough offers a non-invasive, objective diagnostic method, potentially revolutionizing early detection and treatment for Parkinson’s disease.
🧠🆔 @neurocognitionandlearning