AI Based Early Detection of Parkinson's and Alzheimer's Disease Using EEG Signals

In this study, a new approach to the diagnosis of Parkinson's and Alzheimer's diseases is introduced by employing EEG signals and applying PCA and training through the CNN model. Although the focus is on classification, 1D CNN generated from EEG-based signal values are applied independently and results are compared in the proposed method. Based on the classification results, the EEG signals obtained from EEG signals were able to accurately diagnose Parkinson's and Alzheimer's. From these data, the highest classifier accuracy was achieved to be 95%.