Summer 2023 NeurotechX Competition:
Machine Learning EEG Classifier for Neurological Disorders
June 30, 2023

Because of the neurodegenerative nature of dementia, early detection is critical for slowing the progression of the disease and to plan treatment, as research shows an early diagnoses helps caregivers better adapt to changes characterized by dementia. Electroencephalogram, or EEG, is a technique that records changes in the electrical activity of the cerebral cortex by placing electrodes on fixed locations across the scalp. EEG is an incredibly desirable tool for being non-invasive, low-cost, fast, and widely available, making for both an accurate and accessible diagnosis technique with the potential to drastically change the diagnosis timeline of Dementia patients for the better.

For our project, we aimed to implement our own machine learning classifier which uses EEG data to accurately diagnose Alzheimer’s disease and frontotemporal dementia. Our team developed a pipeline and algorithm for classifying the EEG data we worked with. Our model was based on the resting state EEG dataset from this 2021 paper by Miltiadous et al. (https://pubmed.ncbi.nlm.nih.gov/34441371/)
Check out our project submission: https://github.com/charan1319/NeuroTechX-Alzheimers-Identification