Diagnosing Alzheimer's disease is a lengthy, expensive process. A new method under development by UMD undergraduates could result in faster diagnoses, giving patients a better chance to use therapies to delay the disease. Using a 3D-printed EEG device, the Synapto system's machine-learning algorithm compares biomarkers from a subject’s scan with those of a healthy brain, producing a diagnosis before symptoms are observable. The invention won first place and $20,000 in a National Institutes of Health undergraduate design competition.