Spindle Detection

Spindle Detection is an algorithm based on deep learning and signal processing techniques designed to automatically identify and extract sleep spindles from electroencephalogram (EEG) recordings. Sleep spindles are specific patterns of brain activity that occur during sleep and are closely associated with memory consolidation and cognitive function. By accurately detecting these spindles, researchers and clinicians can better assess sleep quality, diagnose sleep disorders, and study the impact of sleep on brain function. This technology has significant applications in the fields of sleep medicine, neuroscience, and psychology.