Nystagmus, a condition characterized by involuntary, repetitive eye movements that significantly impair visual acuity and are indicative of various neurological disorders. Creating deep learning models for nystagmus research has been hindered by a lack of publicly available data, largely due to concerns regarding patient privacy, as eye movement patterns can potentially identify individuals. To overcome this, the research generates synthetic nystagmus videos based on different types of nystagmus waveforms, without using real patient data (GenVOG). This is achieved by utilizing publicly accessible datasets to create long, clinically relevant videos that realistically simulate nystagmus. The effectiveness of the generated videos is evaluated through their application to downstream tasks using real patient datasets.