Smartphone-Based Videonystagmography Using Artificial Intelligence

Abstract

Dizziness is a common symptom in medicine. The anamnesis and detection of a nystagmus is essential to distinguish a vertigo's pathogenesis. The diagnosis is complex, expensive, and not always available across the board. We present a novel location- and time-independent mobile application for videonystagmography (VNG) to support vertigo patients and medical staff. No additional hardware is necessary. The app uses artificial intelligence for eye tracking and to detect a horizontal nystagmus. A feasibility study of the mobile VNG with 13 healthy volunteers was performed. Each participant underwent a caloric vestibular testing to provoke the presence of a vestibular nystagmus. It could be shown that a smartphone-based VNG is possible.

Keywords

• vertigo
• dizziness
• videonystagmography
• nystagmus
• eye tracking
• deep learning
• digital health