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an example of nystagmus profile seen in a patient with BPPV, similar to traces which we hope to utilise machine learning on to help differentiate between BPV and CPV
Vertigo, an illusionary sense of movement, will affect up to 30% of all individuals in their lifetime. The most common cause of this symptom is benign paroxysmal positional vertigo (BPV); this has effective treatments and a benign course. Central positional vertigo (CPV) is less common but have a similar presentation, with causes including strokes, inflammation or tumours.
Currently, there is high healthcare resources utilisation required to differentiate between CPV and BPV. The importance of distinguishing between these is paramount due to differences in treatments and outcomes. This projects aims to establish a method to differentiate CPV from BPV, utilising different characteristics of nystagmus, a type of jerky eye movement commonly found in patients with vertigo.
Dr. Nicholas Yang and his team will utilise nystagmus data from non-invasive methods and apply machine learning techniques to establish an accurate way of differentiating between these conditions. This will positively impact health resources utilisation, reduce time to diagnosis/treatment, and potentially impact around 1 million Australian individuals a year who suffer from vertigo.