In Oxford, an AI-framework for the diagnosis of nystagmus is created - an early symptom of neurodegenerative pathologies, such as Parkinson's disease. Nystagmus is a form of sleep disturbance, a series of involuntary rapid tremors in the eyeballs of a sleeping person. Rapid diagnosis of nystagmus will allow to treat Parkinson’s disease at an early stage.
The researchers used data from 53 patients from an open laboratory database of the Montreal Sleep Research Archive. Records of electrical activity of the brain, skeletal muscles and eye movements were processed using the algorithm of regression decision trees (random forest).
As the main symptom of nystagmus and the approaching Parkinson's disease, researchers considered muscle atony. In total, electrograms identified 156 different features that can indicate the development of pathology.
Scientists used manual and automatic markup methods for a data set. With manual marking, they managed to achieve diagnostic accuracy of 96%, with automatic results being 4% worse. The researchers plan to improve the results of automatic processing using mathematical functions that mimic the behavior of brain neurons.
A month before the publication of the work of experts at Oxford University, scientists from the Swiss Institute of IRIS reported on the results of work on their own system for diagnosing neuropathology. The fundamental difference is that the Swiss system uses data collected using a smartphone, and the development from Oxford relies on special medical tests.