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Researchers from UEA and the Norfolk and Norwich University Hospital (NNUH) have published the results of the biggest collection of continuous eye movement data after testing the effectiveness of a wearable diagnostic headset.
The device, called the Continuous Ambulatory Vestibular Assessment (CAVA) aims to speed up the diagnosis of the most common causes of dizziness. It features electrode sensors that stick to the side of the face and which can detect the electrical signals emanating from the eyeball. These signals are analyzed using a specially developed algorithm to identify instances of nystagmus (eye flickering).
A study done to test the accuracy, reliability and safety of the novel new device, published in the journal Scientific Reports, found the technology to be 99 per cent accurate at detecting eye flicker.
“Following years of development, I’m delighted that this project was successful in identifying short periods of visually induced nystagmus with a high degree of accuracy,” Principal Investigator John Phillips said.
“The success of this trial has proven the potential of this to fulfil a clinical need and establishing a new field of medicine, vestibular telemetry. These results have provided a good foundation from which to conduct a further study intended to evaluate the system’s diagnostic accuracy among patients with dizziness problems.”
Dr Jacob Newman, from UEA’s School of Computing Sciences, said: “We are very pleased that our algorithms have been able to detect such small incidences of nystagmus within such a large dataset, this bodes well for future work that considers nystagmus in individuals experiencing dizziness.”