Reconstructing animated eye movements from electrooculography data to aid the diagnosis of vestibular disorders

Newman, Jacob L. ORCID: https://orcid.org/0000-0002-9149-6181, Phillips, John S. and Cox, Stephen J. (2022) Reconstructing animated eye movements from electrooculography data to aid the diagnosis of vestibular disorders. International Journal of Audiology, 61 (1). pp. 78-83. ISSN 1499-2027

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Abstract

Objective: To develop a method of visualising electrooculography data to improve the interpretability of nystagmus eye-movements captured using the Continuous Ambulatory Vestibular Assessment (CAVA®) device. Design: We are currently undertaking a clinical investigation to evaluate the capabilities of the CAVA® device to detect periods of pathological nystagmus. The work presented here was undertaken using unblinded data obtained from the preliminary phase of this investigation. Study sample: One patient with Ménière’s disease and one with Benign Paroxysmal Positional Vertigo. Results: Using the electrooculography data captured by the CAVA® device, we reconstructed 2D animations of patients’ eye movements during attacks of vertigo. We were able to reanimate nystagmus produced as a consequence of two conditions. Concurrent video footage showed that the animations were visually very similar to the patient’s actual eye-movements, excepting torsional eye-movements. Conclusions: The reconstructed animations provide an alternative presentation modality, enabling clinicians to largely interpret electrooculography data as if they were present during a vertigo attack. We were able to recreate nystagmus from attacks experienced in the community rather than a clinical setting. This information provides an objective record of a patient’s nystagmus and could be used to complement a full neurotologic history when considering diagnosis and treatment options.

Item Type:	Article
Uncontrolled Keywords:	3*,jacob newman ,/dk/atira/pure/researchoutput/REFrank/3_
Faculty \ School:	Faculty of Science > School of Computing Sciences Faculty of Medicine and Health Sciences > Norwich Medical School
UEA Research Groups:	Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Interactive Graphics and Audio Faculty of Medicine and Health Sciences > Research Centres > Population Health Faculty of Science > Research Groups > Data Science and AI
Depositing User:	LivePure Connector
Date Deposited:	26 Jan 2021 00:56
Last Modified:	07 Jan 2025 02:10
URI:	https://ueaeprints.uea.ac.uk/id/eprint/78280
DOI:	10.1080/14992027.2021.1883196

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