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Proof of Concept for an “eyePhone” App to Measure Video Head Impulses
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Proof of Concept for an “eyePhone” App to Measure Video Head Impulses
Authors text
Parker, Taylor Max , Farrel, Nathan, Otero-Millan, Jorge, Kheradmand, Amir, McClenney, Ayodele, Newman-Toker, David
Journal/Book
Digital Biomarkers
Year
2020
Abstract
Objective: Differentiating benign from dangerous causes of dizziness or vertigo presents a major diagnostic challenge for many clinicians. Bedside presentations of peripheral vestibular disorders and posterior fossa strokes are often indistinguishable other than by a few subtle vestibular eye movements. The most challenging of these to interpret is the head impulse test (HIT) of vestibulo-ocular reflex (VOR) function. There have been major advances in portable video-oculography (VOG) quantification of the video HIT (vHIT), but these specialized devices are not routinely available in most clinical settings. As a first step towards smartphone-based diagnosis of strokes in patients presenting vestibular symptoms, we sought proof of concept that we could use a smartphone application (“app”) to accurately record the vHIT. Methods: This was a cross-sectional agreement study comparing a novel index test (smartphone-based vHIT app) to an accepted reference standard test (VOG-based vHIT) for measuring VOR function. We recorded passive (examiner-performed) vHIT sequentially with both methods in a convenience sample of patients visiting an otoneurology clinic. We quantitatively correlated VOR gains (ratio of eye to head movements during the HIT) from each side/ear and experts qualitatively assessed the physiologic traces by the two methods. Results: We recruited 11 patients; 1 patient’s vHIT could not be reliably quantified with either device. The novel and reference test VOR gain measurements for each ear (n = 20) were highly correlated (Pearson’s r = 0.9, p = 0.0000001) and, qualitatively, clinically equivalent. Conclusions: This preliminary study provides proof of concept that an “eyePhone” app could be used to measure vHIT and eventually developed to diagnose vestibular strokes by smartphone.
Citation
Digit Biomark 2021;5:1–8
Broad Topic
Diagnosis
Measuring eye movements