Proof of Concept for an "eyePhone" App to Measure Video Head Impulses.

Q1 Computer Science Digital Biomarkers Pub Date : 2020-12-30 eCollection Date: 2021-01-01 DOI:10.1159/000511287
T Maxwell Parker, Nathan Farrell, Jorge Otero-Millan, Amir Kheradmand, Ayodele McClenney, David E Newman-Toker
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引用次数: 11

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.

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用于测量视频头部脉冲的“eyePhone”应用程序的概念验证。
目的:区分良性与危险原因的头晕或眩晕是许多临床医生面临的主要诊断挑战。外周前庭疾病和后窝中风的床边表现除了一些细微的前庭眼球运动外,通常难以区分。其中最具挑战性的是前庭-眼反射(VOR)功能的头部脉冲测试(HIT)。在便携式视频视觉成像(VOG)量化视频HIT (vHIT)方面取得了重大进展,但这些专门的设备在大多数临床环境中并不常见。作为基于智能手机诊断出现前庭症状的中风患者的第一步,我们寻求概念证明,我们可以使用智能手机应用程序(“应用程序”)来准确记录vHIT。方法:这是一项横断面协议研究,比较了一种新的指数测试(基于智能手机的vHIT应用程序)和一种公认的参考标准测试(基于vog的vHIT)来测量VOR功能。我们记录被动(检查员执行)vHIT顺序用两种方法方便样本的患者访问耳神经病学诊所。我们定量地关联了每侧/耳朵的VOR增益(HIT期间眼睛与头部运动的比率),专家通过两种方法定性地评估了生理痕迹。结果:我们招募了11例患者;两种仪器均不能可靠地量化1例患者的vHIT。每只耳朵(n = 20)的新试验和参考试验的VOR增益测量值高度相关(Pearson’s r = 0.9, p = 0.0000001),并且在质量上临床等效。结论:这项初步研究提供了概念证明,“eyePhone”应用程序可以用于测量vHIT,并最终开发用于通过智能手机诊断前庭中风。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Digital Biomarkers
Digital Biomarkers Medicine-Medicine (miscellaneous)
CiteScore
10.60
自引率
0.00%
发文量
12
审稿时长
23 weeks
期刊最新文献
The State of Digital Biomarkers in Mental Health. The Imperative of Voice Data Collection in Clinical Trials. eHealth and mHealth in Antimicrobial Stewardship Programs. Detecting Longitudinal Trends between Passively Collected Phone Use and Anxiety among College Students. Video Assessment to Detect Amyotrophic Lateral Sclerosis.
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