Development of a Prototype Video Head Impulse Test System Using an iPhone for Screening of Peripheral Vestibular Dysfunction.

Q1 Computer Science
Digital Biomarkers Pub Date : 2023-11-02 eCollection Date: 2023-01-01 DOI:10.1159/000534543
Tatsuaki Kuroda, Kazuhiro Kuroda, Hiroaki Fushiki
{"title":"Development of a Prototype Video Head Impulse Test System Using an iPhone for Screening of Peripheral Vestibular Dysfunction.","authors":"Tatsuaki Kuroda,&nbsp;Kazuhiro Kuroda,&nbsp;Hiroaki Fushiki","doi":"10.1159/000534543","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Head impulse, nystagmus, and test of skew (HINTS) is more accurate for the early diagnosis of occipital fossa stroke than magnetic resonance imaging. However, the head impulse test (HIT) is relatively challenging to perform, as it is subjective. Herein, we developed a prototype video HIT (vHIT) system using an iPhone (Apple, Cupertino, CA, USA) that is compact, easy to operate, and analyzable by our iPhone application.</p><p><strong>Methods: </strong>The iPhone-vHIT and a vHIT using EyeSeeCam (Interacoustics, Eden Prairie, NM, USA) were performed on a healthy man in his 30s and on a patient with vestibular neuritis who visited the Mejiro University Ear Institute Clinic. For the iPhone-vHIT, eye movements were detected by analyzing high-speed videos captured using an iPhone camera, and head movements were followed using an iPhone gyro sensor. An iPhone fixation brace was used to capture the video without any blurring.</p><p><strong>Results: </strong>The iPhone-vHIT system obtained vHIT waveforms similar to those of the EyeSeeCam-vHIT system in the healthy man and the patient with vestibular neuritis. The iPhone-vHIT system effectively detected the reduced vestibulo-ocular reflex gain in patients with vestibular neuritis. The iPhone-vHIT system at 120 frames per second was less sensitive to catch-up saccades than the EyeSeeCam.</p><p><strong>Conclusion: </strong>vHIT systems using a smartphone have been reported but are currently unavailable. At present, the iPhone-vHIT application in this study is the only available smartphone-based vHIT system for screening of peripheral vestibular dysfunction. We believe that the prototype iPhone-vHIT with a high-speed camera will be clinically used to perform the vHIT, even though it only examines the lateral semicircular canal.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"7 1","pages":"150-156"},"PeriodicalIF":0.0000,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10622167/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Biomarkers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1159/000534543","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: Head impulse, nystagmus, and test of skew (HINTS) is more accurate for the early diagnosis of occipital fossa stroke than magnetic resonance imaging. However, the head impulse test (HIT) is relatively challenging to perform, as it is subjective. Herein, we developed a prototype video HIT (vHIT) system using an iPhone (Apple, Cupertino, CA, USA) that is compact, easy to operate, and analyzable by our iPhone application.

Methods: The iPhone-vHIT and a vHIT using EyeSeeCam (Interacoustics, Eden Prairie, NM, USA) were performed on a healthy man in his 30s and on a patient with vestibular neuritis who visited the Mejiro University Ear Institute Clinic. For the iPhone-vHIT, eye movements were detected by analyzing high-speed videos captured using an iPhone camera, and head movements were followed using an iPhone gyro sensor. An iPhone fixation brace was used to capture the video without any blurring.

Results: The iPhone-vHIT system obtained vHIT waveforms similar to those of the EyeSeeCam-vHIT system in the healthy man and the patient with vestibular neuritis. The iPhone-vHIT system effectively detected the reduced vestibulo-ocular reflex gain in patients with vestibular neuritis. The iPhone-vHIT system at 120 frames per second was less sensitive to catch-up saccades than the EyeSeeCam.

Conclusion: vHIT systems using a smartphone have been reported but are currently unavailable. At present, the iPhone-vHIT application in this study is the only available smartphone-based vHIT system for screening of peripheral vestibular dysfunction. We believe that the prototype iPhone-vHIT with a high-speed camera will be clinically used to perform the vHIT, even though it only examines the lateral semicircular canal.

Abstract Image

Abstract Image

Abstract Image

使用iPhone开发用于筛查外周前庭功能障碍的视频头部脉冲测试系统原型。
引言:与磁共振成像相比,头部冲动、眼球震颤和偏斜测试(HINTS)对枕窝卒中的早期诊断更准确。然而,头部冲击测试(HIT)相对来说具有挑战性,因为它是主观的。在此,我们使用iPhone(Apple,Cupertino,CA,USA)开发了一个原型视频HIT(vHIT)系统,该系统结构紧凑,易于操作,可通过我们的iPhone应用程序进行分析。方法:使用EyeSeeCam(Interacoustics,Eden Prairie,NM,USA)对一名30多岁的健康男性和一名到访梅吉罗大学耳朵研究所诊所的前庭神经炎患者进行iPhone vHIT和vHIT。对于iPhone vHIT,通过分析使用iPhone相机拍摄的高速视频来检测眼球运动,并使用iPhone陀螺仪传感器跟踪头部运动。一个iPhone固定支架被用来拍摄视频,没有任何模糊。结果:iPhone vHIT系统在健康男性和前庭神经炎患者中获得了与EyeSeeCam vHIT类似的vHIT波形。iPhone vHIT系统有效地检测到前庭神经炎患者前庭-眼反射增益的降低。每秒120帧的iPhone vHIT系统对追赶扫视的敏感度不如EyeSeeCam。结论:使用智能手机的vHIT系统已被报道,但目前不可用。目前,本研究中的iPhone vHIT应用程序是唯一可用的基于智能手机的vHIT系统,用于筛查外周前庭功能障碍。我们相信,带有高速摄像头的iPhone vHIT原型将在临床上用于进行vHIT,尽管它只检查侧半规管。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信