Development of a mobile medical app for diagnosis and treatment of benign paroxysmal positional vertigo (BPPV)

开发用于诊断和治疗良性阵发性位置性眩晕（BPPV）的移动医疗应用程序

• 批准号: 10661483
• 负责人: COURTNEY HALL
• 金额: --
• 依托单位: JAMES H QUILLEN VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10661483
• 关键词: Algorithmic Software; Automobile Driving; Beds; Benign paroxysmal positional vertigo; Cellular Phone; Clinical; Coupled; Data; Development; Devices; Diagnosis; Diagnostic; Diagnostic tests; Disease; Dizziness; Engineering; Equilibrium; Error Sources; Eye Movements; Face; Feedback; Functional disorder; General Population; Goals; Head; Head Movements; Health Care Costs; Health Personnel; Health Services Accessibility; Improve Access; Instruction; Interruption; Labyrinth; Measures; Motion; Nausea and Vomiting; Organ; Pathologic Nystagmus; Patients; Performance; Positioning Attribute; Primary Care Physician; Procedures; Process; Provider; Rehabilitation therapy; Sampling; Semicircular canal structure; Series; Students; Symptoms; System; Technology; Telephone; Testing; Time; Training; Vertigo; Veterans; Work; accurate diagnosis; barrier to care; brain magnetic resonance imaging; cost; effective therapy; effectiveness evaluation; healthy volunteer; improved; instrumentation; medical schools; military veteran; mobile medical application; otoconia; particle; pilot test; programs; smartphone application; software development; success; usability

Benign Paroxysmal Positional Vertigo (BPPV) is the most common cause of vestibular dysfunction, characterized by brief but disabling vertigo associated with specific head positions (e.g., looking up or rolling over in bed). BPPV can be treated effectively with the Canalith Repositioning Treatment (CRT) which uses a series of head positions to move particles (displaced from the otolith organs into the semicircular canals) out of the semicircular canals. Nevertheless, access to care for many patients with BPPV is poor because the treatment is underused or mis-used by frontline healthcare providers who are not trained to recognize and treat BPPV. Successful diagnosis and treatment of BPPV requires accurate identification of eye movements (nystagmus) during the test procedure and accurate positioning of the patient's head during testing and treatment. The purpose of this project is to test the hypothesis that a smartphone camera and inertial technology can be used to accurately diagnose and treat BPPV. We propose four specific aims: (1) develop a mobile medical application (app) for automated diagnosis and guided treatment of BPPV, (2) determine the accuracy of the app for automated diagnosis of BPPV, (3) determine the usability of the app for automated diagnosis and guided treatment of BPPV, and (4) determine the effectiveness of the app for guided treatment of BPPV. For Aim 1, three tasks are proposed: (1) development of software to record and analyze eye and head movements to diagnose and guide treatment of BPPV, (2) development of headgear to couple the smartphone to the face for accurate eye and head movement recording, and (3) development of tutorial videos to guide the clinician in the proper execution of the Dix-Hallpike maneuver and treatment procedure. The development of the app will be an iterative process in which the engineers will work closely with the expert clinicians who will provide feedback to revise and refine the software algorithm, headgear device, and tutorial videos prior to pilot testing of the app. To determine the accuracy of the app for automated diagnosis of BPPV (Aim 2), the app will be pilot tested on Veterans with complaints of motion-provoked dizziness using the BPPV diagnoses of expert vestibular clinicians as the gold standard. Eye movement recordings of patients with discordant expert versus app diagnoses will be examined to determine the source of the errors and the app/device will be modified accordingly. To determine the usability of the app for automated diagnosis and guided treatment of BPPV (Aim 3), the app will be pilot tested using ten naïve users (first year students in clinical graduate programs or medical school) and ten healthy volunteers (mock patients). Usability will be measured using the System Usability Scale to identify the percentile rank of the product's usability and learnability, and the data will be used to improve usability of the app prior to pilot testing on patients. To determine the effectiveness of the app for guided treatment of BPPV (Aim 4), the app will be pilot tested on ten naïve users who will perform the diagnostic and treatment procedures on Veterans with motion-provoked dizziness. Expert vestibular clinicians will use a performance rubric to rate each user on the adequacy of the diagnostic and treatment procedures. To examine the effectiveness of the app for guided treatment of BPPV, the rating from the performance rubric will be calculated, and adequate performance will be defined as 80% of naïve users achieving a median score of 80%. In addition, the success rate of a single treatment by naïve users will be compared with the success rate of a single treatment by expert clinicians in the Veteran population (86%; Akin et al., 2017) and with the success rate by primary care physicians (40%, Munoz et al., 2007).

良性阵发性位置眩晕（BPPV）是前庭功能障碍的最常见原因， 以简短但禁用与特定头部位置相关的简短但禁用眩晕（例如，查找或滚动 在床上）。可以使用Canalith重新定位处理（CRT）有效地处理BPPV 将颗粒（从耳石器官移动到半圆形管的一系列头部位置）从 半圆形管。但是，许多BPPV患者获得护理的机会很差，因为 一线医疗保健提供者未经训练和治疗的一线医疗保健提供者未充分利用或误会治疗 BPPV。成功的BPPV诊断和治疗需要准确识别眼动运动 （nystagmus）在测试过程中，并在测试过程中准确定位患者的头部 治疗。 该项目的目的是检验智能手机相机和惯性技术的假设 用于准确诊断和治疗BPPV。我们提出了四个具体目标：（1）开发移动医疗 应用（APP）用于自动诊断和BPPV的指导治疗，（2）确定的准确性 用于BPPV自动诊断的应用程序，（3）确定该应用程序对自动诊断的可用性和 BPPV的指导处理，（4）确定应用程序对BPPV的指导处理的有效性。 对于目标1，提出了三个任务：（1）开发软件以记录和分析眼睛和头部 诊断和指导BPPV治疗的动作，（2）开发头饰以搭配智能手机 到脸上进行准确的眼睛和头部运动记录，以及（3）开发教程视频以指导 适当执行Dix-Hallpike操纵和治疗程序的临床。发展的发展 该应用程序将是一个迭代过程，工程师将与专家临床医生紧密合作 提供反馈以修改和完善软件算法，头饰设备和教程视频之前 应用程序的测试。 为了确定该应用程序对BPPV的自动诊断的准确性（AIM 2），该应用程序将进行试点测试 使用专家前庭的BPPV诊断的退伍军人，对动作发达的头晕的抱怨 临床医生是黄金标准。不一致专家与应用患者的眼动记录 将检查诊断以确定错误的根源，并将修改应用程序/设备 根据确定该应用程序对自动诊断的可用性和BPPV的指导处理 （AIM 3），该应用将使用十个幼稚的用户（临床研究生课程的一年级学生或 医学院）和十名健康志愿者（模拟患者）。可用性将使用系统测量 可用性量表以确定产品的可用性和可学习性的百分位等级，数据将是 用于在对患者进行试点测试之前提高应用程序的可用性。确定应用程序的有效性 对于BPPV的指导处理（AIM 4），该应用将对十个幼稚的用户进行试验测试，这些用户将执行该应用程序 具有运动发动的头晕的退伍军人的诊断和治疗程序。专业的前庭临床医生 将使用性能标题来对每个用户的诊断和治疗程序的充分性进行评分。 要检查该应用程序对BPPV的指导处理的有效性，该应用程序的评分来自性能标题 将被计算，并将适当的性能定义为80％的幼稚用户达到中位数得分 80％。此外，将将幼稚用户的单一治疗成功率与成功进行比较 专家临床医生在退伍军人口中的单一治疗率（86％； Akin等，2017），并与 初级保健医生的成功率（40％，Munoz等，2007）。