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

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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).