Title: mVOR: An mHealth approach to the clinical assessment of gaze stability and telerehabilitation of vestibular dysfunction Abstract: Patients with vestibular dysfunction often suffer from gaze instability and an increased risk of falls. Current practice guidelines recommend the use of vestibular rehabilitation for vestibular dysfunction. If patients need to undergo home therapy, additional sensors and instrumentation can pose a challenge in supporting the use of telehealth to objectively assess the contribution of the vestibulo-ocular reflex (VOR) to gaze stability objectively. Following head velocity-based parameters for vestibular rehabilitation has been shown to be effective in patients with dizziness and disequilibrium due to peripheral vestibular loss. However, head velocity-specific goals can largely be ignored as part of home vestibular physical therapy because there is no user-friendly way to directly measure head and eye motion without being connected to some form of external hardware. Although there have been notable attempts to utilize virtual reality and mobile-based technology to monitor postural balance and head motion, advances in native smartphone-based technology and computer vision models could provide us the ability to develop a simple, patient-friendly approach to assessing the VOR. In this project, we aim to develop a mHealth app (mVOR) under the guidance of expert practitioners who specialize in the care of patients with vestibular dysfunction. mVOR will allow for a self-administered vestibular dysfunction assessment by approximating the VOR with a well-established psychophysical test, the gaze stabilization test (GST) protocol. We plan to develop a user-friendly mHealth app that can provide gaze stability outcomes accessible by patients (mVOR: APP) and clinicians (mVOR: DMP). mVOR will ultimately provide users with a single clinical outcome measure (GST score): the highest head velocity (in degrees per second) at which they can maintain their visual acuity. Through the mVOR, the user's smartphone front camera and microphone will accurately obtain visual acuity data and visual processing speeds and track head and eye movements acquired by computer vision algorithms and human- computer interactions. The mVOR: DMP app will graphically summarize results from the mVOR test protocol, which may aid in further shared decision-making from anywhere. Human subject trials performed at our partnering research institution (University of Virginia) will ultimately pave the way for studying the usability, feasibility, and validity of this tool in patients with vestibular dysfunction best served by home vestibular rehabilitation.