Advanced Visualization Engineering for Vision Disorders: A Clinically Focused Guide to Current Technology and Future Applications.

Head-mounted visualization technology, often in the form of virtual, augmented, and mixed reality (VAMR), has revolutionized how visual disorders may be approached clinically. In this manuscript, we review the available literature on VAMR for visual disorders and provide a clinically oriented guide to how VAMR technology has been deployed for visual impairments. The chief areas of clinical investigation with VAMR are divided include (1) vision assessment, (2) vision simulation, and (3) vision rehabilitation. We discuss in-depth the current literature of these areas in VAMR and upcoming/future applications to combat the detrimental impact of visual impairment worldwide.

Barriers to care in neovascular age-related macular degeneration: Current understanding, developments, and future directions.

Neovascular age-related macular degeneration is the advanced and irreversible stage of age-related macular degeneration, the leading cause of severe vision loss in older adults. While anti-vascular endothelial growth factor injections have been shown to preserve or improve vision quality in eyes with neovascular age-related macular degeneration, the treatment regimen can be demanding of patients and caregivers, leading to lower rates of adherence. Therefore, it is crucial that disparities and obstacles in neovascular age-related macular degeneration care are identified to improve access to treatment. Review of the current literature revealed 7 major categories of barriers: travel burden, psychological barriers, financial burden and socioeconomic status, treatment regimen, other comorbidities, provider-level barriers, and system-level barriers. We provide an overview of the major barriers to neovascular age-related macular degeneration care that have been reported, as well as gaps in research that need to be investigated further.

Poster Session: Comparison of Dynamic Visual Acuity Assessments in Head-Mounted Technology and Traditional Laptop-based Method.

An impairment in dynamic visual acuity (DVA) has been observed in astronauts shortly after they return to Earth.1 These transitional effects may lead to safety risks during interplanetary spaceflight. At this time, functional vision assessments are performed via laptop onboard the International Space Station. However, DVA is not performed as a standard assessment, and optimization of traditional assessments may aid in more efficient and frequent testing. As part of our group's NASA-funded head-mounted visual assessment system to detect subtle vision changes in long-duration spaceflight2, we present a method to measure DVA in virtual reality. An early validation study was conducted with 5 subjects comparing our novel assessment with a traditional laptop-based test. All participants had a best correctable visual acuity of 20/20, had no past ocular history, balancing disorders, or neurological history. Our DVA assessment framework was built in UnrealEngine 4. The early validation study confirmed that our VR-based DVA assessment performed similarly to traditional laptop-based test (0.485 and 0.525 LogMar respectively, Pearson Correlation = 0.911). A Bland-Altman plot and analysis demonstrated that our DVA assessment data fell within the upper and lower limits of agreement. Future studies are required to further validate this technology; however, these early results showcase VR-based DVA assessment as a promising alternative to laptop-based methods.

Extended reality quantification of pupil reactivity as a non-invasive assessment for the pathogenesis of spaceflight associated neuro-ocular syndrome: A technology validation study for astronaut health.

The National Aeronautics and Space Administration (NASA) has rigorously documented a group of neuro-ophthalmic findings in astronauts during and after long-duration spaceflight known as spaceflight associated neuro-ocular syndrome (SANS). For astronaut safety and mission effectiveness, understanding SANS and countermeasure development are of utmost importance. Although the pathogenesis of SANS is not well defined, a leading hypothesis is that SANS might relate to a sub-clinical increased intracranial pressure (ICP) from cephalad fluid shifts in microgravity. However, no direct ICP measurements are available during spaceflight. To further understand the role of ICP in SANS, pupillometry can serve as a promising non-invasive biomarker for spaceflight environment as ICP is correlated with the pupil variables under illumination. Extended reality (XR) can help to address certain limitations in current methods for efficient pupil testing during spaceflight. We designed a protocol to quantify parameters of pupil reactivity in XR with an equivalent time duration of illumination on each eye compared to pre-existing, non-XR methods. Throughout the assessment, the pupil diameter data was collected using HTC Vive Pro-VR headset, thanks to its eye-tracking capabilities. Finally, the data was used to compute several pupil variables. We applied our methods to 36 control subjects. Pupil variables such as maximum and minimum pupil size, constriction amplitude, average constriction amplitude, maximum constriction velocity, latency and dilation velocity were computed for each control data. We compared our methods of calculation of pupil variables with the non-XR methods existing in the literature. Distributions of the pupil variables such as latency, constriction amplitude, and velocity of 36 control data displayed near-identical results from the non-XR literature for normal subjects. We propose a new method to evaluate pupil reactivity with XR technology to further understand ICP's role in SANS and provide further insight into SANS countermeasure development for future spaceflight.

Video-Based Activity Recognition for Automated Motor Assessment of Parkinson's Disease.

Over the last decade, video-enabled mobile devices have become ubiquitous, while advances in markerless pose estimation allow an individual's body position to be tracked accurately and efficiently across the frames of a video. Previous work by this and other groups has shown that pose-extracted kinematic features can be used to reliably measure motor impairment in Parkinson's disease (PD). This presents the prospect of developing an asynchronous and scalable, video-based assessment of motor dysfunction. Crucial to this endeavour is the ability to automatically recognise the class of an action being performed, without which manual labelling is required. Representing the evolution of body joint locations as a spatio-temporal graph, we implement a deep-learning model for video and frame-level classification of activities performed according to part 3 of the Movement Disorder Society Unified PD Rating Scale (MDS-UPDRS). We train and validate this system using a dataset of n = 7310 video clips, recorded at 5 independent sites. This approach reaches human-level performance in detecting and classifying periods of activity within monocular video clips. Our framework could support clinical workflows and patient care at scale through applications such as quality monitoring of clinical data collection, automated labelling of video streams, or a module within a remote self-assessment system.

GPT Technology to Help Address Longstanding Barriers to Care in Free Medical Clinics.

The implementation of technology in healthcare has revolutionized patient-centered decision making by providing contextualized information about a patient's healthcare journey, leading to increased efficiency (Keyworth et al. in BMC Med Inform Decis Mak 18:93, 2018, https://doi.org/10.1186/s12911-018-0661-3 ). Artificial intelligence has been integrated within Electronic Health Records (EHR) to prompt screenings or diagnostic tests based on a patient's holistic health profile. While larger hospitals have already widely adopted these technologies, free clinics hold lower utilization of these advanced capability EHRs. The patient population at a free clinic faces a multitude of factors that limits their access to comprehensive care, thus requiring necessary efforts and measures to close the gap in healthcare disparities. Emerging Artificial Intelligence (AI) technology, such as OpenAI's ChatGPT, GPT-4, and other large language models (LLMs) have remarkable potential to improve patient care outcomes, promote health equity, and enhance comprehensive and holistic care in resource-limited settings. This paper aims to identify areas in which integrating these LLM AI advancements into free clinics operations can optimize and streamline healthcare delivery to underserved patient populations. This paper also identifies areas of improvements in GPT that are necessary to deliver those services.

Head-Mounted Dynamic Visual Acuity for G-Transition Effects During Interplanetary Spaceflight: Technology Development and Results from an Early Validation Study.

INTRODUCTION: Dynamic visual acuity (DVA) refers to the ability of the eye to discern detail in a moving object and plays an important role whenever rapid physical responses to environmental changes are required, such as while performing tasks onboard a space shuttle. A significant decrease in DVA has previously been noted after astronauts returned from long-duration spaceflight (0.75 eye chart lines, 24 h after returning from space). As part of a NASA-funded, head-mounted multimodal visual assessment system for monitoring vision changes in spaceflight, we elaborate upon the technical development and engineering of dynamic visual acuity assessments with virtual reality (VR) technology as the first step in assessing astronaut performance when undergoing G-transitional effects. We also report results from an early validation study comparing VR DVA assessment with traditional computer based DVA assessment.METHODS: Various VR/AR headsets have been utilized to implement DVA tests. These headsets include HTC Vive Pro Eye system. Epic's game engine UnrealEngine 4 Version 4.24 was used to build the framework and SteamVR was used to experience virtual reality content. Eye tracking technology was used to maintain fixation of the participant. An early validation study with five participants was conducted comparing this technology versus traditional DVA with a laptop.RESULTS: The head-mounted technology developed for assessing DVA changes during G-transitions is fully functional. The results from the early validation study demonstrated that the two DVA tests (laptop-based and VR) indicated a strong association between both methods (Pearson correlation coefficient of 0.91). A Bland-Altman plot was employed to assess levels of agreement, with all data points falling within the limits of agreement.DISCUSSION: The results from this early validation study indicate that head-mounted DVA assessment performs similarly to traditional laptop-based methods and is a promising method for assessing DVA during spaceflight, particularly in G-transitions. Future studies are required for further assessment of validation and reliability of this technology. With its ease of use, accessibility, and portable design, VR DVA has the potential in the near-future to replace conventional methods of assessing DVA. The technology will likely be an important aspect to help monitor functionality and safety during interplanetary missions where astronauts are exposed to G-transitions.Waisberg E, Ong J, Zaman N, Kamran Sa, Lee AG, Tavakkoli A. Head-mounted dynamic visual acuity for G-transition effects during interplanetary spaceflight: technology development and results from an early validation study. Aerosp Med Hum Perform. 2022; 93(11):800-805.

Terrestrial health applications of visual assessment technology and machine learning in spaceflight associated neuro-ocular syndrome.

The neuro-ocular effects of long-duration spaceflight have been termed Spaceflight Associated Neuro-Ocular Syndrome (SANS) and are a potential challenge for future, human space exploration. The underlying pathogenesis of SANS remains ill-defined, but several emerging translational applications of terrestrial head-mounted, visual assessment technology and machine learning frameworks are being studied for potential use in SANS. To develop such technology requires close consideration of the spaceflight environment which is limited in medical resources and imaging modalities. This austere environment necessitates the utilization of low mass, low footprint technology to build a visual assessment system that is comprehensive, accessible, and efficient. In this paper, we discuss the unique considerations for developing this technology for SANS and translational applications on Earth. Several key limitations observed in the austere spaceflight environment share similarities to barriers to care for underserved areas on Earth. We discuss common terrestrial ophthalmic diseases and how machine learning and visual assessment technology for SANS can help increase screening for early intervention. The foundational developments with this novel system may help protect the visual health of both astronauts and individuals on Earth.

Neuro-ophthalmic imaging and visual assessment technology for spaceflight associated neuro-ocular syndrome (SANS).

Spaceflight associated neuro-ocular syndrome (SANS) refers to a unique collection of neuro-ophthalmic clinical and imaging findings observed in astronauts after long-duration spaceflight. Current in-flight and postflight imaging modalities (e.g., optical coherence tomography, orbital ultrasound, and funduscopy) have played an instrumental role in the understanding and monitoring of SANS development; however, the precise etiology for this neuro-ophthalmic phenomenon is still not completely understood. SANS may be a potential barrier to future deep space missions, and therefore it is critical to further elucidate the underlying pathophysiology for effective countermeasures. The complexity and unique limitations of spaceflight require careful consideration and integration of leading technology to advance our knowledge of this extraterrestrial syndrome. We describe the current neuro-ophthalmic imaging modalities and hypotheses that have improved our current understanding of SANS, discuss newer developments in SANS imaging (including noninvasive near-infrared spectroscopy) and summarize emerging research in the development of an aspirational future head-mounted virtual reality display with multimodal visual assessment technology for the detection of neuro-ocular findings in SANS.

Use of Ultrasound in Patients With Carpal Tunnel Syndrome: A Cost-Effective Solution to Reduce Delays in Surgical Care.

PURPOSE: Currently, electrodiagnostic testing, which comprises electromyogram (EMG) and nerve conduction studies (NCS), is the most commonly used method for confirming the clinical diagnosis of carpal tunnel syndrome (CTS). Electromyogram and NCS can be costly, can require multiple visits, may induce anxiety, and may be painful for patients. The purpose of this study was to determine whether replacing EMG/NCS with ultrasound (US), performed by the treating surgeon, to diagnose CTS decreases time to surgery and the number of office visits. METHODS: We retrospectively reviewed a database that consisted of patients who presented to our department with numbness and/or tingling in the hand(s). We assessed the patients' histories for any subsequent carpal tunnel release, dates of diagnosis, dates of surgery, the number of CTS-related medical visits, and diagnostic methods employed. A fellowship-trained hand surgeon performed US examination, and the patients were referred for EMG/NCS testing. We collected data prior to surgery using the Boston Carpal Tunnel Questionnaire to evaluate symptom severity scale and functional status scale scores. We performed linear regression to assess differences in the time to surgery and the number of medical visits prior to carpal tunnel release. RESULTS: Patients who had the diagnosis confirmed by the surgeon using US (n = 34) underwent surgical intervention 3-4 weeks earlier, with 1.8 fewer medical visits on average than the number of medical visits for those who had their diagnosis confirmed using EMG/NCS (n = 98). CONCLUSIONS: If a confirmatory method for the diagnosis of CTS is required or desired by the treating surgeon, surgeon-conducted US might have an impact on the efficiency of care for patients with CTS. TYPE OF STUDY/LEVEL OF EVIDENCE: Diagnostic IV.