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AbstractScientific conferences and meetings are an integral part of careers in research, medicine, education, and many other professional arenas. Such meetings allow professionals and researchers to share their findings, support expansion of professional networks, enhance professional development, and foster new collaborations. However, barriers throughout the conference experience lead to the exclusion of experts with disabilities, deepening existing inequities in the STEMM (science, technology, engineering, mathematics, and medicine) workforce. This is especially problematic for STEMM experts with blindness or low vision, who remain significantly under-represented throughout the health and science ecosystem. [ABSTRACT FROM AUTHOR]

People with blindness and low vision (pBLV) encounter substantial challenges when it comes to comprehensive scene recognition and precise object identification in unfamiliar environments. Additionally, due to the vision loss, pBLV have difficulty in accessing and identifying potential tripping hazards independently. Previous assistive technologies for the visually impaired often struggle in real-world scenarios due to the need for constant training and lack of robustness, which limits their effectiveness, especially in dynamic and unfamiliar environments, where accurate and efficient perception is crucial. Therefore, we frame our research question in this paper as: How can we assist pBLV in recognizing scenes, identifying objects, and detecting potential tripping hazards in unfamiliar environments, where existing assistive technologies often falter due to their lack of robustness? We hypothesize that by leveraging large pretrained foundation models and prompt engineering, we can create a system that effectively addresses the challenges faced by pBLV in unfamiliar environments. Motivated by the prevalence of large pretrained foundation models, particularly in assistive robotics applications, due to their accurate perception and robust contextual understanding in real-world scenarios induced by extensive pretraining, we present a pioneering approach that leverages foundation models to enhance visual perception for pBLV, offering detailed and comprehensive descriptions of the surrounding environment and providing warnings about potential risks. Specifically, our method begins by leveraging a large-image tagging model (i.e., Recognize Anything Model (RAM)) to identify all common objects present in the captured images. The recognition results and user query are then integrated into a prompt, tailored specifically for pBLV, using prompt engineering. By combining the prompt and input image, a vision-language foundation model (i.e., InstructBLIP) generates detailed and comprehensive descriptions of the environment and identifies potential risks in the environment by analyzing environmental objects and scenic landmarks, relevant to the prompt. We evaluate our approach through experiments conducted on both indoor and outdoor datasets. Our results demonstrate that our method can recognize objects accurately and provide insightful descriptions and analysis of the environment for pBLV. [ABSTRACT FROM AUTHOR]

Visual impairment-related disabilities have become increasingly pervasive. Current reports estimate a total of 36 million persons with blindness and 217 million persons with moderate to severe visual impairment worldwide. Assistive technologies (AT), including text-to-speech software, navigational/spatial guides, and object recognition tools have the capacity to improve the lives of people with blindness and low vision. However, access to such AT is constrained by high costs and implementation barriers. More recently, expansive growth in mobile computing has enabled many technologies to be translated into mobile applications. As a result, a marketplace of accessibility apps has become available, yet no framework exists to facilitate navigation of this voluminous space. We developed the BLV (Blind and Low Vision) App Arcade: a fun, engaging, and searchable curated repository of app AT broken down into 11 categories spanning a wide variety of themes from entertainment to navigation. Additionally, a standardized evaluation metric was formalized to assess each app in five key dimensions: reputability, privacy, data sharing, effectiveness, and ease of use/accessibility. In this paper, we describe the methodological approaches, considerations, and metrics used to find, store and score mobile applications. The development of a comprehensive and standardized database of apps with a scoring rubric has the potential to increase access to reputable tools for the visually impaired community, especially for those in low- and middle-income demographics, who may have access to mobile devices but otherwise have limited access to more expensive technologies or services. A wide array of assistive mobile applications now serve as low cost, convenient, and effective alternatives to standard tools in the rehabilitation domain. Given an extensive (and growing) marketplace of assistive apps, we highlight the importance of developing standardized evaluation frameworks that serve to assess the merit, functionality, and accessibility of tools in respective rehabilitation fields. To provide an introduction to a novel resource accessible to the public to exhibit verified and reliable assistive apps for the visually impaired community, especially for those in low- and middle-income demographics who may not have access to common technologies and services. [ABSTRACT FROM AUTHOR]

Based on statistics from the WHO and the International Agency for the Prevention of Blindness, an estimated 43.3 million people have blindness and 295 million have moderate and severe vision impairment globally as of 2020, statistics expected to increase to 61 million and 474 million respectively by 2050, staggering numbers. Blindness and low vision (BLV) stultify many activities of daily living, as sight is beneficial to most functional tasks. Assistive technologies for persons with blindness and low vision (pBLV) consist of a wide range of aids that work in some way to enhance one's functioning and support independence. Although handheld and head-mounted approaches have been primary foci when building new platforms or devices to support function and mobility, this perspective reviews potential shortcomings of these form factors or embodiments and posits that a body-centered approach may overcome many of these limitations. [ABSTRACT FROM AUTHOR]

Pronounced disparities exist in detecting and treating breast cancer in women with disabilities, leading to cancer detection at advanced stages. This paper provides an overview of disparities for women with disabilities related to breast cancer screening and care, primarily focusing on clinically significant mobility disabilities. Current care gaps include screening barriers related to accessibility and inequitable treatment options, with race and ethnicity, socioeconomic status, geographic location, and disability severity factors mediating the disparities for this population. The reasons for these disparities are myriad and stem from both system-level deficiencies and individual-level clinician bias. Although structural changes are warranted, individual healthcare professionals must also be incorporated into the requisite change. Intersectionality is critical to disparities and inequities and should be central to any discussion of strategies for improving care for people with disabilities, many of whom have intersectional identities. Efforts to reduce screening rate disparities for breast cancer in women with mobility-related disabilities should start with improving accessibility through removing structural barriers, establishing comprehensive accessibility standards, and addressing healthcare professional bias. Future interventional studies are needed to implement and assess the value of programs to improve breast cancer screening rates in women with disabilities. Increasing the representation of women with disabilities in clinical trials may provide another avenue for reducing treatment disparities because these trials often provide breakthrough treatment to women with cancer diagnosed at later stages. Ultimately, attention to the specific needs of patients with disabilities should be improved across the United States to promote inclusive and effective cancer screening and treatment. [ABSTRACT FROM AUTHOR]

Blindness and low vision are an urgent, steadily increasing public health concern. One of the most dramatic consequences of the debilitating conditions that cause visual impairment (VI) is the loss of mobility. Immobility is a grave impediment to quality of life. Orientation and mobility (O&M) training is a profession specific to VI that teaches safe, efficient, and effective travel skills to persons of all ages and in all types of environments. However, the lack of standardized best practices for objective assessment of performance and the exposure of trainees to harm during training are key hurdles for O&M education success. To partially mitigate these drawbacks, we propose a virtual reality platform that can support O&M trainers in the evaluation and refinement of O&M practice, help O&M trainees learn new O&M techniques in a completely safe, yet realistic, environment, and raise awareness for VI in the general public. The proposed platform is tested with a proof-of-concept experiment that evaluates the clinical utility of a custom VI simulation, the immersivity of the virtual reality experience—a crucial attribute for training and educational purposes—and participants' disability awareness and gained knowledge about the challenges faced by persons with VI in their daily life. The first concept is tested by assessing participants' performance in virtual reality-based wayfinding tasks while the second and third are tested through a series of dedicated questionnaires. [ABSTRACT FROM AUTHOR]

Introduction: Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease. Complementary and alternative therapies are increasingly utilized to address its complex multisystem symptomatology. Art therapy involves motoric action and visuospatial processing while promoting broad biopsychosocial wellness. The process involves hedonic absorption, which provides an escape from otherwise persistent and cumulative PD symptoms, refreshing internal resources. It involves the expression in nonverbal form of multilayered psychological and somatic phenomena; once these are externalized in a symbolic arts medium, they can be explored, understood, integrated, and reorganized through verbal dialogue, effecting relief and positive change. Methods: 42 participants with mild to moderate PD were treated with 20 sessions of group art therapy. They were assessed before and after therapy with a novel arts-based instrument developed to match the treatment modality for maximum sensitivity. The House-Tree-Person PD Scale (HTP-PDS) assesses motoric and visuospatial processing–core PD symptoms–as well as cognition (thought and logic), affect/mood, motivation, self (including body-image, self-image, and self efficacy), interpersonal functioning, creativity, and overall level of functioning. It was hypothesized that art therapy will ameliorate core PD symptoms and that this will correlate with improvements in all other variables. Results: HTP-PDS scores across all symptoms and variables improved significantly, though causality among variables was indeterminate. Discussion: Art therapy is a clinically efficacious complementary treatment for PD. Further research is warranted to disentangle causal pathways among the aforementioned variables, and additionally, to isolate and examine the multiple, discrete healing mechanisms believed to operate simultaneously in art therapy. [ABSTRACT FROM AUTHOR]

Background : Blind/low vision (BLV) severely limits information about our three-dimensional world, leading to poor spatial cognition and impaired navigation. BLV engenders mobility losses, debility, illness, and premature mortality. These mobility losses have been associated with unemployment and severe compromises in quality of life. VI not only eviscerates mobility and safety but also, creates barriers to inclusive higher education. Although true in almost every high-income country, these startling facts are even more severe in low- and middle-income countries, such as Thailand. We aim to use VIS4ION (Visually Impaired Smart Service System for Spatial Intelligence and Onboard Navigation), an advanced wearable technology, to enable real-time access to microservices, providing a potential solution to close this gap and deliver consistent and reliable access to critical spatial information needed for mobility and orientation during navigation. Methods: We are leveraging 3D reconstruction and semantic segmentation techniques to create a digital twin of the campus that houses Mahidol University's disability college. We will do cross-over randomization, and two groups of randomized VI students will deploy this augmented platform in two phases: a passive phase, during which the wearable will only record location, and an active phase, in which end users receive orientation cueing during location recording. A group will perform the active phase first, then the passive, and the other group will experiment reciprocally. We will assess for acceptability, appropriateness, and feasibility, focusing on experiences with VIS4ION. In addition, we will test another cohort of students for navigational, health, and well-being improvements, comparing weeks 1 to 4. We will also conduct a process evaluation according to the Saunders Framework. Finally, we will extend our computer vision and digital twinning technique to a 12-block spatial grid in Bangkok, providing aid in a more complex environment. Discussion: Although electronic navigation aids seem like an attractive solution, there are several barriers to their use; chief among them is their dependence on either environmental (sensor-based) infrastructure or WiFi/cell "connectivity" infrastructure or both. These barriers limit their widespread adoption, particularly in low-and-middle-income countries. Here we propose a navigation solution that operates independently of both environmental and Wi-Fi/cell infrastructure. We predict the proposed platform supports spatial cognition in BLV populations, augmenting personal freedom and agency, and promoting health and well-being. Trial registration: ClinicalTrials.gov under the identifier: NCT03174314, Registered 2017.06.02. [ABSTRACT FROM AUTHOR]

The inclusion of people with disabilities has historically been, and continues to be, challenging work. In the health professions, the practice of inclusion should promote and advance the dissemination of efforts to decrease the impact of societal and physical barriers on the lives of people with disability, as well as promote innovative approaches to effectively foster an inclusive society. In addition to a focus on concepts such as the intact abilities of people with disabilities and the facilitation of community participation, an important shift in inclusion-related research requires listening to the lived experience of individuals with disabilities. Listening to their lived experiences and including the valuable insights gleaned from their insider's perspective can enrich efforts to evaluate clinical and educational programs, define population needs, and set research agendas and rehabilitation goals. Building on seminal work from Tamara Dembo, Beatrice Wright, and Margaret Brown, this communication from the Disability Representation Task Force at the American Congress of Rehabilitation Medicine also explores how healthcare providers living with a disability can make a significant contribution to rehabilitation treatment by analyzing how their own experience applies to clinical practice. [ABSTRACT FROM AUTHOR]

Vision-based localization approaches now underpin newly emerging navigation pipelines for myriad use cases, from robotics to assistive technologies. Compared to sensor-based solutions, vision-based localization does not require pre-installed sensor infrastructure, which is costly, time-consuming, and/or often infeasible at scale. Herein, we propose a novel vision-based localization pipeline for a specific use case: navigation support for end users with blindness and low vision. Given a query image taken by an end user on a mobile application, the pipeline leverages a visual place recognition (VPR) algorithm to find similar images in a reference image database of the target space. The geolocations of these similar images are utilized in a downstream task that employs a weighted-average method to estimate the end user's location. Another downstream task utilizes the perspective-n-point (PnP) algorithm to estimate the end user's direction by exploiting the 2D–3D point correspondences between the query image and the 3D environment, as extracted from matched images in the database. Additionally, this system implements Dijkstra's algorithm to calculate a shortest path based on a navigable map that includes the trip origin and destination. The topometric map used for localization and navigation is built using a customized graphical user interface that projects a 3D reconstructed sparse map, built from a sequence of images, to the corresponding a priori 2D floor plan. Sequential images used for map construction can be collected in a pre-mapping step or scavenged through public databases/citizen science. The end-to-end system can be installed on any internet-accessible device with a camera that hosts a custom mobile application. For evaluation purposes, mapping and localization were tested in a complex hospital environment. The evaluation results demonstrate that our system can achieve localization with an average error of less than 1 m without knowledge of the camera's intrinsic parameters, such as focal length. [ABSTRACT FROM AUTHOR]

Number and picture rapid automatized naming (RAN) tests are useful sideline diagnostic tools. The main outcome measure of these RAN tests is the completion time, which is prolonged with a concussion, yet yields no information about eye movement behavior. We investigated eye movements during a digitized Mobile Universal Lexicon Evaluation System (MULES) test of rapid picture naming. A total of 23 participants with a history of concussion and 50 control participants performed MULES testing with simultaneous eye tracking. The test times were longer in participants with a concussion (32.4 s [95% CI 30.4, 35.8] vs. 26.9 s [95% CI 25.9, 28.0], t = 6.1). The participants with a concussion made more saccades per picture than the controls (3.6 [95% CI 3.3, 4.1] vs. 2.7 [95% CI 2.5, 3.0]), and this increase was correlated with longer MULES times (r = 0.46, p = 0.026). The inter-saccadic intervals (ISI) did not differ between the groups, nor did they correlate with the test times. Following a concussion, eye movement behavior differs during number versus picture RAN performance. Prior studies have shown that ISI prolongation is the key finding for a number-based RAN test, whereas this study shows a primary finding of an increased saccade number per picture with a picture-based RAN test. Number-based and picture-based RAN tests may be complimentary in concussion detection, as they may detect different injury effects or compensatory strategies. [ABSTRACT FROM AUTHOR]

Smart health applications have received significant attention in recent years. Novel applications hold significant promise to overcome many of the inconveniences faced by persons with disabilities throughout daily living. For people with blindness and low vision (BLV), environmental perception is compromised, creating myriad difficulties. Precise localization is still a gap in the field and is critical to safe navigation. Conventional GNSS positioning cannot provide satisfactory performance in urban canyons. 3D mapping-aided (3DMA) GNSS may serve as an urban GNSS solution, since the availability of 3D city models has widely increased. As a result, this study developed a real-time 3DMA GNSS-positioning system based on state-of-the-art 3DMA GNSS algorithms. Shadow matching was integrated with likelihood-based ranging 3DMA GNSS, generating positioning hypothesis candidates. To increase robustness, the 3DMA GNSS solution was then optimized with Doppler measurements using factor graph optimization (FGO) in a loosely-coupled fashion. This study also evaluated positioning performance using an advanced wearable system's recorded data in New York City. The real-time forward-processed FGO can provide a root-mean-square error (RMSE) of about 21 m. The RMSE drops to 16 m when the data is post-processed with FGO in a combined direction. Overall results show that the proposed loosely-coupled 3DMA FGO algorithm can provide a better and more robust positioning performance for the multi-sensor integration approach used by this wearable for persons with BLV. [ABSTRACT FROM AUTHOR]

Although the physiatric community increasingly embraces evidence-based medicine (EBM), the current state of EBM training for trainees in physiatry is unclear. The purposes of this article are to report the results of the Association of Academic Physiatrists' surveys of physiatry residency programs in the United States, to discuss the implications of their findings, and to better delineate the "baseline" upon which sound and clear recommendations for systematic EBM training can be made. The two Association of Academic Physiatrists surveys of US physiatry residency programs reveal that most survey respondents report that they include EBM training in their programs that covers the five recommended steps of EBM core competencies. However, although most respondents reported using traditional pedagogic methods of training such as journal club, very few reported that their EBM training used a structured and systematic approach. Future work is needed to support and facilitate physiatry residency programs interested in adopting structured EBM training curricula that include recommended EBM core competencies and the evaluation of their impact. [ABSTRACT FROM AUTHOR]

A group of international researchers and editors summarize how (promptly and easily) an original manuscript can be written using certain tips and tricks. The authors guide novice colleagues with minimal experience using simple hints and straightforward advice in scholarly publishing. The main body of an original article is composed of four parts: Introduction, Methods, Results, and Discussion (the IMRaD format). We make recommendations about how to write these sections. We also make suggestions regarding the title, abstract, key words, and references. In addition, we underline the importance of carefully reading and following general recommendations for the conduct, reporting, editing, and publication of scholarly papers. Specific guidelines are reviewed for improving clarity, accuracy, and transparency, from protocol registration and ethical approval to submission issues, inclusive of rehabilitation specificities. A thorough review of the mission and instructions of the journals under consideration is also critical, inclusive of manuscript preparation guidelines such as word limits of main text, limits in number and style of references, tables and figures, format, checklist, and other specific instructions. Finally, each and every sentence should be iteratively revised for grammar, style, and clarity. [ABSTRACT FROM AUTHOR]

The article discusses the critical need for improved emergency management practices to better serve individuals with disabilities, highlighting the disproportionate risks they face during disasters. Topics discussed include the historical neglect of disability-specific needs in emergency responses, the need for comprehensive and inclusive research and data collection, and the importance of integrating universal accessibility into disaster planning and response.

Background: Sideline diagnostic tests for concussion are vulnerable to volitional poor performance ("sandbagging") on baseline assessments, motivated by desire to subvert concussion detection and potential removal from play. We investigated eye movements during sandbagging versus best effort on the King-Devick (KD) test, a rapid automatized naming (RAN) task. Methods: Participants performed KD testing during oculography following instructions to sandbag or give best effort. Results: Twenty healthy participants without concussion history were included (mean age 27 ± 8 years). Sandbagging resulted in longer test times (89.6 ± 39.2 s vs 48.2 ± 8.5 s, p <.001), longer inter-saccadic intervals (459.5 ± 125.4 ms vs 311.2 ± 79.1 ms, p <.001) and greater numbers of saccades (171.4 ± 47 vs 138 ± 24.2, p <.001) and reverse saccades (wrong direction for reading) (21.2% vs 11.3%, p <.001). Sandbagging was detectable using a logistic model with KD times as the only predictor, though more robustly detectable using eye movement metrics. Conclusions: KD sandbagging results in eye movement differences that are detectable by eye movement recordings and suggest an invalid test score. Objective eye movement recording during the KD test shows promise for distinguishing between best effort and post-injury performance, as well as for identifying sandbagging red flags. [ABSTRACT FROM AUTHOR]

Given the ubiquity of touch for BVI individuals, pandemic-related concerns around touch and the need to minimize contact with other people and public-facing surfaces impose significant challenges. The coronavirus disease 19 (COVID-19) pandemic has created cataclysmic repercussions in virtually every facet of life and has had profound effects on the practice of medicine. COVID-19 and Visual Disability: Can't Look and Now Don't Touch Obvious applications of touch to environmental awareness and spatial cognition include detecting and identifying objects and localizing key features in the environment (eg, doorknobs, railings, and so on).9 However, touch is also an important input for directly supporting safe and efficient navigation. [Extracted from the article]

Sialidosis type 1 is a rare lysosomal storage disorder caused by mutations of the neuraminidase gene. Specific features suggesting this condition include myoclonus, ataxia and macular cherry-red spots. However, phenotypic variability exists. Here, we present detailed clinical and video description of three patients with this rare condition. We also provide an in-depth characterization of eye movement abnormalities, as an additional tool to investigate pathophysiological mechanisms and to facilitate diagnosis. In our patients, despite phenotypic differences, eye movement deficits largely localized to the cerebellum. [ABSTRACT FROM AUTHOR]

Accurate detection and interpretation of eye movement abnormalities often guides differential diagnosis, discussions on prognosis and disease mechanisms, and directed treatment of disabling visual symptoms and signs. A comprehensive clinical eye movement examination is high yield from a diagnostic standpoint; however, skillful recording and quantification of eye movements can increase detection of subclinical deficits, confirm clinical suspicions, guide therapeutics, and generate expansive research opportunities. This review encompasses an overview of the clinical eye movement examination, provides examples of practical diagnostic contributions from quantitative recordings of eye movements, and comments on recording equipment and related challenges. [ABSTRACT FROM AUTHOR]

Highlights • A robust domain-invariant feature is learned. • A model connecting two discriminative neural networks is proposed. • Loss function with metric learning is defined to handle cross-domain issues. • Learned features obtain superior performance on depth-image-based 3D shape retrieval. Abstract In recent years, 3D shape retrieval has been garnering increased attention in a wide range of fields, including graphics, image processing and computer vision. Meanwhile, with the advances in depth sensing techniques, such as those used by the Kinect and 3D LiDAR device, depth images of 3D objects can be acquired conveniently, leading to rapid increases of depth image dataset. In this paper, different from most of the traditional cross-domain 3D shape retrieval approaches that focused on the RGB-D image-based or sketch-based shape retrieval, we aim to retrieve shapes based only on depth image queries. Specifically, we proposed to learn a robust domain-invariant representation between 3D shape and depth image domains by constructing a pair of discriminative neural networks, one for each domain. The two networks are connected by a loss function with constraints on both inter-class and intra-class margins, which minimizes the intra-class variance while maximizing the inter-class margin among data from the two domains (depth image and 3D shape). Our experiments on the NYU Depth V2 dataset (with Kinect-type noise) and two 3D shape (CAD model) datasets (SHREC 2014 and ModelNet) demonstrate that our proposed technique performs superiorly over existing state-of-the-art approaches on depth-image-based 3D shape retrieval task. [ABSTRACT FROM AUTHOR]

Background: Concussion leads to neurophysiologic changes that may result in visual symptoms and changes in ocular motor function. Vision-based testing is used increasingly to improve detection and assess head injury. This review will focus on the historical aspects and emerging data for vision tests, emphasizing rapid automatized naming (RAN) tasks and objective recording techniques, including video-oculography (VOG), as applied to the evaluation of mild traumatic brain injury. Methods: Searches on PubMed were performed using combinations of the following key words: "concussion," "mild traumatic brain injury," "rapid automatized naming," "King-Devick," "mobile universal lexicon evaluation system," "video-oculography," and "eye-tracking." Additional information was referenced from web sites of vendors of commercial eye-tracking systems and services. Results: Tests of rapid number, picture, or symbol naming, termed RAN tasks, have been used in neuropsychological studies since the early 20th century. The visual system contains widely distributed networks that are readily assessed by a variety of functionally distinct RAN tasks. The King-Devick test, a rapid number naming assessment, and several picture-naming tests, such as the Mobile Universal Lexicon Evaluation System (MULES) and the modified Snodgrass and Vanderwart image set, show capacity to identify athletes with concussion. VOG has gained widespread use in eye- and gaze-tracking studies of head trauma from which objective data have shown increased saccadic latencies, saccadic dysmetria, errors in predictive target tracking, and changes in vergence in concussed subjects. Performance impairments on RAN tasks and on tasks recorded with VOG are likely related to ocular motor dysfunction and to changes in cognition, specifically to attention, memory, and executive functioning. As research studies on ocular motor function after concussion have expanded, so too have commercialized eye-tracking systems and assessments. However, these commercial services are still investigational and all vision-based markers of concussion require further validation. Conclusions: RAN tasks and VOG assessments provide objective measures of ocular motor function. Changes in ocular motor performance after concussion reflect generalized neurophysiologic changes affecting a variety of cognitive processes. Although these tests are increasingly used in head injury assessments, further study is needed to validate them as adjunctive diagnostic aids and assessments of recovery. [ABSTRACT FROM AUTHOR]

Objective: To determine if native English speakers (NES) perform differently compared to non-native English speakers (NNES) on a sideline-focused rapid number naming task. A secondary aim was to characterize objective differences in eye movement behaviour between cohorts. Background: The King-Devick (KD) test is a rapid number-naming task in which numbers are read from left-to-right. This performance measure adds vision-based assessment to sideline concussion testing. Reading strategies differ by language. Concussion may also impact language and attention. Both factors may affect test performance. Methods: Twenty-seven healthy  NNES and healthy NES performed a computerized KD test under high-resolution video-oculography.  NNES also performed a Bilingual Dominance Scale (BDS) questionnaire to weight linguistic preferences (i.e., reliance on non-English language(s)). Results: Inter-saccadic intervals were significantly longer in  NNES (346.3 ± 78.3 ms vs. 286.1 ± 49.7 ms, p = 0.001), as were KD test times (54.4 ± 15.1 s vs. 43.8 ± 8.6 s, p = 0.002). Higher BDS scores, reflecting higher native language dominance, were associated with longer inter-saccadic intervals in  NNES. Conclusion: These findings have direct implications for the assessment of athlete performance on vision-based and other verbal sideline concussion tests; these results are particularly important given the international scope of sport. Pre-season baseline scores are essential to evaluation in the event of concussion, and performance of sideline tests in the athlete's native language should be considered to optimize both baseline and post-injury test accuracy. [ABSTRACT FROM AUTHOR]