Faculty Bibliography

OBJECTIVE:Rapid automatized naming (RAN) tasks have been utilized for decades to evaluate neurological conditions. Time scores for the Mobile Universal Lexicon Evaluation System (MULES, rapid picture naming) and Staggered Uneven Number (SUN, rapid number naming) are prolonged (worse) with concussion, mild cognitive impairment, multiple sclerosis and Parkinson's disease. The purpose of this investigation was to compare paper/pencil versions of MULES and SUN with a new digitized format, the MICK app. METHODS:Participants (healthy office-based volunteers, professional women's hockey players), completed two trials of the MULES and SUN tests on both platforms (tablet, paper/pencil). The order of presentation of the testing platforms was randomized. Between-platform variability was calculated using the two-way random-effects intraclass correlation coefficient (ICC). RESULTS:Among 59 participants (median age 32, range 22-83), no significant differences were observed for comparisons of mean best scores for the paper/pencil versus MICK app platforms, counterbalanced for order of administration (P = 0.45 for MULES, P = 0.50 for SUN, linear regression). ICCs for agreement between the MICK and paper/pencil tests were 0.92 (95% CI 0.86, 0.95) for MULES and 0.94 (95% CI 0.89, 0.96) for SUN, representing excellent levels of agreement. Inter-platform differences did not vary systematically across the range of average best time score for either test. CONCLUSION/CONCLUSIONS:The MICK app for digital administration of MULES and SUN demonstrates excellent agreement of time scores with paper/pencil testing. The computerized app allows for greater accessibility and scalability in neurological diseases, inclusive of remote monitoring. Sideline testing for sports-related concussion may also benefit from this technology.

Advanced wearable devices are increasingly incorporating high-resolution multi-camera systems. As state-of-the-art neural networks for processing the resulting image data are computationally demanding, there has been a growing interest in leveraging fifth generation (5G) wireless connectivity and mobile edge computing for offloading this processing closer to end-users. To assess this possibility, this paper presents a detailed simulation and evaluation of 5G wireless offloading for object detection in the case of a powerful, new smart wearable called VIS4ION, for the Blind-and-Visually Impaired (BVI). The current VIS4ION system is an instrumented book-bag with high-resolution cameras, vision processing, and haptic and audio feedback. The paper considers uploading the camera data to a mobile edge server to perform real-time object detection and transmitting the detection results back to the wearable. To determine the video requirements, the paper evaluates the impact of video bit rate and resolution on object detection accuracy and range. A new street scene dataset with labeled objects relevant to BVI navigation is leveraged for analysis. The vision evaluation is combined with a full-stack wireless network simulation to determine the distribution of throughputs and delays with real navigation paths and ray-tracing from new high-resolution 3D models in an urban environment. For comparison, the wireless simulation considers both a standard 4G-Long Term Evolution (LTE) sub-6-GHz carrier and high-rate 5G millimeter-wave (mmWave) carrier. The work thus provides a thorough and detailed assessment of edge computing for object detection with mmWave and sub-6-GHz connectivity in an application with both high bandwidth and low latency requirements.

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.

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.

(1) Background: The King-Devick (KD) rapid number naming test is sensitive for concussion diagnosis, with increased test time from baseline as the outcome measure. Eye tracking during KD performance in concussed individuals shows an association between inter-saccadic interval (ISI) (the time between saccades) prolongation and prolonged testing time. This pilot study retrospectively assesses the relation between ISI prolongation during KD testing and cognitive performance in persistently-symptomatic individuals post-concussion. (2) Results: Fourteen participants (median age 34 years; 6 women) with prior neuropsychological assessment and KD testing with eye tracking were included. KD test times (72.6 ± 20.7 s) and median ISI (379.1 ± 199.1 msec) were prolonged compared to published normative values. Greater ISI prolongation was associated with lower scores for processing speed (WAIS-IV Coding, r = 0.72, p = 0.0017), attention/working memory (Trails Making A, r = -0.65, p = 0.006) (Digit Span Forward, r = 0.57, p = -0.017) (Digit Span Backward, r= -0.55, p = 0.021) (Digit Span Total, r = -0.74, p = 0.001), and executive function (Stroop Color Word Interference, r = -0.8, p = 0.0003). (3) Conclusions: This pilot study provides preliminary evidence suggesting that cognitive dysfunction may be associated with prolonged ISI and KD test times in concussion.

Voluntary rapid eye movements (saccades) redirect the fovea toward objects of visual interest. The saccadic system can be considered as a dual-mode system: in one mode the eye is fixating, in the other it is making a saccade. In this review, we consider two examples of dysfunctional saccades, interrupted saccades in late-onset Tay-Sachs disease and gaze-position dependent opsoclonus after concussion, which fail to properly shift between fixation and saccade modes. Insights and benefits gained from bi-directional collaborative exchange between clinical and basic scientists are emphasized. In the case of interrupted saccades, existing mathematical models were sufficiently detailed to provide support for the cause of interrupted saccades. In the case of gaze-position dependent opsoclonus, existing models could not explain the behavior, but further development provided a reasonable hypothesis for the mechanism underlying the behavior. Collaboration between clinical and basic science is a rich source of progress for developing biologically plausible models and understanding neurological disease. Approaching a clinical problem with a specific hypothesis (model) in mind often prompts new experimental tests and provides insights into basic mechanisms.

The quantitative analysis of saccades in eye movement data unveils information associated with intention, cognition, and health status. Abnormally slow saccades are indicative of neurological disorders and often imply a specific pathological disturbance. However, conventional saccade detection algorithms are not designed to detect slow saccades, and are correspondingly unreliable when saccades are unusually slow. In this article, we propose an algorithm that is effective for the detection of both normal and slow saccades. The proposed algorithm is partly based on modeling saccadic waveforms as piecewise-quadratic signals. The algorithm first decreases noise in acquired eye-tracking data using optimization to minimize a prescribed objective function, then uses velocity thresholding to detect saccades. Using both simulated saccades and real saccades generated by healthy subjects and patients, we evaluate the performance of the proposed algorithm and 10 other detection algorithms. We show the proposed algorithm is more accurate in detecting both normal and slow saccades than other algorithms.