MICK (Mobile Integrated Cognitive Kit) app: Feasibility of an accessible tablet-based rapid picture and number naming task for concussion assessment in a division 1 college football cohort.

Although visual symptoms are common following concussion, quantitative measures of visual function are missing from concussion evaluation protocols on the athletic sideline. For the past half century, rapid automatized naming (RAN) tasks have demonstrated promise as quantitative neuro-visual assessment tools in the setting of head trauma and other disorders but have been previously limited in accessibility and scalability. The Mobile Interactive Cognitive Kit (MICK) App is a digital RAN test that can be downloaded on most mobile devices and can therefore provide a quantitative measure of visual function anywhere, including the athletic sideline. This investigation examined the feasibility of MICK App administration in a cohort of Division 1 college football players. Participants (n = 82) from a National Collegiate Athletic Association (NCAA) Division 1 football team underwent baseline testing on the MICK app. Total completion times of RAN tests on the MICK app were recorded; magnitudes of best time scores and between-trial learning effects were determined by paired t-test. Consistent with most timed performance measures, there were significant learning effects between the two baseline trials for both RAN tasks on the MICK app: Mobile Universal Lexicon Evaluation System (MULES) (p < 0.001, paired t-test, mean improvement 13.3 s) and the Staggered Uneven Number (SUN) (p < 0.001, mean improvement 3.3 s). This study demonstrated that the MICK App can be feasibly administered in the setting of pre-season baseline testing in a Division I environment. These data provide a foundation for post-injury sideline testing that will include comparison to baseline in the setting of concussion.

The MICK (Mobile integrated cognitive kit) app: Digital rapid automatized naming for visual assessment across the spectrum of neurological disorders.

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: 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.

A Low-Vision Navigation Platform for Economies in Transition Countries.

An ability to move freely, when wanted, is an essential activity for healthy living. Visually impaired and completely blinded persons encounter many disadvantages in their day-to-day activities, including performing work-related tasks. They are at risk of mobility losses, illness, debility, social isolation, and premature mortality. A novel wearable device and computing platform called VIS4ION is reducing the disadvantage gaps and raising living standards for the visually challenged. It provides personal mobility navigational services that serves as a customizable, human-in-the-loop, sensing-to-feedback platform to deliver functional assistance. The platform is configured as a wearable that provides on-board microcomputers, human-machine interfaces, and sensory augmentation. Mobile edge computing enhances functionality as more services are unleashed with the computational gains. The meta-level goal is to support spatial cognition, personal freedom, and activities, and to promoting health and wellbeing. VIS4ION can be conceptualized as the dovetailing of two thrusts: an on-person navigational and computing device and a multimodal functional aid providing microservices through the cloud. The device has on-board wireless capabilities connected through Wi-Fi or 4/5G. The cloud-based microservices reduce hardware and power requirements while allowing existing and new services to be enhanced and added such as loading new map and real-time communication via haptic or audio signals. This technology can be made available and affordable in the economies of transition countries.

MULES on the sidelines: A vision-based assessment tool for sports-related concussion.

OBJECTIVE: The Mobile Universal Lexicon Evaluation System (MULES) is a test of rapid picture naming under investigation. Measures of rapid automatic naming (RAN) have been used for over 50 years to capture aspects of vision and cognition. MULES was designed as a series of 54 grouped color photographs (fruits, random objects, animals) that integrates saccades, color perception and contextual object identification. We examined MULES performance in youth, collegiate and professional athletes at pre-season baseline and at the sidelines following concussion. METHODS: Our study teams administered the MULES to youth, collegiate and professional athletes during pre-season baseline testing. Sideline post-concussion time scores were compared to pre-season baseline scores among athletes with concussion to determine degrees and directions of change. RESULTS: Among 681 athletes (age 17 ±â€¯4 years, range 6-37, 38% female), average test times at baseline were 41.2 ±â€¯11.2 s. The group included 280 youth, 357 collegiate and 44 professional athletes; the most common sports were ice hockey (23%), soccer (17%) and football (11%). Age was a predictor of MULES test times, with longer times noted for younger participants (P < .001, linear regression). Consistent with other timed performance measures, significant learning effects were noted for the MULES during baseline testing with trial 1 test times (mean 49.2 ±â€¯13.1 s) exceeding those for trial 2 (mean 41.3 ±â€¯11.2 s, P < .0001, paired t-test). Among 17 athletes with concussion during the sports seasons captured to date (age 18 ±â€¯3 years), all showed increases (worsening) of MULES time scores from pre-season baseline (median increase 11.2 s, range 0.6-164.2, P = .0003, Wilcoxon signed-rank test). The Symptom Severity Score from the SCAT5 Symptom Evaluation likewise worsened from pre-season baseline following injury among participants with concussion (P = .002). CONCLUSIONS: Concussed athletes demonstrate worsening performance on the MULES test compared to their baseline time scores. This test samples a wide network of brain pathways and complements other vision-based measures for sideline concussion assessment. The MULES test demonstrates capacity to identify athletes with sports-related concussion.

Objectifying eye movements during rapid number naming: Methodology for assessment of normative data for the King-Devick test.

OBJECTIVE: Concussion is a major public health problem and considerable efforts are focused on sideline-based diagnostic testing to guide return-to-play decision-making and clinical care. The King-Devick (K-D) test, a sensitive sideline performance measure for concussion detection, reveals slowed reading times in acutely concussed subjects, as compared to healthy controls; however, the normal behavior of eye movements during the task and deficits underlying the slowing have not been defined. METHODS: Twelve healthy control subjects underwent quantitative eye tracking during digitized K-D testing. RESULTS: The total K-D reading time was 51.24 (±9.7) seconds. A total of 145 saccades (±15) per subject were generated, with average peak velocity 299.5°/s and average amplitude 8.2°. The average inter-saccadic interval was 248.4 ms. Task-specific horizontal and oblique saccades per subject numbered, respectively, 102 (±10) and 17 (±4). Subjects with the fewest saccades tended to blink more, resulting in a larger amount of missing data; whereas, subjects with the most saccades tended to make extra saccades during line transitions. CONCLUSIONS: Establishment of normal and objective ocular motor behavior during the K-D test is a critical first step towards defining the range of deficits underlying abnormal testing in concussion. Further, it sets the groundwork for exploration of K-D correlations with cognitive dysfunction and saccadic paradigms that may reflect specific neuroanatomic deficits in the concussed brain.

Feasibility of a cost-effective, video analysis software-based mobility protocol for objective spine kinematics and gait metrics: a proof of concept study.

The purpose of this study was to investigate the potential of a high-throughput, easily implemented, cost-effective, video analysis software-based mobility protocol to quantify spine kinematics. This prospective cohort study of clinical biomechanics implemented 2-dimensional (2D) image processing at a tertiary-care academic institution. Ten healthy, able-bodied volunteers were recruited for 2D videography of gait and functional motion. The reliability of a 2D video analysis software program for gait and range of motion metrics was evaluated over 2 independent experimental sessions, assessing for inter-trial, inter-session, and inter-rater reliability. Healthy volunteers were evaluated for simple forward and side bending, rotation, treadmill stride length, and more complex seated-to-standing tasks. Based on established intraclass correlation coefficients, results indicated that reliability was considered good to excellent for simple forward and side bending, rotation, stride length, and more complex sit-to-standing tasks. In conclusion, a cost-effective, 2D, video analysis software-based mobility protocol represents a feasible and clinically useful approach for objective spine kinematics and gait metrics. As the complication rate of operative management in the setting of spinal deformity is weighed against functional performance and quality of life measures, an objective analysis tool in combination with an appropriate protocol will aid in clinical assessments and lead to an increased evidence base for management options and decision algorithms.