Background <p>Concussion is a common consequence of engaging in collision sports, with the often mild, transient nature of symptoms posing a considerable diagnostic and management challenge. This challenge is vastly magnified for athletes competing at grassroots/non-professional levels, who lack field side access to medical expertise in the assessment of a player’s capacity to continue playing or need for further medical attention. The aim of this pilot study was to evaluate the utility of the BrainEye application and hardware (BrainEye platform) as a concussion screening tool, specifically determining (1) its sensitivity and specificity with respect to identifying an individual with a clinically diagnosed concussion, (2) the stability of the platform through test completion/failure rates, and (3) its usability through operator feedback and uptake/integration into concussion management protocols.</p> Results <p>Using the BrainEye platform, 348 male professional Australian Rules footballers from 10 Australian Football League (AFL) clubs completed 4 simple ocular protocols (pupillary light reflex, PLR; smooth pursuit eye movements, SMP; near-point convergence, NPC; horizontal gaze nystagmus, HGN) at baseline, prior to the onset of the 2022 AFL season, and following the clinical diagnosis of concussion throughout the season during a game/training/practice (<i>n</i> = 11 players immediately following a concussive event, and on 14 occasions 2–7 days following a concussive event). Although club participation and protocol adherence rates were suboptimal, with clubs citing COVID-19 restrictions and cumbersome hardware set-up as primary reasons for non-participation/missing data, a BrainEye score that derived from an algorithm combining smooth pursuit and pupillary light reflex measures, achieved 100% sensitivity relative to clinical judgement, in identifying all instances of clinically diagnosed concussion, and 85% specificity.</p> Conclusions <p>Collectively, the results of this study suggest that by removing the requirement for add-on hardware and providing a smartphone-only option with direct feedback on performance to the user, the BrainEye application may provide a useful screening tool for sport-related concussion.</p>

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Investigating the Utility of the BrainEye Smartphone Eye Tracking Application and Platform in Concussion Management

  • Meaghan Clough,
  • Jade Bartholomew,
  • Owen White,
  • Joanne Fielding

摘要

Background

Concussion is a common consequence of engaging in collision sports, with the often mild, transient nature of symptoms posing a considerable diagnostic and management challenge. This challenge is vastly magnified for athletes competing at grassroots/non-professional levels, who lack field side access to medical expertise in the assessment of a player’s capacity to continue playing or need for further medical attention. The aim of this pilot study was to evaluate the utility of the BrainEye application and hardware (BrainEye platform) as a concussion screening tool, specifically determining (1) its sensitivity and specificity with respect to identifying an individual with a clinically diagnosed concussion, (2) the stability of the platform through test completion/failure rates, and (3) its usability through operator feedback and uptake/integration into concussion management protocols.

Results

Using the BrainEye platform, 348 male professional Australian Rules footballers from 10 Australian Football League (AFL) clubs completed 4 simple ocular protocols (pupillary light reflex, PLR; smooth pursuit eye movements, SMP; near-point convergence, NPC; horizontal gaze nystagmus, HGN) at baseline, prior to the onset of the 2022 AFL season, and following the clinical diagnosis of concussion throughout the season during a game/training/practice (n = 11 players immediately following a concussive event, and on 14 occasions 2–7 days following a concussive event). Although club participation and protocol adherence rates were suboptimal, with clubs citing COVID-19 restrictions and cumbersome hardware set-up as primary reasons for non-participation/missing data, a BrainEye score that derived from an algorithm combining smooth pursuit and pupillary light reflex measures, achieved 100% sensitivity relative to clinical judgement, in identifying all instances of clinically diagnosed concussion, and 85% specificity.

Conclusions

Collectively, the results of this study suggest that by removing the requirement for add-on hardware and providing a smartphone-only option with direct feedback on performance to the user, the BrainEye application may provide a useful screening tool for sport-related concussion.