PUBLICATIONS

Below is a selection of case studies, publications, press releases and reports for EyeGuide and eye tracking technology in general.

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Mixed Martial Art (MMA) Research Study to Understand the Impact of Extreme Sports Activity on Athletes’ Visual Acuityi

Dr. Brian Stillii
Dr. Ben Baroniaiii
Dr. Mike Kellyiv
Manuscript Draft Date: May 19, 2019

There have been extensive studies which report on establishing the use of eye tracking of visual stimuli to assess user attention and cognitive performancev. As Heitger, et al point out,vi while other neuropsychological tools for mTBI/concussion detection often fail or have particular limitations, “Studies in populations with neural injury and neurodegenerative disorders have shown that eye movement control relates closely to the functional integrity of the brain…” (p. 2851). This is why, Heitger, et al continue, “eye movement paradigms have been routinely used in the field of cognitive neuroscience to study the role of factors such as attention, working memory, response inhibition, speed of information processing, predictive behaviour and (motor) planning” (p. 2851).

Maruta et al., (2012) notevii, “Attention is a core function in cognition and also the most prevalent cognitive deficit in mild traumatic brain injury (mTBI). Predictive timing is an essential element of attention functioning because sensory processing and execution of goal-oriented behavior are facilitated by temporally accurate prediction” (n.p.). Users who can visually keep steady, accurate attention on a moving object in their environment, what Maruta et al characterize as Dynamic Visio-Motor Synchronization (DVS), likely suffer from no impairment. But if users, with acceptable visual acuity, cannot keep attention on a moving object in a normal way, then the failure to do so may indicate, along with other measurements part of mTBI/concussion detection protocol, that there is possible neurological impairment. In fact, Maruta’s 2012 study, since confirmed by other similar studiesviii , showed that mTBI subjects “demonstrated DVS scores worse than 95% of normal subjects.”
As compelling as such findings are, for our study we were not interested in further exploring the applicability of DVS testing to determine potential neurological impairment. Rather, in the hopes of understanding if DVS testing could be applied to sports performance training, we question if DVS, when administered to a select group of extreme sports athletes, can detect changes in a user’s visual acuity after a physically demanding event. Specifically, for a study which we report on in this paper, we tested DVS, using a portable eye tracking hardware and software system, in a group of 45 Mixed Martial Arts (MMA) amateur and professional fighters. These fighters were tested before and after bouts and the data collected were analyzed to answer the following research questions:

  1. Would athletes after significant sports activity that challenged them physically and mentally distribute DVS scores lower than those administered to them pre-activity?
  2. Could athletic performance and the extreme fatigue resulting from it negatively impact visual acuity?
  3. In addition, would those athletes who were successful in such sports activity, winning, for example, a fight, present better visual acuity scores after activity compared to those athletes who were not successful?
  4. Finally, would those athletes presenting better pre-fight DVS scores do better than those with inferior scores, signaling that visual acuity superiority may be a factor in successful athletic performance?

Previous performance literature, visual acuity

In 1986 Abernethy hypothesizedix on the impact of experimental optometry techniques related to enhanced sports performance. In a follow up article written some 15 years later, Abernethy et al determined from their study that visual training did not enhance performance.x However, Ciuffreda concluded differently in a later study, arguing that eye-hand reaction time can be improved through training.xi Later articles have continued to support the usefulness of studying and implementing visual acuity training for sports performance. For example, Poltavski and Biberdorf used the Nike Sparq Sensory Training Station to evaluate the ability of hockey players to discriminate visual stimuli, learning in the process that those players with better visual reaction times to particular stimulus scored more goals and had fewer penalty minutes.xii

Research reporting as it relates specifically to smooth pursuit testing and sports performance is more limited. Most relevant to our study is Palidis et al’s recent work that studied this type of eye movement in baseball players, noting “the importance of smooth pursuit eye movements for the ability to resolve spatial detail in moving objects and identifies patterns that might enhance perceptual performance.”xiii In part, our study builds on their work by focusing again on smooth pursuit or DVS assessment as a factor in athletic performance.

Study Population and Test Protocol

Our study’s population consisted of 45 MMA professional fighters (all male) conveniently selected from two MMA events held in 2017: a Cage Fury Fighting Championship (CFFC) held in New Jersey, and a Bellator promotion in Connecticut. Fighter average age was 34, and experience ranged from 1 to 20 years.

All fighters were given pre-fight physicals by board-certified and licensed physicians and drug-tested via urine samples. As part of the pre-fight physical, fighters were tested, either the day before or day of the fight, one at a time using the EyeGuide Focus system. This initial test established a pre-fight baseline score for later comparison against a post-fight score.

After the fight, ringside physicians evaluated each fighter. Physicians made a determination based upon their exam if a fighter needed immediate emergency attention. Only one fighter was sent immediately from the fight location to the hospital for emergency care. All other fighters were then sent to the EyeGuide Focus test area to complete their post-fight Focus test.

To ensure that significant head movement and general body shakiness did not cause false-negative results, no fighter was tested within five minutes of concluding a fight, allowing heart rate to return closer to a resting rate. As an additional mitigation of potential head-movement, the Focus test administrator secured the fighter’s head against the forehead rest during the 10-second test to guarantee no head movement occurred during testing.

Post-fight testing generally occurred 10 minutes after each fight’s conclusion. Aside from this these adjustments necessitate by elevated heart rates and adrenaline, the post-fight Focus test followed the same process as the pre-fight Focus test.

Three fighters did not provide a post-fight evaluation. One was sent to the hospital for care immediately post-fight. The other two refused to participate in the test following fight losses. The data from these three fighters were not included in any analysis comparing pre- and post-fight Focus scoring.

About the EyeGuide Focus DVS Testing System

EyeGuide Focus measures “smooth pursuit” or DVS using a rapid, mobile testing platform. The testing platform consists of power source, a headrest with a built in digital camera for collecting visual data of either eye, and a tablet for showing the visual test and displaying test results. Focus can be stored in a box with a handle for easy movement to testing locations.

Figure 1: EyeGuide Focus System

Testing Procedure and Scoring

Athletes being tested put their head in the headrest and their chin on the chin holder. On a display screen 24 inches away, they then focused on a moving stimulus, which is a white, filled circle against a black background. The stimulus moves in a horizontal or lazy eight pattern to carry out smooth pursuit, DVS testing.

Figure 2: Chin and forehead rest reduces head movement as user follows white stimulus on screen during 10 second smooth pursuit test.

Specifically, the stimulus starts at the center of the display and moves clockwise at 120 Hz following the path of a circle on the right side of the screen. When the stimulus reaches the center of the display, the path changes to a counterclockwise circle on the left side of the screen. The test ends when the stimulus returns to the center of the display. The test lasts exactly 10 seconds. The score is the sum of the absolute difference between the distances two sets of points of the stimulus and the actual eye movement. The Focus test collects 1,200 points of data during the test.

Typically, users record first a baseline score, representing their best score, often occurring pre-sports season for athletes. Subsequent tests may take place at any time. These are done to track a user’s visual performance to understand if particular activities or events, such as strenuous exercise, insufficient sleep causing fatigue, or a play in sports, or accident at work, may cause changes in visual tracking performance.
The lower the score, the greater the DVS accuracy and thus an indication of better visual attention. A higher scoring indicates poor DVS accuracy or an inability on the part of the user to follow smoothly (by location and time) the reticle or focus of attention as it moves across the screen. If the subsequent Focus score is one or more standard deviations or thresholds below the prior “best attempt” baseline score, this result is considered statistically significant. Focus reports the difference, providing a numerical score as well as a visual presentation that shows the prior baseline test pathway in blue with the follow up inferior test pathway overlaid in red.

Establishing Community Baseline Scores

Previous research (Kelly, 2017) has established the efficacy of EyeGuide Focusxiv. Since that publication, Focus has been used to carry out 9,506 tests of males and females ranging from 8-70 years old. Scoring of that population is described in Figure 3, showing distribution into nine scoring thresholds: Very Superior, Superior, High Average, Average, Low Average, Borderline, Poor, Very Poor, and Extremely Poor.

Figure 3: EyeGuide Focus Scoring Thresholds
Of all Focus tests, 5,978 have been recorded as individual baseline tests meant to provide a snapshot of an athlete’s best DVS score for later comparison to subsequent tests.
Figure 4: EyeGuide Focus Baseline Test Scoring Distribution

The baseline test scores, as Figure 4 shows, are normally distributed (with a mean score of 21,737). When the data are separated by sex, the scores remain normally distributed. There is no significant sex effect on Focus scores. Scoring from one year to next is consistent. 448 athletes re-tested one year after recording a previous baseline score showed relatively similar if not subtly improved results (see Figure 5).

Figure 5: Comparison of annual baseline scoring for 448 athletes

MMA Study Results and Discussion

All data were analyzed using IBM SPSS Statistics version 23. Missing data was excluded, and extreme outliers, i.e. scores greater than 250,000, were removed. Descriptive statistics were calculated for all variables. T-tests were used to compare continuous variables such as baseline, concussion, and recovery scores. Paired t-tests were used to detect significant differences between baseline and concussion scores, concussion and recovery scores, and all before and after MMA fight scores. Comparisons of categorical values were analyzed using chi-squared tests. All statistical tests were considered significant at a P value less than 0.05.

MMA fighters were given the Focus test as part of the pre-fight physical. Immediately after the bout, the fighters were re-tested to assess changes in visual acuity following a fight. On average, Focus test scores more than doubled following the bout. There was a significant change
(p<0.001) from the baseline test mean of 17,426.06 to a mean of 37,693.76 following the fight (see Figures 6-8).

Figure 8: Comparison of MMA Fighters Pre and Post Fight Scoring Showing Clear Difference between results. Pre-fight testing in blue, Post-fight in red.

In fact, further analysis demonstrated that 21/40 fighters (52.5%) had a post-fight Focus score greater than two standard deviations above the pre-fight baseline average, demonstrating a significant change in visual acuity following a fight. For example, the following representative overlays show that an individual with a baseline score of 21,803.02 pre-fight (Figure 9) had a significantly increased Focus score, 79,330.20, following the fight (see Figure 10). Using the Baseline Classification from Figure 3, this represents a change from an Average Score to Extremely Poor.

Figure 9: Individual MMA fighter’s pre-fight score

The results of 20 fights were analyzed to determine if there was an interaction between fight performance and fight result. In other words, did the losing fighter display a visual acuity score post-fight lower than the winning fighter? Our analysis revealed no significant interaction between a Focus test score and fight result.

However, fighters with a baseline score in the category “High Average” (n=18) had a lower mean change score (difference between baseline and post-fight score = 12662.2) than the rest of the fighters (mean change = 25338.0) (t(43)=2.12, p=0.0395). 8 of those 18 “High Average” fighters won their fights and recorded “High Average” post-fight scoresxv. Conversely, 7 of 16 of fighters with “Average” pre-fight, baseline scores ended up in the “Extremely Poor” category with post-fight scoresxvi, and they lost their fights. Why did so many High Average fighters win, and so many Average fighters lose?

Conclusions

Although limited in size and scope, this study does demonstrate the potential of DVS testing to identify visual acuity deficit, caused by extreme athletic activity, in the absence of other symptoms. All MMA fighters in the study experienced degraded post-fight visual acuity, as measured by the Focus DVS test, compared to pre-fight visual acuity.

Data from testing did not support a hypothesis that athletic performance, measured by winning or losing, indicated a better or worse post-activity DVS score. Again, all athlete scores decreased post-fight. However, there was enough compelling information, although not statistically significant, to compel future research into the possibility that an athlete with better visual acuity, pre-activity, will perform better during activity. Certainly, this study’s results regarding MMA fighter performance replicates other research connecting better visual acuity with better athletic resultsxvii.

Obvious limitations existed in the study. DVS scoring or smooth pursuit testing are not comprehensive. Other visual acuity testing, to include saccadic and convergence/divergence testing, may yield contrary results. Testing so quickly after such an extreme sports activity may also have impacted DVS scoring results, since an elevated heart rate and/or excessive head movement and blinking have been shown to introduce false negative scoring in visual acuity testing. This study also didn’t account for the potential influence of dominant eye on scoring.

Nevertheless, trends suggested in this study support further implementation of DVS testing to understand visual acuity in athletes, examining those factors that cause changes to it, such as extreme sports activity and related results, including severe fatigue if not mTBI. An argument can also be made to monitor closely the visual acuity of athletes at the beginning and throughout athletic activities (such as entire sports season) to see if changes occur because of such activities. Evidence presented wasn’t compelling enough to suggest also that those with better visual acuity are better at the athletics in which they participate. But data presented offer justification for further study to understand if athletic success is determined, in part, by visual acuity. If so, can such visual acuity be improved as a mechanism to improve performance through consistent visual training?

i to be submitted to the Journal of Sports Sciences
ii Dr. Still is Chief Scientist of EyeGuide, signaling a potential conflict of interest. To mitigate, all data collection and analysis were carried out by other researchers.
iii Dr. Baronia is a board-certified neurosurgeon and clinical assistant professor, Texas Tech University Health Sciences Center
iv Dr. Kelly is a board-certified sports medicine physician affiliated with Procare Medical Associates LLC, Sports Medicine
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xv The difference in mean change score between “High Avg à High Avg” (2052.38) and “High Avg à Other Categories” (24206.15) is significant, p<0.001 xvi The difference in mean change score between “Avg –> Extremely Poor” (44295.7) and “Avg –> Other Categories” (9426.9) is significant, p<0.001
xvii Uchida, Y., Kudoh, D., Higuchi, T., Honda, M., & Kanosue, K. (2013). Dynamic Visual Acuity in Baseball Players Is Due to Superior Tracking Abilities. Medicine & Science in Sports & Exercise, 45(2), 319-325.
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