Discovering Oculometric Patterns to Detect Cognitive Performance Changes in Healthy Youth Football Athletes

  • Gaurav N. PradhanEmail author
  • Jamie M. Bogle
  • Michael J. Cevette
  • Jan Stepanek
Research Article


In this paper, we focus on the application of oculometric patterns extracted from raw eye movements during a mental workload task to assess changes in cognitive performance in healthy youth athletes over the course of a typical sport season. Oculometric features pertaining to fixations and saccades were measured on 116 athletes in pre- and post-season testing. Participants were between 7 and 14 years of age at pre-season testing. Due to varied developmental rates, there were large interindividual performance differences during a mental workload task consisting of reading numbers. Based on different reading speeds, we classified three profiles (slow, moderate, and fast) and established their corresponding baselines for oculometric data. Within each profile, we describe changes in oculomotor function based on changes in cognitive performance during the season. To visualize these changes in multidimensional oculometric data, we also present a multidimensional visualization tool named DiViTo (diagnostic visualization tool). These experimental, computational informatics and visualization methodologies may serve to utilize oculometric information to detect changes in cognitive performance due to mild or severe cognitive impairment such as concussion/mild traumatic brain injury, as well as possibly other disorders such as attention deficit hyperactivity disorders, learning/reading disabilities, impairment of alertness, and neurocognitive function.


Cognitive performance Oculometrics Concussion Eye tracking Multidimensional patterns Pre- and post-season 



We acknowledge Dr. Samantha Kleindienst, Dr. David Dodick, Dr. Jennifer Wethe, Dr. Amaal Starling, and the entire Youth Athlete Study Team for facilitating and coordinating the data collection sessions.

Compliance with Ethical Standards

Conflict of Interest

One or more of the investigators associated with this project and Mayo Clinic have a financial interest related to this research.


  1. 1.
    Stepanek J, Cocco D, Pradhan GN, Smith BE, Bartlett J, Studer M, Kuhn F, Cevette MJ (2013) Early detection of hypoxia-induced cognitive impairment using the King-Devick test. Aviat Sp Environ Med 84(10):1017–1022CrossRefGoogle Scholar
  2. 2.
    Fischer TD, Red SD, Chuang AZ, Jones EB, McCarthy JJ, Patel SS, Sereno AB (2016) Detection of subtle cognitive changes after mTBI using a novel tablet-based task. J Neurotrauma 33(13):1237–1246CrossRefGoogle Scholar
  3. 3.
    Cifu DX, Wares JR, Hoke KW, Wetzel PA, Gitchel G, Carne W (2015) Differential eye movements in mild traumatic brain injury versus normal controls. J Head Trauma Rehabil 30(1):21–28CrossRefGoogle Scholar
  4. 4.
    Sussman ES, Ho AL, Pendharkar AV, Ghajar J (2016) Clinical evaluation of concussion: the evolving role of oculomotor assessments. Neurosurg Focus 40(4):E7CrossRefGoogle Scholar
  5. 5.
    Pradhan GN, Bogle J, Kleindienst S, Cevette MJ, and Stepanek J (2017) “Correlating multi-dimensional oculometrics with cognitive performance in healthy youth athletes,” J Healthc Informatics Res, pp. 1–20Google Scholar
  6. 6.
    Risen S, Reesman J, Yenokyan G, Slomine B, Suskauer S (2017) The course of concussion recovery in children 6-12 years of age: experience from an interdisciplinary rehabilitation clinic. PM R 9(9):874–883CrossRefGoogle Scholar
  7. 7.
    Baillargeon A, Lassonde M, Leclerc S, Ellemberg D (2012) Neuropsychological and neurophysiological assessment of sport concussion in children, adolescents and adults. J Brain Inj 26(3):211–220CrossRefGoogle Scholar
  8. 8.
    Davis G et al (2017) What is the difference in concussion management in children as compared to adults? A systemic review. Br J Sports Med 51(12):949–957CrossRefGoogle Scholar
  9. 9.
    Stamm J et al (2015) Age of first exposure to football and later-life cognitive impairment in former NFL players. Neurology 84(11):1114–1120CrossRefGoogle Scholar
  10. 10.
    Russell K, Hutchison M, Selci E, Leiter J, Chateau D, Ellis M (2016) Academic outcomes in high-school students after a concussion: a retrospective population-based analysis. PLoS One 11(10):e0165116CrossRefGoogle Scholar
  11. 11.
    Alexander D, Shuttleworth-Edwards A, Kidd M, Malcolm C (2015) Mild traumatic brain injuries in early adolescent rugby players: long-term neurocognitive and academic outcomes. Brain Inj 29(9):1113–1125CrossRefGoogle Scholar
  12. 12.
    Galetta KM, Brandes LE, Maki K, Dziemianowicz MS, Laudano E, Allen M, Lawler K, Sennett B, Wiebe D, Devick S, Messner LV, Galetta SL, Balcer LJ (Oct. 2011) The King-Devick test and sports-related concussion: study of a rapid visual screening tool in a collegiate cohort. J Neurol Sci 309(1–2):34–39CrossRefGoogle Scholar
  13. 13.
    Oberlander TJ, Olson BL, Weidauer L (2017) Test-retest reliability of the King-Devick test in an adolescent population. J Athl Train 52(5):439–445CrossRefGoogle Scholar
  14. 14.
    Alsalaheen BA, Haines J, Yorke A, Diebold J (2016) King-Devick test reference values and association with balance measures in high school American football players. Scand J Med Sci Sports 26(2):235–239CrossRefGoogle Scholar
  15. 15.
    Lloyd SP (1982) Least squares quantization in PCM. IEEE Trans Inf Theory 28(2):129–137MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Arthur D and Vassilvitskii S (2007) “k-means++: the advantages of careful seeding,” in In Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms (SODA ‘07),, pp. 1027–1035Google Scholar
  17. 17.
    Davies D, Bouldin DL (1979) A cluster separation measure. IEEE Trans Pattern Anal Mach Intell PAMI-1(2):224–227CrossRefGoogle Scholar
  18. 18.
    Maruta J, Ghajar J (2014) Detecting eye movement abnormalities from concussion. Concussion 28:226–233Google Scholar
  19. 19.
    Weise KK, Swanson MW, Penix K, Hale MH, Ferguson D (2016) King-Devick and pre-season visual function in adolescent athletes. Optom Vis Sci 93:00–00Google Scholar
  20. 20.
    Stepanek J, Pradhan GN, Cocco D, Smith BE, Bartlett J, Studer M, Kuhn F, Cevette MJ (2014) Acute hypoxic hypoxia and isocapnic hypoxia effects on oculometric features. Aviat. Sp. Environ. Med. 85(7):700–707CrossRefGoogle Scholar
  21. 21.
    Munce TA, Dorman JC, Odney TO, Thompson PA, Valentine VD, Bergeron MF (2014) Effects of youth football on selected clinical measures of neurologic function: a pilot study. J Child Neurol 29(12):1601–1607CrossRefGoogle Scholar
  22. 22.
    King D, Hume P, Gissane C, Clark T (2015) Use of the King-Devick test for sideline concussion screening in junior rugby league. J Neurol Sci 357(1–2):75–79CrossRefGoogle Scholar
  23. 23.
    Rizzo J-R et al. (2016) “Rapid number naming in chronic concussion: eye movements in the King-Devick test,” Ann Clin Transl Neurol, pp. 1–11Google Scholar
  24. 24.
    Rizzo JR, Hudson TE, Dai W, Desai N, Yousefi A, Palsana D, Selesnick I, Balcer LJ, Galetta SL, Rucker JC (2016) Objectifying eye movements during rapid number naming: methodology for assessment of normative data for the King-Devick test. J Neurol Sci 362:232–239CrossRefGoogle Scholar
  25. 25.
    Mcdevitt J, Appiah-Kubi KO, Tierney R, Wright WG (2016) Vestibular and oculomotor assessments may increase accuracy of subacute concussion assessment. Int J Sports Med 37(9):738–747CrossRefGoogle Scholar
  26. 26.
    Mucha A, Collins MW, Elbin RJ, Furman JM, Troutman-Enseki C, DeWolf RM, Marchetti G, Kontos AP (2014) A brief vestibular/ocular motor screening (VOMS) assessment to evaluate concussions: preliminary findings. Am J Sports Med 42(10):2479–2486CrossRefGoogle Scholar
  27. 27.
    Murray NG, Ambati VNP, Contreras MM, Salvatore AP, Reed-Jones RJ (2014) Assessment of oculomotor control and balance post-concussion: a preliminary study for a novel approach to concussion management. Brain Inj 28(4):496–503CrossRefGoogle Scholar
  28. 28.
    Fukushima J, Hatta T, Fukushima K (2000) Development of voluntary control of saccadic eye movements. I. Age-related changes in normal children. Brain and Development 22(3):173–180CrossRefGoogle Scholar
  29. 29.
    Salman MS, Sharpe JA, Eizenman M, Lillakas L, Westall C, To T, Dennis M, Steinbach MJ (2006) Saccades in children. Vis Res 46(8–9):1432–1439CrossRefGoogle Scholar
  30. 30.
    Munoz D, Broughton J, Goldring J, Armstrong I (1998) Age-related performance of human subjects on saccadic eye movement tasks. Exp Brain Res 121(4):391–400CrossRefGoogle Scholar
  31. 31.
    Suh M, Basu S, Kolster R, Sarkar R, McCandliss B, Ghajar J (2006) Increased oculomotor deficits during target blanking as an indicator of mild traumatic brain injury. Neurosci Lett 410(3):203–207CrossRefGoogle Scholar
  32. 32.
    Lin TP, Adler CH, Hentz JG, Balcer LJ, Galetta SL, Devick S (2014) Slowing of number naming speed by King-Devick test in Parkinson’s disease. Parkinsonism Relat Disord 20(2):226–229CrossRefGoogle Scholar
  33. 33.
    Benedict PA, Baner NV, Harrold GK, Moehringer N, Hasanaj L, Serrano LP, Sproul M, Pagnotta G, Cardone DA, Flanagan SR, Rucker J, Galetta SL, Balcer LJ (2015) Gender and age predict outcomes of cognitive, balance and vision testing in a multidisciplinary concussion center. J Neurol Sci 353(1–2):111–115CrossRefGoogle Scholar
  34. 34.
    Luna B, Velanova K, Geier CF (2008) Development of eye-movement control. Brain Cogn 68(3):293–308CrossRefGoogle Scholar
  35. 35.
    Galetta KM, Morganroth J, Moehringer N, Mueller B, Hasanaj L, Webb N, Civitano C, Cardone DA, Silverio A, Galetta SL, Balcer LJ (2015) Adding vision to concussion testing: a prospective study of sideline testing in youth and collegiate athletes. J Neuroophthalmol 35(3):235–241CrossRefGoogle Scholar
  36. 36.
    Fu H, Wei Y, Camastra F, Arico P, Sheng H (2016) Advances in eye tracking technology : theory , algorithms , and applications. Comput Intell Neurosci 2016:2–4Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Aerospace Medicine and Vestibular Research LaboratoryMayo Clinic ArizonaScottsdaleUSA

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