Diagnostic accuracy of tablet-based software for the detection of concussion

Suosuo Yang, Benjamin Flores, Rotem Magal, Kyrsti Harris, Jonathan Gross, Amy Ewbank, Sasha Davenport, Pablo Ormachea, Waleed Nasser, Weidong Le, W. Frank Peacock, Yael Katz, David M. Eagleman

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Despite the high prevalence of traumatic brain injuries (TBI), there are few rapid and straightforward tests to improve its assessment. To this end, we developed a tablet-based software battery ("BrainCheck") for concussion detection that is well suited to sports, emergency department, and clinical settings. This article is a study of the diagnostic accuracy of BrainCheck. We administered BrainCheck to 30 TBI patients and 30 pain-matched controls at a hospital Emergency Department (ED), and 538 healthy individuals at 10 control test sites. We compared the results of the tablet-based assessment against physician diagnoses derived from brain scans, clinical examination, and the SCAT3 test, a traditional measure of TBI. We found consistent distributions of normative data and high test-retest reliability. Based on these assessments, we defined a composite score that distinguishes TBI from non-TBI individuals with high sensitivity (83%) and specificity (87%). We conclude that our testing application provides a rapid, portable testing method for TBI.

Original languageEnglish (US)
Article numbere0179352
JournalPLoS ONE
Issue number7
StatePublished - Jul 2017

ASJC Scopus subject areas

  • General


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