{"doi":"10.3389/fneur.2022.1039955","title":"Eye tracking for classification of concussion in adults and pediatrics","abstract":"Introduction: In order to obtain FDA Marketing Authorization for aid in the diagnosis of concussion, an eye tracking study in an intended use population was conducted. Methods: Potentially concussed subjects recruited in emergency department and concussion clinic settings prospectively underwent eye tracking and a subset of the Sport Concussion Assessment Tool 3 at 6 sites. The results of an eye tracking-based classifier model were then validated against a pre-specified algorithm with a cutoff for concussed vs. non-concussed. The sensitivity and specificity of eye tracking were calculated after plotting of the receiver operating characteristic curve and calculation of the AUC (area under curve). Results: = 282) was 31.6%. Conclusion: A pre-specified algorithm and cutoff for diagnosis of concussion vs. non-concussion has a sensitivity and specificity that is useful as a baseline-free aid in diagnosis of concussion. Eye tracking has potential to serve as an objective \"gold-standard\" for detection of neurophysiologic disruption due to brain injury.","journal":"Frontiers in Neurology","year":2022,"id":260476,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":16,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.946,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":721734,"name":"Robert J. Spinner","orcid":"0000-0003-0443-7763","position":1,"is_corresponding":false},{"id":914708,"name":"Gerard Dynkowski","orcid":null,"position":2,"is_corresponding":false},{"id":914709,"name":"Susan Kirelik","orcid":null,"position":3,"is_corresponding":false},{"id":494799,"name":"Tory Schaaf","orcid":null,"position":4,"is_corresponding":false},{"id":691221,"name":"Stephen P. Wall","orcid":"0000-0003-3965-5074","position":5,"is_corresponding":false},{"id":914185,"name":"Paul P. Huang","orcid":"0000-0003-0563-921X","position":6,"is_corresponding":false},{"id":914184,"name":"Uzma Samadani","orcid":"0000-0003-2566-5909","position":0,"is_corresponding":true}],"reference_count":22,"raw_metadata":null,"created_at":"2026-07-19T00:26:07.666421Z","pmid":"36530640","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}