Objective: The goal of this study was to validate an EEG based multimodal index to aid in the assessment of concussion at time of injury, severity of concussion, and aid in evaluating readiness to return to play/activity.

Background:  The absence of a gold standard for diagnosis of concussion results in reliance on subjective self-report of symptoms. EEG has been demonstrated to be sensitive to changes in brain function following head injury, especially in connectivity. Using machine learning with inputs primarily from EEG measures, and including multimodal inputs, an objective marker of the likelihood of concussion (Concussion Index, CI) was derived. 

Methods:  Male and female concussed athletes and controls ages of 13-25yr, represented a convenience sample (n=580), enrolled from US High School, Colleges, and Concussion Clinics.  Concussed subjects had a witnessed head impact and were removed from play by site guidelines.  Assessments were performed within 72 hours of injury, at clinically determined return to play (RTP), 45 days following RTP, and included EEG (frontal and frontotemporal regions), neurocognitive performance, and standard concussion assessments.

Results:  Sensitivity = 85.99%, Specificity = 70.78%, NPV = 90.10% and PPV = 62.02, were obtained. Results demonstrated significance: 1) between CI at injury compared to RTP (p<0.0001); 2) between CI in patients with rapid (<14 days) compared with those with prolonged recovery (≥14 days), (p=0.0038); 3) stability over time in controls (p<0.0001); and 4) between CI and total symptom burden (correlation coefficient 0.8031, p<0.0001).

Conclusions: This study independently validated a multimodal, EEG-based, objective index of concussion (CI).  The neurotechnology platform incorporating this capability is handheld, rapid to use, and lends itself to incorporation into the standard assessment of concussion to aid in clinical diagnosis and assessment of readiness to RTP. This data supported the FDA clearance for the Concussion Index (embedded in the BrainScope medical device).