Concussion, also referred as mild traumatic brain injury is one of the most common occurrences in high impact games like football, ice hockey, rugby as well as other fast spaced sports. According to the CDC, between 2001 and 2009, an estimated 173,285 people under age 19 were treated in hospital emergency rooms for concussion related to sports and recreation activities. Some common signs of concussion are temporary  disorientation,  confusion,  dizziness,  nausea,  and  headache,  with  or  without  loss  of consciousness,  memory  or  structural  damage.  Concussion  assessment  is  a  challenge  and  no  single approach  appears  sufficient  for  a  sensitive  and  specific concussion  assessment.  We  hypothesize  that combined  evaluation  of  multiple  modalities  including  EEG  recordings,  neuropsychological/motor assessment scores, and impact sensor readings can provide a set of characteristic “signatures” that will collectively better determine not only injury severity and recovery timeline projections but also permit effective and objective ‘Return to play’ decisions. Our main objective is to collect pre, mid, and end of season baseline as well as multiple time point post-concussion  neuropsychological/motor, impact, and EEG  data  from  members  of  a  Grand  Forks  area  high  school  football  team  to  define  the  relationship between the concussed and non-concussed athlete performances over time. This data is directly compared to the team-based, athletic trainer derived assessments.

I. Cardio-Postural analysis

At present we are focusing on postural analysis. Postural analysis mainly records a demographic profile and health history as a baseline, then considers current concussion symptoms, followed by a series of neurocognitive tests that assess verbal memory, visual memory, processing speed, and reaction time. Test scores can be compared to previous tests and are used to determine concussion influence and readiness to return to sport.

The tools we are using for assessment are the King Devick Test and the BESS (Balance Error Scoring System). King-Devick Test (K-D Test) is a two-minute test that requires an athlete to read single digit numbers displayed on a paper. King-Devick Test Screens For:

  1. Eye movements
  2. Attention
  3. Concentration
  4. Speech/Language

The BESS consists of 6 tests lasting 20 seconds each, performed on a firm surface (grass, turf, court) and a piece of medium-density foam, all with the eyes closed, and scored based on the number of errors across trials. These are:

  1. Double leg stance
  2. Single-leg stance using the non-dominant foot
  3. Tandem stance

Figure shows the data collection system including sample data for BESS test analysis. A Wii Balance Board is being used as the testing surface to take objective data points in addition to the BESS test’s subjective error observations.

II. EEG analysis:

Diagnosis and clinical management of concussion is one of the greatest challenges for clinicians. A reliable assessment for concussion and recovery does not yet exist since conventional tools are designed to evaluate a subject’s ability to perform simple tasks or his/her answers to questions that reflect attitude and/or subjective judgment. Although several neuropsychological and motor assessments have been developed and implemented for sports teams of various levels and ages, the sensitivity of these tests is yet to be validated with more objective measures in order to make return-to-play (RTP) decisions more confidently. Existing evidence indicates that electroencephalogram (EEG) recordings detect abnormal brain activities in asymptomatic concussed athletes, demonstrating superior sensitivity over neuropsychological assessments.

In this study, for the EEG assessment, we are using a 9-lead wireless EEG headset and B-Alert System to record EEG during a series of cognitive tasks in the form of event-related potentials (ERP). This noninvasive EEG headset delivers high quality EEG signals in a portable design. The elimination of all wires ensures mobility during recordings, while also avoiding the artifacts and noise typically associated with the wires of traditional EEG systems. Figure shows the EEG data collection using B alert system.Our study mainly focus on the power spectral analysis of these data at frequency bands delta (2- 4Hz), theta (4-8Hz), alpha (8-13Hz), beta (13-30Hz), gamma (30-40Hz).

Leave a Reply

Your email address will not be published. Required fields are marked *