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Evaluation of the HS-1000 acoustic neuromonitoring device in the diagnosis and assessment of sports-induced concussion
  1. Allen Sills1,2,
  2. Timothy Lee1,
  3. Tricia Kwiatkowski3,
  4. Thomas Swanson3,
  5. Guy Weinberg3
  1. 1Vanderbilt Sports Concussion Centre
  2. 2Department of Neurological Surgery, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
  3. 3HeadSense Medical Inc., Cleveland, OH, USA


Objective To evaluate the correlation between data collected from the HS-1000 multi-modality brain monitoring device and standard neurological, psychomotor, and neuropsychological diagnostics in the assessment of acute sports-induced concussion.

Design Prospective, open-label, non-randomised study.

Setting Collegiate athletes were recruited at the Vanderbilt Sports Concussion Centre, Nashville, TN.

Participants Sixty-four subjects across concussed (n1=14) and healthy control (n2=50) arms were consented.

Interventions and assessment of risk factors Eligible subjects suffering recent concussion and age/gender-matched healthy controls were enrolled into the study. Participants in both groups were monitored for at least 15min per recording with the HS-1000. Concussed subjects were recorded 4 times relative to time of concussion injury: acute/baseline, 48 hr, 1 wk, 1 mo. Healthy control subjects were recorded at 2 time points: baseline, 2 wk.

Outcome measures Standard clinical diagnostics and demographic information were collected from all study participants. As per current clinical standards and their assigned group, concussed subjects received Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT), Modified Balance Assessment Scale (mBESS), and total clinical symptom index scores. MathWorks MATLAB™ (Matrix Laboratory) engineering software was used to interpret signals and calculate sensitivity-specificity as a function of predictive accuracy with clinically confirmed concussion status.

Main results Post-processing of HS-1000 signals identified concussed athletes with a sensitivity-specificity of 86.1% and 91%, respectively.

Conclusions The HS-1000 demonstrated strong predictive accuracy compared with clinical diagnosis. Improved statistical power through greater sampling sizes and the development of a real-time diagnostic algorithm suggests this technology holds promise in the assessment and diagnosis of sports-induced concussion.

Competing interests None.

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