Despite the growing evidence of its impact on positive patient outcomes, the use of continuous EEG (cEEG) in the ICU is still often limited to academic centers and teaching hospitals because of a lack of qualified personnel to read EEGs. In response to this market need, we have developed AutoEEG - a high performance automatic seizure detection system. AutoEEG provides a similar level of performance in detecting seizures in cEEGs as trained neurologists at teaching hospitals. In this NSF-funded Parternships for Innovation (PFI-TT) project, we are advancing this technology in two ways:

  • adapting our existing offline tools into a real-time application,
  • further reducing the false alarm rate so that performance is clinically acceptable.


The positive impact of cEEG monitoring has resulted in the Critical Care Continuous EEG Task Force of the American Clinical Neurophysiology Society recommending its use. Our integration of real-time seizure detection technology into an industry-leading EEG hardware system will allow clinical evaluation of this technology. AutoEEG will improve outcomes for intensive care patients suffering from neural insult while simultaneously reducing the cost of care. It will allow neurologists to more precisely apply medications to their patients. The real-time alerting capabilities of AutoEEG allows neurologists to provide more responsive and effective critical care.