Our team specializes in real-time computer assisted monitoring of electroencephalograms (EEGs) in the intensive care unit (ICU). In previous work, we have demonstrated a clear and urgent market for such technology, and we have created a proof-of-concept solution using state-of-the-art machine learning tools. We have also developed a community of stakeholders, partners, and collaborators to aid us in bringing our tools to market. We seek to further prepare our technology for market by (a) adapting our existing offline tools into a real-time application, and (b) further reducing our false alarm rates. We continue to engage with our various partners in order to strengthen our commercialization and marketing strategy.
We use cutting edge deep learning software trained on the world's most comprehensive EEG data archive. The result is a software tool that can detect seizures in the ICU at a level of performance similar to that of trained neurologists. Critically, we can detect seizures with a sensitivity of 40.29% with 5.77 false alarms per 24 hours. We know from our extensive market research that this level of performance is reasonably close to the performance required for clinical acceptance.
The primary mechanism for distribution of EEG software is through companies that produce EEG hardware systems for critical-care environments and bundle their software tools with hardware sales. The secondary distribution strategy is through software producers of healthcare information systems. EEG software companies that target end users in the ICU environment will benefit from a more robust and reliable solution for automatic event detection. Our broad market is real-time data analytics for neuro-monitoring within high and mid acuity settings. High-acuity monitoring is used for critical care in ICU’s, operating rooms and high dependency units. Mid-acuity monitoring is used for patients requiring high level of medical attention in emergency, recovery, and post-operative care rooms.