The team at Brain Scientific has made it our mission to build a complete Neurology EEG EcoSystem, offering two distinct devices to streamline your EEG prep, testing, and diagnosis. NeuroCap™ our disposable headset with 22 pre-gelled electrodes follows the international 10–20 system, and our hand-held, wireless, 21-channel NeuroEEG™ amplifier provides confidence to clinicians and patients when testing to detect abnormalities in brain waves, or in the electrical activity of the brain to diagnose neurological disorders. 

NeuroCap™ provides numerous benefits to clinicians and patients. Any healthcare worker can prep and apply NeuroCap™ in just 5-minutes, no longer requiring you to wait for your tech-on-call, all the while shortening the time to reading test results, evaluating, and diagnosing your patient. NeuroCap™ is compatible with 3rd party amplifiers when using our universal cable with the touch-proof DIN connectors.  

As our healthcare providers focus on enabling and utilizing telehealth to diagnose and treat patients, NeuroCap™ enables tele-neurology allowing clinicians to make rapid decisions remotely and bridging the gap in access to neurological care. Using NeuroCap™ can accelerate the time to diagnosis, eliminate the need for your patients to travel distances to testing site facilities, and provide a timely and accurate diagnosis in an efficient manner. 

NeuroEEG™ is our 21-channel amplifier that provides clinicians the same quality as traditional EEG equipment. The portability and wireless connectivity offer you the ability to test anywhere in your hospital, office, remote setting, or ambulance to quickly serve your patients. 

NeuroHub™ is a state-of-art Neurology SaaS platform used to collect and aggregate data from current and future BRSF devices like the NeuroCap™, NeuroEEG™, and external sources such as research and medical data banks, 3rd-party devices, and clinical-use applications. NeuroHub™ will allow comprehensive monitoring and facilitate collaborative diagnosis, analysis, research, treatment, and prevention by employing sophisticated Artificial Intelligence (AI) and machine learning (ML) algorithms utilizing historical and current patient, device, and platform data.