Stony Brook University

04/10/2026 | Press release | Distributed by Public on 04/10/2026 10:52

Advancing Technology to Detect Consciousness and Promote Recovery in Patients With Brain Injury

Neurosciences team to receive $2.5 million in NIH funding to develop and validate "SeeMe"

STONY BROOK, NY, April 10, 2026 - A team of researchers at Stony Brook University led by Sima Mofakham, PhD, has received a grant from the National Institutes of Health's National Institute of Mental Health (NIMH) to develop a brain-behavior synchronization system called "SeeMe" that uses electrophysiological signals, computer vision and artificial intelligence (AI) technology in brain injury patients to detect early signs of consciousness and promote recovery.

Thousands of brain-injured patients are labeled as "unresponsive" in hospitals every year. Neuroscientists believe that perhaps as many as one-quarter of these patients may be conscious but not able to show it.

"It's this disconnect, called cognitive motor dissociation, that we are hoping to solve with SeeMe," says Dr. Mofakham, Lead Principal Investigator, Associate Professor and Vice Chair of Research for the Department of Neurosurgery in the Renaissance School of Medicine (RSOM), and affiliated Associate Professor in the Department of Electrical and Computer Engineering at Stony Brook University.

"Cognitive motor dissociation is one of the most urgent diagnostic blind spots in neurology and critical care," adds Co-Principal Investigator Chuck Mikell, MD, Clinical Associate Professor and Vice Chair for the Department of Neurosurgery.

This depiction of the SeeMe system with a model TBI patient illustrates how phase one work centers on using computer vision and hand sensors to detect consciousness. Phase two work would focus on electronically stimulating the vagus nerve to enhance movement.
Credit: Sima Mofakham

Current clinical assessments of consciousness rely largely on bedside examination, which can miss subtle and inconsistent signs of command following. SeeMe is designed to improve on that by first providing an automated, objective, and sensitive way to detect those signals. Then, by using that information, clinicians may be able to support a treatment strategy aimed at promoting recovery.

According to Dr. Mofakham, first the researchers will further develop and validate SeeMe as a monitoring tool that uses computer vision, hand sensors, and brain activity recordings to identify subtle responses to spoken commands. In the second phase of the research, the team will use that same platform to guide treatment and test whether SeeMe can detect emerging voluntary behavior in real time and use it to time vagus nerve stimulation in a way that may help strengthen movement and recovery.

They will test SeeMe in 80 traumatic brain injury (TBI) patients to validate the system. After that, they will use SeeMe to design a closed-loop simulation system to facilitate the recovery of consciousness.

The newly awarded NIMH grant (R61MH138612), effective this month, will provide more than $2.5 million over five years to support research evaluating SeeMe through April 2031. The funding will be across two phases, R61 and R33. Funding for the R33 phase is contingent on successful completion of the R61 milestones.

The project includes a third Co-Principal Investigator, Petar M. Djurić, PhD, Distinguished Professor in the Department of Electrical and Computer Engineering at Stony Brook University.

Previous research highlighting SeeMe as a breakthrough technology was published in Nature Communications Medicine in 2025. For more details on that work, see this press release.

Stony Brook University published this content on April 10, 2026, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on April 10, 2026 at 16:52 UTC. If you believe the information included in the content is inaccurate or outdated and requires editing or removal, please contact us at [email protected]