SeeMe: An Automated Tool to Detect Early Recovery After Brain Injury

Early prediction of outcomes after acute brain injury (ABI) remains a major unsolved problem. Presently, physicians make predictions using clinical examination, traditional scoring systems, and statistical models. In this study, we will use a novel technique, "SeeMe," to objectively assess the level of consciousness in patients suffering from comas following ABI. SeeMe is a program that quantifies total facial motion over time and compares the response after a spoken command (i.e. "open your eyes") to a pre-stimulus baseline.

Acute brain injury (ABI) recovers at a variable rate. While some progress has been made in predicting long-term outcomes in traumatic brain injury (TBI) and intracranial hemorrhage, there is a critical need for short-term prediction of outcomes, in the first days and weeks after injury. With advances in machine learning and artificial intelligence, there is a growing interest in facial analysis and its application in neurological and psychiatric disorders. Here we describe "SeeMe," a novel automated objective measure of consciousness based on microexpression analyses in response to auditory commands. In measuring the smallest muscular movements undetectable by clinical observation, this technique has the high spatial resolution needed to detect hidden signs of recovery and the high temporal resolution needed to study neural circuits.