237 SeeMe: An Automated Methodology to Detect Early Signs of Recovery After Acute Brain Injury

Abstract

INTRODUCTION: Assessing the functional state of the brain and predicting recovery after acute brain injury (ABI) remains a major unsolved problem. At present, physicians make predictions using clinical examination, traditional scoring systems, and statistical models, which have significant shortcomings and lack the ability to forecast recovery on an individual basis. METHODS: SeeMe is based on analyzing subtle facial expressions in response to auditory commands (i.e., “open your eyes,” “make a smile”) over time and compares the results to a pre-stimulus baseline. These subtle motions are often not detectable by the naked eye. We enrolled 26 comatose ABI patients and 16 healthy volunteers to test this tool. Command-evoked eye-opening movements were compared to clinical observation and the JFK Coma Recovery Scale-Revised (CRS-R). RESULTS: In our study, 22 of 26 (85%) patients recovered consciousness during hospitalization after ABI. On average, SeeMe detected command-evoked eye opening ∼9 days before clinical assessment using the CRS-R and ∼3 days before blinded human raters who observed the recorded videos using the naked eye.Using the optimally identified decision threshold, SeeMe demonstrated the following performance metrics on ABI patients with no eye opening to command (auditory CRS subscale = 2): sensitivity = 74.1%, specificity = 66.6%, positive predictive value = 16.8%, and negative predictive value = 96.6%. CONCLUSIONS: These findings demonstrate the high predictive performance of SeeMe in assessing consciousness in ABI patients and provide a quantitative tool for studying neural circuits and developing novel therapeutic approaches. SeeMe's ability to detect low-amplitude motor movements opens new avenues for understanding and facilitating recovery of consciousness in patients with ABI.