“Development of a Point of Care System for Automated Coma Prognosis”
Data will be collected from 50 participants in coma. Electroencephalogram/event-related potentials (EEG/ERP) data will be recorded for 24 consecutive hours at a maximum of 5 time-points spanning 30 days from the date of recruitment to track participants' clinical state. In the case of patient emergence (clinically diagnosed using the GCS), data are recorded to form an additional basis for assessment. An additional dataset from 20 healthy controls will be collected, each spanning a 15-hour recording period in order to formulate a baseline. Collected data are to form the basis for automatic analysis and detection of ERP components in coma. Salient features (i.e., biomarkers) extracted from the ERPs and resting-state EEG will be identified and combined in an optimal fashion to give an accurate indicator of prognosis.
Methods have not been listed for this study. If you require more information about the methods of this study, please inquire with the researcher.
Development of a Point of Care System for Automated Coma Prognosis - A Prospective Cohort Study