Disorders of consciousness (DOC) are among the major challenges of contemporary medicine, mostly due to the high rates of misdiagnoses in clinical assessment, based on behavioral scales. This turns our attention to potentially objective neuroimaging methods. Paradigms based on electroencephalography (EEG) are most suited for bedside applications, but sensitive to artifacts. These problems are especially pronounced in pediatric patients.
We present the first study on the assessment of pediatric DOC patients by means of command-following procedures and involving long-latency cognitive event-related potentials. To deal with the above mentioned challenges, we construct a specialized signal processing scheme including artifact correction and rejection, parametrization, classification and final assessment of the statistical significance. To compensate for the possible bias of the tests involved in the final diagnosis, we propose the Monte Carlo evaluation of the processing pipeline. To compensate for possible sensory impairments of DOC patients, for each subject we check command-following responses to the stimuli in the major modalities: visual, tactile, and audio (words and sounds).
We test the scheme on 20 healthy volunteers and present results for 15 patients from a hospital for children with severe brain damage, in relation to their behavioral diagnosis on the Coma Recovery Scale-Revised (CRS-R).
