title: A feasibility study of an improved procedure for using EEG to detect brain responses to imagery instruction in patients with disorders of consciousness.
abstract: One of the major concerns of recent studies is the correct discrimination between vegetative and minimally conscious state as the distinction between these two conditions has major implications for subsequent patient rehabilitation. In particular, it would be advantageous to establish communication with these patients. This work describes a procedure using EEG to detect brain responses to imagery instruction in patients with disorders of consciousness. Five healthy subjects and five patients with different disorders of consciousness took part in the study. A support vector machine classifier applied to EEG data was used to distinguish two mental tasks (Imagery Trial) and to detect answers to simple yes or no questions (pre-Communication Trial). The proposed procedure uses feature selection based on a nested-leave-one-out algorithm to reduce the number of electrodes required. We obtained a mean classification accuracy of 82.0% (SD 5.1%) for healthy subjects and 84.6% (SD 9.1%) for patients in the Imagery Trial, and a mean classification accuracy of 80.7% (SD 11.5%) for healthy subjects and 91.7% (SD 7.4%) for patients in the pre-Communication Trial. The subset of electrodes selected was subject and session dependent.
authors.affiliation: Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, Cesena, Italy.
authors.forename: Anna Lisa
authors.initials: AL
authors.lastname: Mangia
authors.affiliation: Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, Cesena, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Pirini
authors.affiliation: Rehabilitation Unit, Maggiore Hospital, Bologna, Italy.
authors.forename: Laura
authors.initials: L
authors.lastname: Simoncini
authors.affiliation: Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, Cesena, Italy.
authors.forename: Angelo
authors.initials: A
authors.lastname: Cappello
mesh_terms: D000328:Adult; D000465:Algorithms; D000704:Analysis of Variance; D001921:Brain / Q000503:physiopathology*; D016022:Case-Control Studies; D003142:Communication; D003243:Consciousness / Q000502:physiology*; D003244:Consciousness Disorders / Q000503:physiopathology*; D003710:Demography; D004566:Electrodes; D004569:Electroencephalography; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D019018:Imagery, Psychotherapy; D008297:Male