Disorders of Consciousness: using the Perturbational Complexity Index to distinguish between voluntary and involuntary movements.

The debate behind the word "consciousness" has been vivid for centuries among ethicists, philosophers and neurologists. Distinguishing between different Disorders of Consciousness (DOCs) in after-coma patients, in particular, is still difficult, and the diagnosis is based on scales whose assignement may be subjective and thus mistaken. Finding an accurate mathematical way to interpret a patient's movements and understand if they are completely voluntary or just involuntary reflexes may be a more objective way to classify their level of consciousness. This thesis work proposes to find a way to distinguish among voluntary and involuntary movements in healthy subjects by analysing the Event Related Potentials (ERPs) behaviour obtained from EEG recordings. For each subject and experiment, after recording the EEG signals while performing the movements, the ERPs were extracted and a measure of the Integrated Information Theory firstly proposed by Giulio Tononi, called Perturbational Complexity Index (PCI), was calculated on the basis of the state transitions before and after the on-set of the movement. Finally, the obtained values were used to validate different classifiers, for which significant results were reached.