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Real-time Strategies in Brain Computer Interfaces when Driven by Purely Visual Imagery Signals.
Rel. Francesco Paolo Andriulli, Davide Consoli, Paolo Ricci, Arturo Micheli. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2022
Abstract
Brain-computer interfaces (BCIs), when used for medical application, allow patients suffering from severely debilitating diseases to improve their life quality. A BCI translates brain signals in commands that can be used by the patient to drive several instruments, without the need of an electromyography (EMG) that is instead necessary in applications like myoelectric prosthesis. In fact, the BCI approach grants the possibility to interact with the external environment also to patients suffering from severe neuromuscular diseases, such as locked-in syndrome or advanced stages of multiple sclerosis. Currently, the most widespread technique used to monitor the brain signals in a BCI pipeline is electroencephalography (EEG), where a set of electrodes placed on the subject’s head measures the potential differences related to neural activity.
The EEG driven BCIs can be categorized depending on the kind of signals used that they try to detect and classify
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