Andrea Bonomi
Role of spatial filtering in the pre-processing chain of a BCI for non-responsive patients.
Rel. Gabriella Olmo, Vito De Feo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2022
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (24MB) | Preview |
Abstract
Brain injuries represent a relevant current public health problem. Often, they lead to periods of unconsciousness, coma, or even death. Generally, individuals who exit from a period of coma survive in a non-responsive state, unable to voluntarily respond to external stimuli. For these nonresponsive patients, even though they accomplish movements, it is not trivial to establish and associate them with a level of consciousness, in order to interpret their intentions. This obstacle may easily conduct to misleading diagnoses. In order to obtain a more reliable diagnosis, it is essential to establish and develop methods able to enhance studies of various levels of consciousness in nonresponsive patients.
In this thesis an innovative brain-computer interface (BCI) is presented, having the goal to analyze electroencephalographic (EEG) and electromyographic (EMG) signals, recorded from healthy individuals, to extract meaningful information about the intention to move while performing or imagining to perform motor tasks and to compare them with the ones retrieved from nonresponsive patients
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
