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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-01212019-170153


Tipo di tesi
Tesi di laurea magistrale
Autore
CIGNONI, ARIANNA
URN
etd-01212019-170153
Titolo
Drowsiness detection for surgeons: design of a wearable integrated EEG system
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA BIOMEDICA
Relatori
relatore Ciuti, Gastone
Parole chiave
  • artificial neural network
  • drowsiness
  • sleep deprivation
  • wearable eeg
Data inizio appello
15/02/2019
Consultabilità
Non consultabile
Data di rilascio
15/02/2089
Riassunto
Surgeons that experience sleep restriction and deprivation, may have attentional lapses: the onset of lapses and microsleeps increase the probability of making medical errors, compromising patient's safety. Electroencephalography (EEG) is a gold standard tecnique for monitoring cortical electrical activity and it can objectively measure and track drowsiness. However, EEG cannot be worn during daily work's shift due to its encumbrance and bulk. The aims of this study is to design an EEG device that is miniaturized, wearable, lightweight, motion tolerant. The device sends the EEG signals through a wireless communication to an external device where they will be processed using classification algorithms able to detect drowsy states.
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