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Video and EEG based analysis for arousals detection in paras

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by

Maria Sbrancia

on 30 October 2013

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Transcript of Video and EEG based analysis for arousals detection in paras

Video and EEG based analysis for arousals detection in parasomnias
NOCTURNAL FRONTAL LOBE EPILEPSY (NFLE)
Characterized by frontal lobe seizures arising during sleep;
Clinical manifestations (seizures):
Dystonic posturing;
Vocalization;
Hypermotor automatisms (such as kicking);
Walking or running.
Types of NFLE:
Paroxysmal arousals
Paroxysmal nocturnal dystonia
Episodic nocturnal wonderings
Frequent unawareness of the events
Seizures usually last < 30s
Distinctive characteristics of NFLE:
Unpredictable occurrence of events
Many seizures per night
Non age-related onset
NREM AROUSAL
PARASOMNIAS

• Often confused with NFLE
• Inability to arouse fully from NREM sleep (first third of the night)
• Types of NREM arousal parasomnias:
Confusional arousals
Somnambulism
Sleep terrors

Differential diagnosis between NFLE and NREM arousal parasomnias
SCALP EEG
VIDEO-EEG
Not enough to establish a correct diagnosis
Gold-Standard for diagnosis
Obstacles using Video-EEG
Only available in hospitals
Unpredictable nature of motor events
Limited number of recorded events
Solution:
home-made video recordings
PROJECT:
Motion-detection video device
MAIN GOAL:
Build a motion sensitive device that records as many events as the ones detected by Video-EEG
Characteristics
Materials
Cheap
Portable
Easy to handle
Hardware:
Raspberry Pi
Night vision webcam
Software:
Motion-detection application compatible with Raspberry Pi OS
Current Situation
Following Steps
Daniel Hofko
Joana Carmona
Maria Sbrancia
Mariana Falcão
Rui Infante
MEBiom
Introdução à Engenharia Biomédica 2013/2014
Full transcript