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Difference between revisions of "EEG artifact detection for epilepsy monitoring"

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=== Introduction ===
 
=== Introduction ===
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===Status: Available===
 
===Status: Available===
 
:Looking for Semester and Master Project Students
 
:Looking for Semester and Master Project Students
:Supervision: [[:User:Thoriri | Thorir Mar Ingolfsson]], Andrea Cossettini, Simone Benatti
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:Supervision: [[:User:Thoriri | Thorir Mar Ingolfsson]], [[:User:Cosandre | Andrea Cossettini]], Simone Benatti
  
 
===Character===
 
===Character===
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Revision as of 10:54, 5 November 2021

Ieeg seizure.png

Introduction

Epilepsy is a central nervous system disorder in which brain activity becomes abnormal, causing seizures or periods of unusual behavior, sensations, and sometimes loss of awareness. The golden diagnostic standard is represented by Electroencephalography (EEG) systems, which unfortunately are cumbersome and can make patients uncomfortable because of perceived stigmatization. Thus, both patients and caregivers would benefit from the availability of wearable long-term EEG monitoring devices. These long-term EEG monitoring devices must be robust to different noises or artifacts, which can be either external disturbances or movement of the patient that taints the EEG signal.

Project Description

In this project, the student works with an EEG headband with dry and wet electrodes attached to it and the BioWolf wearable ExG device, which has the PULP Mr. Wolf multicore processor on board. The project’s goal is to design a system capable of detecting various artifacts and then indicate to the user that artifacts are present and then do measures to either disregard that data or smooth it out to try to reconstruct the original EEG signal from it.


Status: Available

Looking for Semester and Master Project Students
Supervision: Thorir Mar Ingolfsson, Andrea Cossettini, Simone Benatti

Character

  • 20% literature review
  • 80% Implementation


Professor

Luca Benini

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