2. Project Members
Supervisors
•Pro.Dr. Mostafa Gad-Haqq
•Pro.Dr.Tareq Gharib
•Dr. Howaida Abd El Fatah
Assistants
•T.A ManalTantawy
Team Members
•Ahmed KhaledAbd El-glil
•Ahmed MohamedAhmed Mahany
•IslamAhmed Hamed
•Kamal Ashraf Kamal
•Mohammed Saeed Ibrahim
3. Agenda
• Problem Statement
• Objective
• Motivation
• Description
Introduction to EEG Signals
Brain Computer Interface
• Basic System Architecture
• Tools, technologies and SWE Methodology
• Time Plan
• References
7. Objective
• Help disabled people to normal life and
communication without the need of others.
• Develop a generic EEG Classification that can
support different applications
• Develop brain computer interface application
by using cognitive EEG signal.
10. EEGsignal(Description cont)
•It is an approximation of the cumulative electrical
activity of neurons.
•Actions that affect the EEG signals to three categories:-
Muscular Movements
Expressive States
Cognitive States (Our Scope)
11. EEGsignal(Description cont)
•Study of EEG paves the way for some problem:-
Monitoring Alertness, Coma, and Brain death.
locating areas of damage following head injury and
tumour.
Investigating and testing epilepsy.
Monitoring the brain development.
investigating sleep disorders and mental disorders.
14. BrainComputerInterface(Descriptioncont.)
What is it good for ?
•People with little muscle control.
•Early medical diagnose
People with Amyotrophic lateral sclerosis(ALS)
Spinal injuries.
Mental disorders.
15. Agenda
• Basic System Architecture
• Tools, technologies and SWE Methodology
• Time Plan
• References
17. Basic System Architecture(cont)
EEG Signal
Pre-processing
EEG Signal
Classification
EEG Signal
acquisition
Emotive SDK
Research Edition.
Removal Noise
Feature Extraction
•DFT
•ICATransforms
•DiscreteWaveletTransform
•Autoregressive Modeling
Neural Network
Genetic Algorithm
SupportVector Machine
There are many algorithms to perform EEG signal feature extraction
and classification
Compare And Choose
Computer
Interface
18. Tools, technologies and SWE
Methodology
• Tools &Technologies
Software
Microsoft .NET Framework(Visual Studio 2008)
Hardware
Emotive SDK Research Edition.
• Software development methodology
Agile.
20. References
Books
EEG Signal Processing Book Dr Saeid Sanei (Author), J. A.
Chambers (Author).
Papers
Predicting ReachingTargets from Human EEG.[Paul S. Hammon,
Scott Makeig, Howard Poizner, EmanuelTodorov, and Virginia R. de Sa]
,IEEE Signal Processing Magazine-jaunary 2008.