25 Nov 2010 Tusday

1. Brain Computer Interface
http://eegclassifyandrecognize.blogspot.com/

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

4. Problem Statement
Handicaps
Handicaps need assistance to perform
their everyday activities

5. Problem Statement
Biometric Security
High Risk Security

6. Problem Statement
Medical Diagnose
For Mental disorders and spinal injuries

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.

8. Motivation
• Help handicaps to normal life and
communication without the need of others.

9. EEGsignal(Description )
•Definition:-
An electroencephalogram is a measure of the
brain's voltage changes as detected from scalp
electrodes.
Electrodes: Small metal discs placed on the scalp in special positions.

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.

12. EEGsignal(Descriptioncont)
•Waves

13. Brain Computer Interface(Description)
Definition:-
Brain Computer Interface (BCI) is a collaboration in
which a brain accepts and controls a Mechanical
device as a natural part of its representation of the
body.

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.
Dementia.(cognitive abilities).
Epileptic disease.

15. BrainComputerInterface(Descriptioncont.)
•In Review
Allow those with poor muscle control to
communicate and control physical devices

16. Agenda
• Basic System Architecture
• Tools, technologies and SWE Methodology
• Time Plan
• References

17. Basic System Architecture
Generic
EEG Signals
Classification
Computer
Interface

18. 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

19. Tools, technologies and SWE
Methodology
• Tools &Technologies
 Software
 Microsoft .NET Framework(Visual Studio 2008)
 Hardware
 Emotive SDK Research Edition.
• Software development methodology
 Agile.

20. Time Plan

21. References
Books
Author s are Dr Saeid Sanei and A. Chambers, EEG
Signal Processing.
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.

22. Thanks