the first seminar

Brain Computer Interface

http://eegclassifyandrecognize.blogspot.com/

Project MembersSupervisors• Pro.Dr. Mostafa Gad-Haqq• Pro.Dr.Tareq Gharib• Dr. Howaida Abd El Fatah

Assistants• T.A Manal Tantawy

Team Members• Ahmed Khaled Abd El-glil• Ahmed Mohamed Ahmed Mahany• Islam Ahmed Hamed• Kamal Ashraf Kamal• Mohammed Saeed Ibrahim

Agenda• Problem Statement• Objective• Motivation• Description

Introduction to EEG Signals Brain Computer Interface

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

Problem Statement

HandicapsHandicaps need assistance to

perform their everyday activities

Problem Statement

Biometric SecurityHigh Risk Security

Problem Statement

Medical DiagnoseFor Mental disorders and spinal

injuries

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.

Motivation

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

EEG signal( 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.

EEG signal( 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)

EEG signal( 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.

EEG signal(Description cont)

•Waves

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.

Brain Computer Interface( Description cont. )

What is it good for ?

•People with little muscle control.•Early medical diagnosePeople with Amyotrophic lateral sclerosis(ALS)

Spinal injuries.Mental disorders.

Dementia.(cognitive abilities).Epileptic disease.

Brain Computer Interface( Description cont. )

•In Review

Allow those with poor muscle control to communicate and control physical devices

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

Basic System Architecture

GenericEEG

Signals Classificat

ion

Computer Interface

Basic System Architecture(cont)

EEG Signal Pre-

processing

EEG Signal Classificatio

n

EEG Signal

acquisition

Emotive SDK Research Edition.

Removal NoiseFeature Extraction• DFT• ICA Transforms• Discrete Wavelet

Transform• Autoregressive Modeling

Neural NetworkGenetic AlgorithmSupport Vector Machine

There are many algorithms to perform EEG signal feature extraction and classification

Compare And Choose

Computer

Interface

Tools, technologies and SWE Methodology• Tools & Technologies

Software Microsoft .NET Framework(Visual Studio

2008)

Hardware Emotive SDK Research Edition.

• Software development methodologyAgile.

Time Plan

References

BooksAuthor s are Dr Saeid Sanei and A. Chambers, EEG Signal Processing.

PapersPredicting Reaching Targets from Human EEG.[Paul S. Hammon, Scott Makeig, Howard Poizner, Emanuel Todorov, and Virginia R. de Sa] ,IEEE Signal Processing Magazine-jaunary 2008.

Thanks