1st seminar
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This document provides an overview of a brain computer interface project. It introduces the project members and supervisors. It then discusses the objectives of helping disabled people communicate without assistance and developing a generic EEG classification system. It provides descriptions of EEG signals, what they measure in the brain, and how they are detected by electrodes on the scalp. It outlines the basic system architecture of acquiring EEG signals, preprocessing, feature extraction, classification, and a computer interface. It also lists the timeline, tools used including Emotive SDK and software development methodology. In summary, the document outlines a student project aiming to develop a brain computer interface using EEG signals to help people with disabilities communicate.
![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.](https://image.slidesharecdn.com/finalseminar-101126075027-phpapp01/85/1st-seminar-20-320.jpg)
1st seminar
- 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.
- 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.
- 15. Agenda • Basic System Architecture • Tools, technologies and SWE Methodology • Time Plan • References
- 16. Basic System Architecture Generic EEG Signals Classification Computer Interface
- 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.
- 19. Time Plan
- 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.
- 21. Thanks