Brain Computer Interface ppt
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Brain Computer Interface allows direct communication between the brain and external devices. It reads electrical signals from the brain and translates them into a digital format. Research on BCIs started in the 1970s with basic sensors implanted in rats, mice, monkeys and humans. Today, BCIs can be invasive, partially invasive or non-invasive. Invasive BCIs are implanted directly into the brain to provide high quality signals, while non-invasive BCIs like EEGs record electrical activity from the scalp. BCIs have applications in medicine, military technology, and assisting people with disabilities.
Brain Computer Interface ppt
- 1. Brain Computer Interface By, Ajay George S8 - IT 03/13/13 IT Department, JECC
- 2. What is BCI Direct communication pathway between the brain and an external device Reads electrical signals from brain Signals translated into a digital form 03/13/13 IT Department, JECC
- 3. History Research started from 1970 BCI Project by Jacques Vidal Implanting simple BCI sensors within rats, mice, monkeys, and humans. 03/13/13 IT Department, JECC
- 4. History 1990 - implanting an electrode in the motor cortex of a paralyzed patient. Makes the patient communicate by moving a cursor. 1999 Trained rats to use their brain signals to move a robotic water-dispensing arm. 03/13/13 IT Department, JECC
- 5. How BCI work 03/13/13 IT Department, JECC
- 6. How BCI work 03/13/13 IT Department, JECC
- 7. How BCI work Uses optical nerves for image input Camera input directed to brain 03/13/13 IT Department, JECC
- 8. Types of BCI Invasive Partially Invasive Non-Invasive 03/13/13 IT Department, JECC
- 9. Invasive BCI Targeted for people with paralysis Implanted directly into the grey matter Produce the highest quality signals Jens Naumann, a man with acquired blindness, being scar-tissue build-up interviewed about his vision 03/13/13 IT Department, JECC
- 10. Partially Invasive BCI BCI devices are implanted inside the skull produce better resolution signals Cathy Hutchinson, who was one lower risk of of the first persons to have a forming scar-tissue direct connection between her brain and a computer implanted 03/13/13 IT Department, JECC
- 11. Non-Invasive BCI Easy to wear produce poor signal dispersing the electromagnetic waves created by the neurons 03/13/13 IT Department, JECC
- 12. Recording Domains 03/13/13 IT Department, JECC
- 13. Electrocorticography(ECoG ) Pioneered in the early 1950s Measures the electrical activity of the brain Taken from beneath the skull Embeds electrodes in a plastic bag placed above cortex A surgical incision is required 03/13/13 IT Department, JECC
- 14. MRI technology Uses brain signals to control Detects the subjects brain signals and sends the MRI signals over Ethernet cables, via TCP/IP, to a computer. 03/13/13 IT Department, JECC
- 15. MRI technology 03/13/13 IT Department, JECC
- 16. Magnetoencephalography (MEG) Magnetic Field of 10-15 T to 10-13 T S.Q.U.I.D Sensors are required Shielded room is needed 03/13/13 IT Department, JECC
- 17. Electroencephalography (EEG) Recording of electrical activity along the scalp Measures voltage fluctuations resulting from ionic current. Fine temporal resolution Ease of use, portable and low set-up cost 03/13/13 IT Department, JECC
- 18. Electroencephalography (EEG) Emotiv Cap, 14 Electordes, Wireless connection. Commercial BCI from NeuroSky 03/13/13 IT Department, JECC
- 19. Electroencephalography (EEG) P300 03/13/13 IT Department, JECC
- 20. Electroencephalography (EEG) Described in frequency ranges Delta (隆) < 4 Hz. Most apparent in deep sleep states. Theta (慮) waves 4-8 Hz, appear in a relaxed state and during light sleep and meditation. 03/13/13 IT Department, JECC
- 21. Electroencephalography (EEG) Alpha (留) waves 8-12 Hz, associated with meditation and relaxation. Beta (硫) 13-30 Hz waves, connected to alertness and focus. Gamma (粒) waves > 30 Hz, related to subjective awareness 03/13/13 IT Department, JECC
- 22. Electroencephalography (EEG) System Block Diagram 03/13/13 IT Department, JECC
- 23. Processes Bandpass Filter - to filter out frequencies that do not fall within the 留 and 硫 ranges. Related to senseorimotor activities Common Spatial Patterns (CSP) enhances the discriminability between classes. 03/13/13 IT Department, JECC
- 24. Processes Feature Extraction methods used to collect useful vectors Log Variance Power Density Estimation (PSD) Wavelet Packet Decomposition (WPD) 03/13/13 IT Department, JECC
- 25. Processes Principle Component Analysis (PCA) -reduce the dimensionality of the feature vector Classification Method - to build classifier which discriminate between labels. Linear Discriminant Analysis (LDA) is used 03/13/13 IT Department, JECC
- 26. Electroencephalography (EEG) 03/13/13 IT Department, JECC
- 27. Applications Medicinal Military Bioengineering Brain operated wheelchair Multimedia and Virtual Reality 03/13/13 IT Department, JECC
- 28. Conclusion Enables people to communicate and control appliances with use of brain signals Open gates for disabled people. Development of new brain imagining techniques Numerous future applications 03/13/13 IT Department, JECC
- 29. Bibliography Toward Inexpensive and Practical Brain Computer Interface by Hamzah S. AlZubi Nayel S. Al-Zubi Waleed Al-Nuaimy Robot Navigation using Brain-Computer Interfaces by Athanasios Vourvopoulos and Fotis Liarokapis 03/13/13 IT Department, JECC
- 30. Bibliography A general framework of Brain-Computer Interface with Visualization and Virtual Reality Feedback by Gufei Sun, Kuangda Li, Xiaoqiang Li, Bofeng Zhang, Shizhong Yuan, Gengfeng Wu 03/13/13 IT Department, JECC
- 31. Thank You 03/13/13 IT Department, JECC