The overarching goal of this thesis is to make a start in the field of BCI. This thesis starts with an overview of the entire multi-disciplinary field of BCI, covering the basic fundamental ingredients, methods and modalities.
EEG-based BCI experiments have been designed and conducted. The experiments are designed to find distinctive brain patterns which are generated voluntary.
Next to the experiments an environment is created which offers a structured approach to the analysis of the EEG data from the experiments and allows for future continuation of BCI research.
The workbench contains, among others, the following models: ICA, FFT, AR, CSP and LD. The workbench performed well and produced quality results during testing. The quality of the experimental data after evaluation with the constructed workbench appeared to be mediocre at best, caused by the low spatial resolution of the EEG equipment, appliance errors and experimental design faults.
Recommendation for future work are to use different equipment, follow the line of synchronous BCI and construct a classifier to evaluate the data quality and construct an online BCI.
This thesis initiates BCI research at the TU Delft.
1.1.Brain Computer Interface 1
1.2.The nature of EEG 1
1.3.Problem domain 2
1.6.Research questions 3
2.1.BCI overview 7
2.1.1.BCI definition 7
2.1.2.The history of BCI 7
2.1.3.The target group 7
2.2.Basic BCI elements 8
2.3.The input 9
2.3.1.The neuron 9
2.3.2.The brain 10
2.4. Brain activity measurement 11
2.4.2. Selecting a measurement method – Why EEG? 13
2.4.3. Invasiveness 13
2.4.4. The 10-20 system 14
2.4.5. Channels 14
2.5.The potential classes 14
2.5.1.Event related potentials 15
2.5.2.Rhythmic activity 15
2.5.3.Event related (de)synchronizations (ERD/ERS) 16
2.5.4. BCI approaches 16
2.5.5. Natural intent versus active control 16
2.5.6. Pattern recognition versus operant conditioning approach 17
2.5.7. Synchronous vs. asynchronous control 17
2.5.8. Universal vs. individual 18
2.5.9. Online vs. offline 18
2.6.Signal pre-processing 18
2.6.1.Amplification & A/D-converter 18
2.6.3. Reference filters 18
2.6.4. Bandpass filter 19
2.6.6.Artifact removal 20
2.6.7.Independent Component Analysis 20
2.6.8. Properties of ICA 21
2.6.9. Maximizing non-Gaussianity 21
2.6.10. The algorithm of ICA 22
2.6.11. Limitations of ICA 22
2.6.12.Purpose of ICA 22
2.6.13. ICA assumptions versus EEG 23
2.6.14.Channel selection 23
2.7.Translation algorithm 24
2.7.1.Feature extraction 24
2.7.2.Feature classification 24
2.8.2. Training principle 25
2.8.3. Feedback 26
2.9.Comparing BCI 27
2.9.1.BCI performance 27
2.9.2.Comparing criteria 27
2.9.3. Combining approaches 28
2.10.In depth look at the translation algorithm 28
Imagine sitting in a room and suddenly you would like to know every thing about the crusades in the Middle Ages, without moving a single muscle but by simply thinking about this idea triggers your brain interface system in searching the required data and transfers it directly to your brain. And you can start discussing it with your friends.
Imagine the old blind guy being able to see again by connecting a camera to his brain, although he lost his sight in a car accident years ago.
Imaging take a well deserved vacation to a tropical island by simply inserting the coordinates in your computer and your mind is off…
Many similar ideas have been uttered over the years and countless movies have been made concerning a link to and from the brain. Movies like the Matrix have always fascinated man. For years these stories belonged solely in the realm of science fiction; however the last couple of years a shift has been made in to the realm of reality.
While some proposed ideas may seem to be too futuristic to be possible, it is not unlikely that the principle idea behind it will become reality in the future. In fact it is already taking shape.
Science has always pursued the goal of aiding the human being in an ever increasing effort to increase the quality of life, whether this is to cure and aid the disabled, assist in high workload environment or simply for our pleasure and entertainment. It is apparent that the pursuit of technological advances and increasing science never stops.
Off course these techniques do not come falling from the sky, but require great effort from dedicated researchers all over the world. This is where we start our journey…
Brain Computer Interface
What is a Brain Computer Interface? As mentioned in the preface a BCI represents a direct interface between the brain and a computer or any other system. BCI is a broad concept and comprehends any communication between the brain and a machine in both directions: effectively opening a completely new communication channel without the use of any peripheral nervous system or muscles.
In principle this communication is thought to be two way. But present day BCI is mainly focusing on communication from the brain to the computer. To communicate in the other direction, inputting information in to the brain, more thorough knowledge is required concerning the functioning of the brain. Certain systems like implantable hearing-devices that convert sound waves to electrical signal which in turn directly stimulate the hearing organ already exist today. These are the first steps. The brain on the other hand is on a whole other complexity level compared to the workings of the inner ear.
From here on the focus is on communication directly from the brain to the computer. Most commonly the electrical activity (fields) generated by the neurons is measured, this measuring technique is known as EEG (Electroencephalography). An EEG-based BCI system measures specific features of the EEG-activity and uses these as control signals.
Over the past 15 years the field of BCI has seen a rapidly increasing development rate and obtained the interest of many research groups all over the world. Currently in BCI-research the main focus is on people with severe motor disabilities. This target group has little (other) means of communication and would be greatly assisted by a system that would allow control by merely thinking.