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Emotiv Epoc/EEG/BCI

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Technical seminar on a brain computer interfacing device known as emotiv epoc and its working principles eeg and bci.

Technical seminar on a brain computer interfacing device known as emotiv epoc and its working principles eeg and bci.

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  • 1. Technical Seminar on “Emotiv Epoc/EEG/BCI” By Suhail Ahmed Khan 1RN07EC096
  • 2. Introduction
    • Emotiv Epoc is a brain computer interfacing device
    • It is basically a headset that can read and interpret brain waves
  • 3.
    • Emotiv Epoc is based on two working principles which are- Electroencephalography and Brain-Computer Interfacing
    • Electroencephalography (EEG) is the recording of electrical activity along the scalp produced by firing of neurons within the brain.
    • A brain-computer interface (BCI), sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a human brain and an external device.
  • 4. Working Principles
    • The Emotiv system measures the electrical activity associated with the brain and the muscles of the face. What the brain-computer interface essentially does is process the electrical signals linked with the brain activity and convert them into a command or a language that can be understood by the machine.
  • 5.
    • This Block Diagram gives us the general idea of brain computer interface
    • BCI is of three forms- invasive(where the BCI is directly implanted in the brain), Partially invasive(Planted partially inside the skull) and Non invasive ( where the BCI is planted completely on the external of the skull)
  • 6.
    • Electroencephalography belongs to the Non Invasive BCI category.
    • It is a neurological test that involves attaching electrodes to the head of a person to measure and record electrical activity in the brain over time.
    • It works using the most common Artificial Neural Networks Learning and Training techniques, namely the Back Propagation algorithm and McCulloch-Pitts model.
  • 7. Biological Neuron Biological Terminology ANN terminology Neuron Node/unit/cell Synapse Connection/link Synaptic Efficiency Connection Strength/weight Firing frequency Node output
  • 8. McCulloch-Pitts Model
    • Simplest form of Artificial Neural Model.
    • Here different inputs, X 1 to X n are fed to a summer along with some known weights (W 0 to W n )
    • These are given to an activation function, which determines the output in terms of avtivation value or induced local field.
    • Some common activation functions are the threshold function and sigmoid functions.
    • This is classified under supervised learning
  • 9. Back Propagation Algorithm
    • It is a supervised learning method, and is a generalization of the delta rule.
    • There are two phases in BP: Propagation and weight update using delta rule.
    • Error at the output can be calculated directly at the output neurons using d j (n)-y i (n) but this corresponds to hidden neurons.
    • Hence the hidden neurons need to be penalized or awarded.
    • This is done by back propagating the error backwards.
  • 10.
    • The  delta rule  is a gradient descent learning rule for updating the weights of the artificial neurons in a single-layer  perceptron.
    • For a neuron j with activation function g(x), the delta rule for j’s ith weight w ji is given by,
  • 11. Hardware Components
    • The main physical components are the 14 electrodes, the gyroscope, sensors and a Lithium-poly battery.
    • The device connects wirelessly with the computer or the embedded system.
  • 12. Specifications Number of Channels 14 (plus CMS/DRL references) Channel names (Int. 10-20 locations) AF3, AF4, F3, F4, F7, F8, FC5, FC6, P7, P8, T7, T8, O1, O2 Sampling method Sequential sampling, Single ADC Sampling rate ~128Hz (2048Hz internal) Resolution 16 bits (14 bits effective) 1 LSB = 1.95μV Bandwidth 0.2 - 45Hz, digital notch filters at 40Hz and 60Hz Dynamic range (input referred) 256mVpp Coupling mode AC coupled Connectivity Proprietary wireless, 2.4GHz band Battery type Li-poly Battery life (typical) 12 hours Impedance measurement Contact quality using patented system
  • 13. Operation
  • 14. Training
    • Just like any other ANN device, the EPOC has to be trained under supervised learning to give the desired outputs.
  • 15.
    •   This sort of training is usually called Cognitive Training, where Data from training to classify their individual brainwave ‘signature’, for each focussed and intent thought trained.
    • There are four different mental states or facial gesture and predefined Actions that can be triggered when they occur.
  • 16. Software
    • ABI is a simple software for the Modular EEG that implements an experimental Brain Computer Interface (BCI).
    • Multichannel Human Computer
    • Interface allows traditional input of
    • conscious control while providing a
    • feedback loop based on user
    • perception
  • 17.
    • The programming language used in the API (application program interface) is known as Python C.
    • Example code is as shown below:
    consumer_key = 'x31x00x35x54x38x10x37x42x31x00x35x48x38x00x37x50' research_key = 'x31x00x39x54x38x10x37x42x31x00x39x48x38x00x37x50'   sensorBits = { 'F3': [10, 11, 12, 13, 14, 15, 0, 1, 2, 3, 4, 5, 6, 7], 'FC6': [214, 215, 200, 201, 202, 203, 204, 205, 206, 207, 192, 193, 194, 195], 'P7': [84, 85, 86, 87, 72, 73, 74, 75, 76, 77, 78, 79, 64, 65], 'T8': [160, 161, 162, 163, 164, 165, 166, 167, 152, 153, 154, 155, 156, 157], 'F7': [48, 49, 50, 51, 52, 53, 54, 55, 40, 41, 42, 43, 44, 45], 'F8': [178, 179, 180, 181, 182, 183, 168, 169, 170, 171, 172, 173, 174, 175] } classEmotivPacket (object): def__init__ (self, data): self . counter = ord(data[0]) self . sync = self . counter == 0xe9 self . gyroX = ord(data[29]) - 102 self . gyroY = ord(data[30]) - 104 #assert ord(data[15]) == 0  
  • 18.  
  • 19. Applications
    • The lists of applications for this device are numerous ranging from medical applications to electro-mechanical to entertainment applications.
    • The applications can be divided into two types- The ones currently in use and those that are in beta (development) stages.
  • 20. Present Applications
    • Currently this system is being used in Virtual 3D navigation and in gaming applications.
    • Here a person can control a character on the screen just through his or her facial expressions.
    • No physical movements of arms is required as in traditional gaming.
  • 21. Developer Applications
    • Two of the best known developer applications of the Emotiv Epoc are: The brain driver car and the mind controlled wheel chair
    • In the brain driver car the can be made to accelerate/decelerate or turn just by bio-electric signals from the 16 channel EPOC
    • An electric wheel chair can be made to navigate just by simple actions such as blinking and smiling.
  • 22.
    • Brain Driver Car
    • Mind Controlled Wheel Chair
  • 23. Advantages/Disadvantages
    • Advantages
    • New method of interacting with machines/computer, where no physical touch is required.
    • Relatively cheap compared to other EEG devices.
    • No conduction gel required for the electrodes.
    • Disadvantages
    • Current version limits to only four different actions(i.e., inputs)
    • Many applications still in beta stages
    • Hard to market since not many people are known to the idea of BCI.
  • 24. Current Status
    • This system is being currently extensively being used in the medical and gaming fields. But it is still in the developer (Beta) stages for most of its Electro-Mechanical Applications.
    • There is stiff competition from other BCI products such as OCZ’s neural impulse actuators (NIA), shown in figure. It uses only 3 electrodes.
  • 25. Conclusion
    • Brain-Computer Interface (BCI) is a method of communication based on voluntary neural activity generated by the brain and independent of its normal output pathways of peripheral nerves and muscles.
    • The neural activity used in BCI can be recorded using invasive or non-invasive techniques.
    • We can say as detection techniques and experimental designs improve, the BCI will improve as well and would provide wealth alternatives for individuals to interact with their environment.
    • Electroencephalography is the process of recording the electrical activity in the brain.
    • Emotiv Epoc is a neural headset that works on the principle of Electroencephalography or EEG.
  • 26. Questions
  • 27. Video