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Brain Computer Interface Mina Mikhail [email protected]

Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

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Page 1: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Brain Computer Interface

Mina [email protected]

Page 2: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Introduction

• Ways for controlling computers – Keyboard– Mouse– Voice– Gestures

• Ways for communicating with people– Talking – Writing – Gestures

Page 3: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Problem

• Shortage of the current ways of interaction– Require muscle movements

• Disabled people– Totally paralyzed people are estimated to be

2 cases per 100,000 each year– Amyotrohic lateral sclerosis (ALS)

• This raises the need of a new way of communication

Page 4: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Brain Computer Interface

• Direct Neural Interface or Brain-Machine interface

• An interface between the human brain and computers

• A New communication Channel

Page 5: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

BCI Misconceptions

• Cannot read thoughts

• Cannot write to the brain

• Cannot repair injured areas

• Cannot operate without your will

Page 6: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Human Brain• The Ultimate Parallel Machine !• Billions of neurons require a lot of energy.

– 15% of the cardiac output– 20% of total body oxygen consumption– 25% of total body glucose utilization.

• Energy consumption for the brain to simply survive is 0.1 calories per minute … and …

• 1.5 calories per minute during crossword puzzle

Page 7: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Brain Regions

•• Frontal Lobe Frontal Lobe – Primary motor cortex, Frontal Eye,– information processing,

•• ParietalParietal– Sensory information, taste, pressure, sound,

temp..•• OccipitalOccipital

– Visual processing center•• TemporalTemporal

– Auditory processing

Frontal lobe

Parietal

OccipitalTemporal

Page 8: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Human Brain

• Whenever a neuron is active, its voltage changes

Page 9: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Human Brain

• Million of neurons fire together• Each mental state produces a distinct

pattern of electrical activity

Page 10: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Measuring Brain Activity

Page 11: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Measuring Brain Activity• Positron emission tomography

– A radio Active isotope is injected into the subject’s blood

– Isotopes emits positrons• Advantages

– High spatial resolution• Disadvantages

– Expensive– Low time resolution– Not portable

Page 12: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Functional Magnetic Resonance• FMRI depends on blood flow• It measures the magnetic properties of the

hoemoglobin• Active neurons consume oxygen carried by

hemoglobin• Advantages

– High spatial resolution• Disadvantages

– Expensive– Low time resolution– Not portable

Page 13: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

EEG

• Measures the electrical activity of the neurons.

• Advantages– High time resolution– Cheaper– portable

• Disadvantages– Low spatial resolution– Still not user friendly

Page 14: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

EEG Montage

• 10-20 system– An international system that describes and

applies the location of the electrodes

Page 15: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Rhythmic Activity• Delta Band

– < 3 Hz– Deep sleep

• Theta Band– 4-7 Hz– Drowsiness and meditation

• Alpha Band– 8-12 Hz– Awake

• Beta Band– 13-30 Hz– Concentration and thinking

Page 16: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

BCI Categories

Page 17: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

BCI Categories

Page 18: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

BCI Categories

Page 19: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Differences

• Electrode placements• Number of electrodes• Number of trial before taking a decision

Page 20: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

General Approach

Page 21: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Signal Acquisition

• EEG CAP• Bioamplifier• Electrodes• Active electrodes• Conductive gel• Impedance Checker

Page 22: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Signal Preprocessing

• Artifacts– Technical Artifacts

• Line noise• Electrode Artifacts

Page 23: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Signal Preprocessing• Physiological Artifacts

– Eye Blinking artifacts– Eye movement Artifacts– Muscle Activity artifact

Page 24: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Signal Preprocessing

Page 25: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Methods for Artifact Rejection

• Filters • Artifact Rejection• Artifact Subtraction (using EMG sensors)• Blind Source Separation

– Independent Component Analysis (ICA)

Page 26: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Feature Extraction (frequency domain)

• Frequency Domain Features– FFT, wavelets, finite impulse response– EEG Frequency Band Power

• most of the times a measure of event related desynchronization (ERD) is used

Page 27: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Feature Extraction (Time domain)

• Spatial Domain Feautres– Hjorth parameters

• Three parameters are used to characterize the EEG

– Activity (mean power)– Mobility (mean frequency)– Complexity

Page 28: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Classification

• Bayes Classifiers

• Support Vector Machines• Artifical Neural Networks

Page 29: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Application

• Wheel Chair• Controlling Cursor• Controlling OS• Word Processing

Page 30: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

Research Labs

• Graz Brain Computer Interface• BCI Research at Alberta University• BCI Research at Oxford University• Berlin Brain Computer Interface• Computer Vision and Multimedia

Laboratory Geneva University

Page 31: Brain Computer Interface › ~rafea › csce590 › spring09 › mina › mina's p… · • Artifact Subtraction (using EMG sensors) • Blind Source Separation – Independent Component

BCI Systems