The Berlin Brain-Computer Interface: Machine Learning-Based Detection of User Specific Brain States
Umar Farooq
Berlin Brain ComputerInterface
Lateralized Readiness Potential :
Advantages•Early Distinction of left and right hand movements•Refractory period is small enough to offer high speed commands
Disadvantages•Doesn’t last long, persistence is small•For patients, with long time disability they loose the ability to generate readiness potential •Classification resolution is small
Negative Shift of the Brain Potential contralateral to the intention of hand movement
Subject’s Profile
• 6 Subjects ( all male; age 27 – 46 years): – 2 had one session experience with previous BBCI
setup– 1 had one session experience with current BBCI
setup– 2 had 4 sessions experience with current BBCI
setup– 1 subject had no prior experience with any BCI
setup
* 1 session means 25 trials
To ensure only EEG based feedback
• In addition to EEG, EMG ( at both forearms and right leg )and EOG ( for both horizontal and vertical eye movement) were recorded to ensure that they don’t offer any influence on generating feedback.
Training Sessions
• By training we mean Machine Learning, not Subject Learning
Left Hand (L)
Right Hand(R)
Right Feet (F)
Highlight time: 3.5 sec
3 subjects did 3 sessions eachOther 3 got training only once
Highlight Interval time :1.75 to 2.25sec
Topographic display of the energy in specified frequency band
Darker Shades indicate lower energy resp. ERD
Only Two classes are chosen that gave best discrimination in order to train a binary classifier
Feedback Sessions• 1D ‘absolute’ Cursor Control
Display Refreshing Rate: 25fps
15 cm
3 cm
3 cm
Representing Success of trials
20 cm
With every new frame at t0, the cursor is updated to a new position (pt0,0) according to the classifier output
Blue represents the targetFor the purpose of hint to the subject
Feedback Sessions• 1D ‘relative’ Cursor Control
Display Refreshing Rate: 25fps
With every new frame at t0,
position of cursor pt0 is old position pt0-1, shifted by an amount proportional to the classifier output
Difference is that now we are controlling the direction and speed for the cursor position rather than the absolute position of cursor
Basket Game
Success and Failures
Smaller than the centre one as knack is easier at sides
1200
to
3000
ms
BCI control on x axisTime on y axis
Left Trials
Right Trials
Erroneous Trials
Erroneous trials are represented by dotted lines
Information Transfer Rate (ITR) ------- bits per minute
Cursor rate control
Mental Typewriter Not based on EVOKED POTENTIAL
Based on Right hand and Right Foot Movements
•Imagining the right hand, turns the arrow clockwise•By Imagining the right foot movement, rotation stops and arrow starts extending•If this imagination is performed in longer period the arrow touches the hexagon and thereby selects it
Ave
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Improvement: 25% to 50% reduction of error rate
Using Multiple Features
LRP and ERD are independent
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