umar farooq

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

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Improvement: 25% to 50% reduction of error rate

Using Multiple Features

LRP and ERD are independent