1. The Berlin Brain-Computer Interface: Machine Learning-Based Detection of User Specific Brain States Umar Farooq Berlin Brain Computer Interface

2. 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

4. 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

5. 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.

6. 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 each Other 3 got training only once Highlight Interval time :1.75 to 2.25sec

7. 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

8. Feedback Sessions 1D ‘absolute’ Cursor Control Display Refreshing Rate: 25fps 15 cm 3 cm Representing Success of trials 20 cm With every new frame at t 0, the cursor is updated to a new position (p t 0,0) according to the classifier output Blue represents the target For the purpose of hint to the subject

9. Feedback Sessions 1D ‘relative’ Cursor Control Display Refreshing Rate: 25fps With every new frame at t 0, position of cursor p t 0 is old position p t 0 -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

10. Basket Game Success and Failures Smaller than the centre one as knack is easier at sides 1200 to 3000 ms

11. BCI control on x axis Time on y axis Left Trials Right Trials Erroneous Trials Erroneous trials are represented by dotted lines

12. Information Transfer Rate (ITR) ------- bits per minute Cursor rate control

13. 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 Average Speed 7.6 char/min including correction of all errors occurred during typing

14. Improvement: 25% to 50% reduction of error rate Using Multiple Features

16. LRP and ERD are independent