1. Bongjae Choi, Sungho Jo Presented by: Yanrong Wo
A Low-Cost EEG System-Based Hybrid Brain-Computer Interface for Humanoid Robot Navigation and Recognition
Bongjae Choi, Sungho Jo
Presented by: Yanrong Wo

2. Background EEG BCI : Electroencephalogram Brain Computer Interface
Non-invasive
Two Types of BCI Protocols:
Active
Reactive
Non-invasive: easy, safe, but noisier/less accurate
Active: Consciously think about something
Reactive: brain signals related to an external stimuli
Active - more natural
Reactive - less training/simpler implementation

3. Active BCI Protocol ERD: Event Related Desynchonization
Amplitude Decrease
ERS: Event Related Synchronization
Amplitude Increase
Motor Imagery
Thinking about performing an action without executing it
Motor Imagery: Used by sports psycologists too

4. Reactive BCI Protocols
P300 Potential
wave caused by decision making
Amplitude increases after a target stimulus
300 ms delay
SSVEP
Steady state visually evoked potential
Response to visual stimuli at a certain frequency
SSVEP- Looking at certain frequency causes your brain to send signals at multiples of that frequency

5. What’s the goal?
Use a low-cost BCI system to navigate a humanoid robot through a maze from a designated start to a designated goal and along the way detect if there any images of the user’s favorite object.

6. The equipment Emotiv Epoc BCI Easy to use, portable, simple to operate
14 channels sampling at a frequency of 128Hz
Nao Humanoid
25 DOF
Monocular vision on its head
3.3cm/s walking speed, 0.13 rad/s turning speed (configured)

7. Is it cheap? BioSemi ActiveTwo
“8 channels hardware complete with active electrodes, plus acquisition software: approx: EUR 13,500”
“256+8 channels hardware complete with headcaps and active electrodes, plus acquisition software: approx. EUR 75,000”
13500 Euro = $14500
75000 = 80500

8. What’s the difference?
2015 paper

9. The experiment Two modes: Exploration and Navigation SSVEP and ERD
Recognition
P300

10. Exploration and Navigation
Moving forward and body turns (left/right)
Exploration
Head turns (left/right)
Visual feedback during both
ERD to switch between exploration and navigation modes
SSVEP for left/right head turns
ERD motor imagery can be anything, hand or foot, foot encouraged
User doesn’t control body turns - if body and head are misaligned by more than 9 degrees, switching into exploration mode will align them

11. Exploration and Navigation

12. Recognition Mode Objects in view are outlined in a box
User centers the view on the object(s)
Blue window border indicates recognition mode
4s rest, before each object randomly flashed for 250ms (random order)
Epoch of signals for that object is 600ms long starting from flashing
(Recall that P300 has a 300 ms delay)
Blue window border disappears indicating end of recognition mode
Place center of object(s) in center of screen

13. Recognition Mode

14. BCI Protocols ERD-based protocol Common Spatial Patterns SVM
SSVEP-based protocol
Canonical Correlation Analysis
Selection of SSVEP vs ERD
P300-based Protocol
xDAWN spatial filters
Bayesian linear discriminant
analysis classifier
Dynamic Fading Feedback Rule
CSP - extract features
SVM - support vector machine

15. Candidate Selection Criteria
Between years of age
Same gender (male)
Same laterality (right handed)
No central nervous system abnormalities
Not taking psychiatric medications
No history of epilepsy, dyslexia, or hallucinations
No previous BCI experience
5 healthy male volunteers (age 23.4 土 3.8

16. The whole thing

17. Video

18. The Results All subjects took more time (avg 1.22)
Took less steps and explored more
Two methods are comparable

19. Conclusions and Future Work
Has potential
Lower quality data, but worked
Apply to more practical applications
Make usage more user friendly

20. References
BioSemi. "Applications: N2pc Effect." Applications: N2pc Effect. N.p., n.d. Web. 02 Apr
BioSemi. "Frequently Asked Questions." Biosemi EEG ECG EMG BSPM NEURO Amplifiers Systems. N.p., n.d. Web. 02 Apr
Choi B, Jo S (2013) A Low-Cost EEG System-Based Hybrid Brain-Computer Interface for Humanoid Robot Navigation and Recognition. PLoS ONE 8(9): e doi: /journal.pone
Emotive. "Headsets Archives." Emotiv. N.p., n.d. Web. 02 Apr
Martinez-Leon, Juan-Antonio, Jose-Manuel Cano-Izquierdo, and Julio Ibarrola. "Are Low Cost Brain Computer Interface Headsets Ready for Motor Imagery Applications?" Expert Systems with Applications 49 (2016): Web.

21. Thanks!
Questions?