BRAIN COMPUTER INTERFACES

AIM

This course aims at informing students about brain-computer interfaces and giving them the opportunity to use their engineering skills in this field by understanding the working principles of the current systems.

CONTENT

This course contains; Introduction to the course ,Background information ,BCI Basics ,EEG based BCI Approaches ,Stimulus presentation ,Recording and Analysis tools ,Details of Assignments,FNIRS based BCIs,Other BCIs ,Measuring the performance of BCIs,Applications of BCIs,Summary of the course and discussion, future perspectives,Student Presentations,Student Presentations.

1. 1

   Students who complete this course successfully: 1- Learn main concepts in brain-computer interfaces. 2- Learn working principles of several brain-computer interfaces. 3- Learn the performance measures of brain-computer interfaces. 4- Become familiar with the stimulus presentation, recording, and analysis tools. 5- Apply signal processing methods to EEG recordings obtained with brain-computer interfaces using software. 6- Acquire skills on reviewing and presenting research papers on brain-computer interfaces.

WEEKLY PLAN

1. WEEK 1

   Introduction to the course

2. WEEK 2

   Background information

   Preparation: Read the lecture slides

3. WEEK 3

   BCI Basics

   Preparation: Read the lecture slides

4. WEEK 4

   EEG based BCI Approaches

   Preparation: Read the lecture slides

5. WEEK 5

   Stimulus presentation

   Preparation: Read the lecture slides

6. WEEK 6

   Recording and Analysis tools

   Preparation: Read the lecture slides

7. WEEK 7

   Details of Assignments

8. WEEK 8

   FNIRS based BCIs

   Preparation: Read the lecture slides

9. WEEK 9

   Other BCIs

   Preparation: Read the lecture slides

10. WEEK 10

    Measuring the performance of BCIs

    Preparation: Read the lecture slides

11. WEEK 11

    Applications of BCIs

    Preparation: Read the lecture slides

12. WEEK 12

    Summary of the course and discussion, future perspectives

13. WEEK 13

    Student Presentations

    Preparation: Upload your presentation files

14. WEEK 14

    Student Presentations

ASSESSMENT

• Rate of Midterm Exam to Success50%
• Rate of Final Exam to Success50%

WORKLOAD

READING

• Desney S. Tan, Anton Nijholt. Brain-computer interfaces, Applying our Minds to Human-Computer Interaction, Springer, 2010.

TEACHING STAFF

• Assist.Prof. Zafer İŞCANCOORDINATOR
• Assist.Prof. Zafer İŞCAN