In this subject, we will explore these technologies and approaches for acquiring and then translating brain activity into useful information. We will also discuss the components of a brain-computer interface (BCI) system, invasive and non-invasive neural interfaces, the clinical and practical applications for a variety of users, and the ethical considerations of interfacing with the brain. The topics includes basics of brain wave (EEG), BCI, signal processing, data mining, and also contains hands-on tutorial and laboratory session on using wearable device to collect and analyse EEG data.
Subject learning objectives (SLOs)
This is an interesting subject on Brain-Computer Interface (BCI) design with a focus on modern methods. Students will investigate the benefits and limitations of commonly used signal processing and data mining methods and signal processing methods (which include independent component analysis, Bayesian inference, dimensionality reduction, and information theoretic approaches), and then apply these methods on real neural data. We aim to equip students with the foundational knowledge and skills to pursue opportunities in the emerging field of brain-computer interface.
Teaching and learning strategies
Subject presentation includes combined lecture, tutorial and laboratory sessions and research and development work for the assignments. The tutorial sessions focus on hands-on experience in brain data analytics tools, and understanding and interpretation of the results. The laboratory sessions focus on hands-on experience in carrying out BCI experiments and collecting high quality data.
- J. Wolpaw and E. W. Wolpaw, Brain-Computer Interfaces: Principles and Practice, Oxford University Press, 2011.
- L. F. Nicolas-Alonso and J. Gomez-Gil, Brain Computer Interfaces, a Review, Sensors, 12, 2012, 1211-1279. 3. C. Kothe, BCILAB, https://sccn.ucsd.edu/wiki/BCILAB.
Assessment task 1
Your class activity (20%)
Note: Demonstrate your understanding of BCIs or EEG basics. Contribute to in-class activity and discussion.
Assessment task 2
The BCI consultant (35%)
Note: This assignment is a group project (form a team of 3) where students are given a business (industrial) or scientific problem and need to write a project proposal for approaching that problem by the means of BCIs. Students must also present a 15 minute pitch for the project in week 9.
Assessment task 3
EEG Data exploration, preparation and mining in action (45%)
Note: This assignment includes practical work on EEG data visualisation, exploration and preparation (preprocessing and transformation) for EEG data analytics. Students must also present a 15 minute pitch for the project in week 18. Further Information: Announced in class
Subject Introduction; The Role of Research in IT; Evaluating Sources of Information
Notes: Tutorial: Your Research Interests and Skills; Groups and Topics Confirmation
Assessment 1 commences: Building Research Skills