Researching and Teaching a Brain-Computer Interface at Tsinghua University with MATLAB
Psychology Students Developed Valuable Professional Skills
“In developing brain-computer interface technology, we used a large number of MATLAB tools.... These tools have made research on brain-computer interfaces easier and have also strongly promoted cutting-edge progress in brain-computer interfaces.”
Key Outcomes
- Signal Processing Toolbox and Statistics and Machine Learning Toolbox helped advance BCI research by automating aspects of data processing and freeing researchers up to focus on higher level tasks
- MATLAB interface made it possible for nontechnical psychology students to begin their own BCI research
- Academic case resources shared by collaborators in MATLAB were a useful teaching tool for students exploring the technology
Dan Zhang is an associate professor of psychology at Tsinghua University, an internationally recognized engineering and research institution, where his work focuses on understanding the power of the human brain. Zhang is working at the cutting edge of brain-computer interface (BCI) research, developing ways for computers to interpret and use brain signals to decode emotions.
Manually processing BCI data can be time-consuming and difficult. To solve this problem, Zhang has integrated MATLAB® tools, including Signal Processing Toolbox™ and Statistics and Machine Learning Toolbox™, to accelerate both research and student comprehension. These toolboxes enable researchers to present visual information, develop BCI decoding algorithms, and process and decode data in real time.
Zhang also used MATLAB tools in the classroom to help psychology students without a coding background learn and experiment with BCI technology. MATLAB offers rich academic case data, easy-to-use learning tutorials, and learning community support. It also offers scalability that encompasses both basic analysis functions and the exploration of new methods, helping students develop important professional skills.