In recent years, technologies in which a living body and an artificial system are directly coupled, such as Brain-computer
interface (BCI), have been developed. EEG-based BCI is one of the widely studied BIC. For conducting projects on EEG-based
BCI, accurate understanding of brainwaves is required. This lecture mainly treats techniques for measuring electroencephalography
(EEG) and event-related potentials (ERP) including topics of human brain, cognitive neuroscience, bioinstrumentation, signal/information
processing and statistical analysis. Students learn the topics through presentations of each chapter of the textbook and papers
.
This lecture also treats mathematical models of biological phenomena and biomimetic information processing and research ethics in human research.
Students learn these topics through preparing and giving presentations on each chapter and treatise of the textbook and research papers in every class.
This lecture also treats mathematical models of biological phenomena and biomimetic information processing and research ethics in human research.
Students learn these topics through preparing and giving presentations on each chapter and treatise of the textbook and research papers in every class.
The purpose of this course is to learn basics of biology and physiology, measuring biological signals, signal processing,
information processing, and statistical analysis, which were required for conducting projects on EEG-based BCI. The purpose
of this course also includes learning basics of mathematical models of biological phenomena and biomimetic information processing.
Through learning the topics, students acquire wide view required for developing bionic systems.
- Can understand basics of biology and physiology, measuring biological signals, signal processing, information processing, and statistical analysis, which are required for conducting projects on EEG-based BCI
- Can understand basics of mathematical models of biological phenomena and biomimetic information processing
- Can understanding research ethics in human research
| Class schedule | HW assignments (Including preparation and review of the class.) | Amount of Time Required | |
|---|---|---|---|
| 1． | Overview of EEG-based brain computer interface | materials distributed in the class | 190minutes |
| 2． | Overview of EEG and ERP | materials distributed in the class | 190minutes |
| 3． | ERP Components | materials distributed in the class | 190minutes |
| 4． | Design of experiments recording EEG/ERP | materials distributed in the class | 190minutes |
| 5． | Recording EEG/ERP | materials distributed in the class | 190minutes |
| 6． | Artifact rejection and correction in measuring EEG/ERP | materials distributed in the class | 190minutes |
| 7． | Signal processing for EEG signals (1) - Frequency analysis - Filtering |
materials distributed in the class | 190minutes |
| 8． | Signal/information processing of EEG signals (2) - Correction and averaging techniques - Time frequency analysis |
materials distributed in the class | 190minutes |
| 9． | Amplitudes and Latencies of ERP | materials distributed in the class | 190minutes |
| 10． | Statistical Analysis of EEG/ERP experiments | materials distributed in the class | 190minutes |
| 11． | Mathematical model of biological phenomena and their application ・Mathematical model of biological phenomena ・Biomimetic information processing Research ethics in human research |
materials distributed in the class | 190minutes |
| 12． | Problem setting and Literature investigation on bionic and biomimetic engineering | materials distributed in the class | 190minutes |
| 13． | Presentations on bionic and biomimetic engineering | materials distributed in the class | 190minutes |
| 14． | Discussions on bionic and biomimetic engineering | materials distributed in the class | 180minutes |
| Total. | - | - | 2650minutes |
| presentations | assignments | Total. | |
|---|---|---|---|
| 1. | 90% | 90% | |
| 2. | 7% | 7% | |
| 3. | 3% | 3% | |
| Total. | 90% | 10% | - |
Grade is judged by presentations (90%) and assignments (10%) in each class.
60% of evaluation requires conducting survey, understanding and making presentation for basic technologies required for conducting system development of bionic systems by interdisciplinary view.
60% of evaluation requires conducting survey, understanding and making presentation for basic technologies required for conducting system development of bionic systems by interdisciplinary view.
Textbook: Steven J. Luck, "An Introduction to the Event-Related Potential Technique, Second edition," THE MIT PRESS
Foundations of electric and electronic circuits (amplifier), signal processing, industrial mathematics (Differential and integral
calculus, linear algebra, statistics)
- Lunch break on Friday: Making appointment is recommended.
- Course that cultivates an ability for utilizing knowledge
| Work experience | Work experience and relevance to the course content if applicable |
|---|---|
| Applicable | Utilizing the experience in research works on functional brain imaging in an institute of research, basics of biology and physiology, measuring biological signals, signal processing, information processing, system integration, biomimetic technologies, and ethics are explained. |
Last modified : Sun Mar 21 16:47:25 JST 2021