Course title
1M5163001
Bionic and biomimetic system engineering

HORIE Ryota Click to show questionnaire result at 2017
Course content
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.
Purpose of 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.
Goals and objectives
  1. 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
  2. Can understand basics of mathematical models of biological phenomena and biomimetic information processing
  3. Can understanding research ethics in human research
Language
English
Class schedule

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
Relationship between 'Goals and Objectives' and 'Course Outcomes'

presentations assignments Total.
1. 90% 90%
2. 7% 7%
3. 3% 3%
Total. 90% 10% -
Evaluation method and criteria
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.
Textbooks and reference materials
Textbook: Steven J. Luck, "An Introduction to the Event-Related Potential Technique, Second edition," THE MIT PRESS
Prerequisites
Foundations of electric and electronic circuits (amplifier), signal processing, industrial mathematics (Differential and integral calculus, linear algebra, statistics)
Office hours and How to contact professors for questions
  • Lunch break on Friday: Making appointment is recommended.
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
Active-learning course
More than one class is interactive
Course by professor with work experience
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.
Education related SDGs:the Sustainable Development Goals
  • 3.GOOD HEALTH AND WELL-BEING
Last modified : Fri Mar 18 23:14:28 JST 2022