KA240601 Biological Information Processing

Hiroshima University Syllabus

Japanese

Academic Year 2025Year School/Graduate School School of Informatics and Data Science

Lecture Code KA240601 Subject Classification Specialized Education

Subject Name 生体情報学

Subject Name
（Katakana）セイタイジョウホウガク

Subject Name in
English Biological Information Processing

Instructor FURUI AKIRA

Instructor
(Katakana) フルイ　アキラ

Campus Higashi-Hiroshima Semester/Term 3rd-Year,  Second Semester,  3Term

Days, Periods, and Classrooms (3T) Weds1-4：IAS K108

Lesson Style Lecture Lesson Style
(More Details) Face-to-face

Lecture & Exercises using Python

Credits 2.0 Class Hours/Week 4 Language of Instruction B : Japanese／English

Course Level 3 : Undergraduate High-Intermediate

Course Area（Area） 25 : Science and Technology

Course Area（Discipline） 02 : Information Science

Eligible Students 3rd grade

Keywords Biosignal Processing, Visual and Auditory Information Processing, Motor Control, Brain Information Processing, Machine Learning, Pattern Recognition, Human-Computer Interaction

Special Subject for Teacher Education 　 Special Subject 　

Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) This course teaches information processing technologies focused on humans, providing students with computational methods for human understanding. By comparing human biological systems with information technology, students will learn to analyze information processing from multiple disciplines.
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) Computer Science Program
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.

Data Science Program
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis.

Intelligence Science Program
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis.
・D2. Information processing ability and data analysis ability to contribute to the application and development of artificial intelligence and IoT.

Class Objectives
/Class Outline This course covers information processing in the human body and brain, along with computational methods for understanding and applying these processes. Students will learn about visual, auditory, and motor systems, study brain information processing theories, and explore biosignal measurement techniques and machine learning applications. Python exercises will provide both theoretical knowledge and practical skills in biological informatics.

Class Schedule Lesson 1. Guidance and Introduction
Lesson 2. Biosignal Measurement and Processing Techniques
Lesson 3. Vision I: Human Visual System and Information Processing
Lesson 4. Vision II: Fundamentals and Applications of Computer Vision
Lesson 5. Audition I: Human Auditory System and Speech Recognition
Lesson 6. Audition II: Acoustic Signal Processing and Machine Audition
Lesson 7. Motor I: Human Motor Control and Learning Mechanisms
Lesson 8. Motor II: Motion Recognition and Robotics
Lesson 9. Neural System I: Structure and Function of the Nervous System
Lesson 10. Neural System II: Predictive Information Processing
Lesson 11. Biosignal Processing and Feature Extraction
Lesson 12. Biological Information Analysis Using Machine Learning
Lesson 13.  Individual Differences and Adaptive Learning
Lesson 14. Social Implementation of Bioinformatics
Lesson 15. Summary

Assessment through exercises and a final report assignment.

Text/Reference
Books,etc. Course materials will be distributed on the course support page.

PC or AV used in
Class,etc.

(More Details) Text, Handouts, PC

Learning techniques to be incorporated

Suggestions on
Preparation and
Review Course materials will be distributed. Reviewing them before and after lectures will help deepen your understanding of the content. Also, the exercise assignments will help reinforce the content of each session.

Requirements Python will be used for exercises. Please prepare a programming environment by setting up Python on your local PC or preparing Google Colaboratory.

Grading Method Comprehensive evaluation based on exercise assignments and a final report.

Practical Experience

Summary of Practical Experience and Class Contents based on it

Message

Other

Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching.

Academic Year	2025Year	School/Graduate School	School of Informatics and Data Science
Lecture Code	KA240601	Subject Classification	Specialized Education
Subject Name	生体情報学
Subject Name （Katakana）	セイタイジョウホウガク
Subject Name in English	Biological Information Processing
Instructor	FURUI AKIRA
Instructor (Katakana)	フルイ　アキラ
Campus	Higashi-Hiroshima	Semester/Term	3rd-Year, Second Semester, 3Term
Days, Periods, and Classrooms	(3T) Weds1-4：IAS K108
Lesson Style	Lecture	Lesson Style (More Details)	Face-to-face
Lecture & Exercises using Python
Credits	2.0	Class Hours/Week	4	Language of Instruction	B : Japanese／English
Course Level	3 : Undergraduate High-Intermediate
Course Area（Area）	25 : Science and Technology
Course Area（Discipline）	02 : Information Science
Eligible Students	3rd grade
Keywords	Biosignal Processing, Visual and Auditory Information Processing, Motor Control, Brain Information Processing, Machine Learning, Pattern Recognition, Human-Computer Interaction
Special Subject for Teacher Education		Special Subject
Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students)	This course teaches information processing technologies focused on humans, providing students with computational methods for human understanding. By comparing human biological systems with information technology, students will learn to analyze information processing from multiple disciplines.
Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students)	Computer Science Program （Abilities and Skills）・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value. Data Science Program （Abilities and Skills）・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value. ・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis. Intelligence Science Program （Abilities and Skills）・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value. ・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis. ・D2. Information processing ability and data analysis ability to contribute to the application and development of artificial intelligence and IoT.
Class Objectives /Class Outline	This course covers information processing in the human body and brain, along with computational methods for understanding and applying these processes. Students will learn about visual, auditory, and motor systems, study brain information processing theories, and explore biosignal measurement techniques and machine learning applications. Python exercises will provide both theoretical knowledge and practical skills in biological informatics.
Class Schedule	Lesson 1. Guidance and Introduction Lesson 2. Biosignal Measurement and Processing Techniques Lesson 3. Vision I: Human Visual System and Information Processing Lesson 4. Vision II: Fundamentals and Applications of Computer Vision Lesson 5. Audition I: Human Auditory System and Speech Recognition Lesson 6. Audition II: Acoustic Signal Processing and Machine Audition Lesson 7. Motor I: Human Motor Control and Learning Mechanisms Lesson 8. Motor II: Motion Recognition and Robotics Lesson 9. Neural System I: Structure and Function of the Nervous System Lesson 10. Neural System II: Predictive Information Processing Lesson 11. Biosignal Processing and Feature Extraction Lesson 12. Biological Information Analysis Using Machine Learning Lesson 13. Individual Differences and Adaptive Learning Lesson 14. Social Implementation of Bioinformatics Lesson 15. Summary Assessment through exercises and a final report assignment.
Text/Reference Books,etc.	Course materials will be distributed on the course support page.
PC or AV used in Class,etc.
(More Details)	Text, Handouts, PC
Learning techniques to be incorporated
Suggestions on Preparation and Review	Course materials will be distributed. Reviewing them before and after lectures will help deepen your understanding of the content. Also, the exercise assignments will help reinforce the content of each session.
Requirements	Python will be used for exercises. Please prepare a programming environment by setting up Python on your local PC or preparing Google Colaboratory.
Grading Method	Comprehensive evaluation based on exercise assignments and a final report.
Practical Experience
Summary of Practical Experience and Class Contents based on it
Message
Other
Please fill in the class improvement questionnaire which is carried out on all classes. Instructors will reflect on your feedback and utilize the information for improving their teaching.

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