In the field of human-centric information systems, the instructor gives lectures on selected topics from media information processing, intelligent information processing, sensory information processing and biological information processing. The background science and the technologies of both hardware and software are discussed.
This course is aiming at providing the basic knowledge to understand human-centric information systems.
By completing this course, students will be able to
(1) Have an understanding of fundamentals on psychophysics, statistics, measurement engineering, multivariate analysis, display engineering, and human interface.
(2) Then based on (1), find the relations of those methodologies to media information processing, intelligent information processing, sensory information processing and biological information processing,
(3) Apply those methodologies to their own researches.
Media information processing, Intelligent information processing, Sensory information processing, Biological information processing
|✔ Specialist skills||Intercultural skills||Communication skills||Critical thinking skills||✔ Practical and/or problem-solving skills|
This course holds two classes in a row. Two classes are devoted to each item of the fundamentals of human-centric information systems. The theory and examples are introduced in the first class, and the exercises are assigned to students and the answers and related knowledges are explained in the second class.
|Course schedule||Required learning|
|Class 1||Orientation||What should you learn for human-centric information systems?|
|Class 2||Methodologies for psychophysics I||Understanding of basic methods and data analysis for psychophysical experiments.|
|Class 3||Methodologies for psychophysics II||Understanding of basic methods and data analysis for psychophysical experiments.|
|Class 4||Statistics for human-centric information systems I||Understanding of basic statistical methods in usability assessment for human-centric information systems.|
|Class 5||Statistics for human-centric information systems II||Understanding of basic statistical methods in usability assessment for human-centric information systems.|
|Class 6||Measurement engineering I||Learn temperature and optical sensors, and their analogue measurement circuits.|
|Class 7||Measurement engineering II||Learn measurement methods of frequency and phase, and then understand digital measurement circuits for sensors.|
|Class 8||Display engineering I||What are the principles and features of displays?|
|Class 9||Display engineering II||What are the principles and features of displays?|
|Class 10||Multivariate analysis for human-centric information systems I||Understand the the fundamentals of the multivariable analysis, cluster analysis, principal component analysis, etc.|
|Class 11||Multivariate analysis for human-centric information systems II||Understand how to perform multivariable analysis in medical practice and in human-centric information research and Learn how to apply those methods with the software.|
|Class 12||Basic concept on human interface I||Understanding of basic concepts required to design human interface such as interaction, affordance, cybenetics and virtual reality.|
|Class 13||Basic concept on human interface II||Understanding of basic concepts required to design human interface such as interaction, affordance, cybenetics and virtual reality.|
|Class 14||General discussion||How can you apply the methods learned in this course to research in the field of human-centric information systems?|
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Not specified. Supplementary materials will be provided.
The level of understanding is assessed by exercise in each class (60%).
The practical skill is assessed by the method according presentation or in it in the general discussion part (40%).