2026 (Current Year) Faculty Courses School of Engineering Department of Mechanical Engineering Graduate major in Mechanical Engineering

Human Interface

Academic unit or major: Graduate major in Mechanical Engineering
Instructor(s): Satoshi Miura
Class Format: Lecture (Face-to-face)
Media-enhanced courses: -
Day of week/Period (Classrooms): 5-6 Thu (M-135)
Class: -
Course Code: MEC.H436
Number of credits: 100
Course offered: 2026
Offered quarter: 2Q
Syllabus updated: Mar 5, 2026
Language: English

Syllabus

Course overview and goals

The purpose of this lecture is to learn the basics and applications of human interfaces, as well as to learn practical methods through hands-on experience.

Course description and aims

The objectives of this course are as follows:
・Be able to explain human interfaces and their surrounding areas.
・Be able to explain and put into practice models related to human interfaces.
・Be able to explain applications of human interfaces.

Keywords

Human interface, Human-centric design, Usability, Human machine interface, Human computer interaction

Competencies

Specialist skills
Intercultural skills
Communication skills
Critical thinking skills
Practical and/or problem-solving skills

Class flow

In this class, you will connect your PC to the internet and practice programming depending on the lecture session. Please prepare and review each lecture.

Course schedule/Objectives

	Course schedule	Objectives
Class 1	Fundamentals and recent aspects of human interface	Students will learn the history of HMI, Norman's Seven Principles, VR, AR, CA, NUI, OUI, and multimodal interfaces.
Class 2	Usability and human-centered design	Gain knowledge of usability, Nielsen's usability characteristics, UI, UX, accessibility, and more.
Class 3	Computational Neuroscience and Cognitive Models	Students will learn model human processors, NN, feedback error learning models, least orbit generation models, human error, Gestalt characteristics, Weber-Fechner, and Fitz's law.
Class 4	Cognitive model practice	Experience and acquire cognitive models through the program.
Class 5	Utilization of biometric data1	Acquire the mechanisms of operation accuracy, motion, tactile power, and hearing.
Class 6	Utilization of biometric data2	Acquire the mechanisms of vision, electromyography, electroencephalogram, BMI, and others.
Class 7	Evaluation and optimization of usability	Students will learn how to develop human interfaces using evaluation and optimization.

Study advice (preparation and review)

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.

Textbook(s)

Distribute materials as needed

Reference books, course materials, etc.

Yoshinori Kitahara, Learning Human Interface with Illustrations, Kodansha;
Kazunori Shido, Human Interface, Corona Publishing;
Takuya Kamata, Human Interface Theory, SCC;
Ichiro Shiio, Introduction to Human-Computer Interaction, Science Publishing;
Mitsuo Kawato, Computational Theory of the Brain, Sangyo Tosho;
Hirokazu Takahashi, Introduction to Brain Science for Mechanics: Reverse Engineering the Brain, Nikkan Kogyo Shimbun;
DA Norman, translated by Hisao Nojima, Design for Whom?, Shinyosha Cognitive Science Selection