Selected Representative Publications
(★ = first or corresponding author)
1. Nonverbal Sensing — Measuring the User
★ Design and Implementation of a Nonverbal Information Analysis System
J. Woo, C. Matsumoto, Y. Sone. JACIII, 30(4), 2026.
— Skeletal-based gesture analysis comparing DTW-based and neural network-based classification for user-state sensing.
★ A Gaze Analysis System for Emotional Attunement in Human–Robot Interaction
Y. Sone, J. Woo. JACIII, 30(4), 2026.
— LSTM–MDN model predicting future 3D gaze points to anticipate user attention in MR smart-home environments.
Human Posture Recognition for Estimation of Human Body Condition
W. Quan, J. Woo, Y. Toda, N. Kubota. JACIII, 23(3), pp. 519–527, 2019.
— Posture-based estimation of physical condition as an early step toward multimodal state sensing.
2. Human-State Estimation — Understanding the User
★ System for Analyzing User Interest Based on Eye Gaze Responses to Enhance Empathy with Users
J. Woo, J. Hu. JACIII, 29(3), pp. 641–648, 2025.
— Estimating user interest from gaze responses to enable empathetic robot behavior.
★ Design of a Human-Centric Robotic System for User Support Based on Gaze Information
Y. Sone, J. Woo. JACIII, 29(4), pp. 796–802, 2025.
— Linking estimated user attention to concrete robot support decisions.
★ Emotional Empathy Model for Robot Partners Using Recurrent Spiking Neural Network with Hebbian-LMS Learning
J. Woo, N. Kubota. Malaysian Journal of Computer Science, 30(4), pp. 258–285, 2017.
— Computational model of empathetic internal state generation in robot partners.
3. Adaptive Support — Acting for the User
★ Development of a Control Support System for Smart Homes Using the Analysis of User Interests Based on Mixed Reality
Y. Sone, C. Matsumoto, J. Woo, Y. Ohyama. ROBOMECH Journal, 12(2), 2025.
— MR-based smart-home control driven by estimated user interest; digital-twin representation of real appliances.
★ Development of a Human-Centric System Using an IoT-Based Socially Embedded Robot Partner
J. Woo, T. Sato, Y. Ohyama. Journal of Robotics and Mechatronics, 35(3), pp. 859–866, 2023.
— Integrating robot partners with IoT living environments for context-aware information support.
★ Robot Partner Development Platform for Human–Robot Interaction Based on a User-Centered Design Approach
J. Woo, Y. Ohyama, N. Kubota. Applied Sciences, 10(22), 7992, 2020.
— Modular smart-device-based platform enabling rapid development of human-centric robot partners.
★ System Integration for Cognitive Model of a Robot Partner
J. Woo, J. Botzheim, N. Kubota. Intelligent Automation and Soft Computing, 24(4), pp. 829–842, 2018.
— Integrated cognitive–emotional–behavioral architecture; the foundation of the robot partner line. (Most-cited journal paper)
Interdisciplinary Collaboration
Modeling and Trajectory Tracking Control of Continuum Robot with Magnetic Spacer Disks and Soft Drives
S. Zhao, Q. Meng, X. Lai, J. Woo, J. She, E. F. Fukushima, M. Wu.
IEEE Transactions on Automation Science and Engineering, 22, pp. 22468–22483, 2025.
Book
J. She, J. Woo, Y. Ohyama. Introduction to Linear Control System Design. CORONA Publishing, 2022.
(Japanese ed.: 佘錦華・禹珍碩・大山恭弘『英語で学ぶ 制御システム設計』コロナ社)