Wu Lab.

Human Sensing Laboratory (ヒューマン・センシング研究室)

Registered students (2025): D4:1, D1:2, M2:3, M1:5, Rs:2, B4:11, Total: 24    -Lab. News-

  • Supervisor (Bo Wu，Ph.D.)  -Link-

BO WU received the Ph.D. degree in Human Sciences from Waseda University, Tokyo, Japan in 2015. He is currently a lecturer in the School of Computer Science of Tokyo University of Technology, Japan. He also is a Research Follow with the Kansai University, DS lab. He has been engaged in the research fields of Internet of Things (IoT), information and computer science, and social and human informatics. His current research interests include human motion capture, eye-movement analysis, machine learning & Big data analysis, and human-centered application system development. Dr. Wu is a member of IEEE CS and Information Processing Society of Japan.

  • Publications

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  • Lab. Research Contents （研究内容）

    • The research goal of our lab is to Create New Value based on human sensing.
    • Sensing targets include Biosignals, Human motion, Eye movements, and Human-to-human or device output sensing etc.

  • 2026年度の募集計画：

    • 修士：3（定員最大5人）
    • 博士：1（定員最大2人）
    • 研究生・2026年1月再開予定（定員最大2人）
    • 注意事項：応募する時に履歴書、成績表と研究計画を送ってください。本研究室では複数の分野にまたがる研究テーマを大歓迎ですが、研究の実用性や”面白いさ“を最も重要視するため、できるだけ早めに連絡するように。

  • Keywords （キーワード）

    • Human behavior Analysis;
    • Deep learning;
    • XR (Cross Reality, include VR, AR, etc.)
    • Agricultural work support;
    • Body motion measurement;
    • Driver Characteristics Analysis;
    • Eye-tracking;
    • Empirical mode decomposition;
    • Human-computer interaction (HCI);
    • Vehicle Driving;
    • Usercentered design.

Ph.D. four-year students (D3+)
    • Yu Qi –A Famework of Imitative Movements Analysis for Animal Exercise Courses via Human Pose Estimation
Pre-Entry　Ph.D. One-year students (D1)
    • Jun Wang –アイトラッキングに基づくコミュニケーション用スケッチ描画過程解析に関する研究　（内部進学M２ー＞D１、奨学金付き）
    • Siyu Xiong –コミュニケーション能力の向上のための微表情における知的感情分析システムの開発に関する研究（進学M２ー＞D１）
Master’s Degree 2nd year students (M2)
    • Qirun Wang —Analyzing the Effects of Driving Experience on Backing Maneuvers Based on Data Collected by  Eye-Tracking Devices
    • Yanmei Jiao — リアルタイムな視線検出を用いたウォークスルー 型身分認証システムの開発に関する研究
    • Wenjiong Deng –自動車運転手がギアを切り替える際の視覚に関する研究
Master’s degree 1st year students (M1)
    • Chenhao Li  –Exploring the impact of different types of music on drivers （異なる種類の音楽がドライバーに与える影響を探る）
    • Hang Yi — Development of an AI Tennis Coaching System Based on CNN (CNNに基づくAIテニスコーチングシステムの開発)
    • Changlong Xu –Analysis of the effect of ambient light on dozing driving in long-distance driving simulation tasks (長距離運転シミュレーションタスクにおける居眠り運転に対する環境光の影響分析)
    • Yue Qian —
    • Zhenzheng Xu —Smart Glasses-Based Hazard Warning System for Driver’s Blind Spots （スマートグラスを用いた運転者の死角危険警告システム ）
Pre-Entry Master’s Students (2025.4-2026.3)
    • Qun Xu —An Intelligent Calligraphy Practice Assistance System Based on Deep Learning and Extended Reality (深層学習と XR に基づくスマート書道練習支援システム)
Pre-Entry Doctoral Students (2025.4-2026.3)
    • Xiangyu Su –スマートグラスにおける筆跡と指の動きによるマルチモーダル認証システム開発に関する研究
Undergraduates (Fourth-year student)
    • 11人在籍.
Undergraduates (Third-year student)
    • 13人予定.
Others
    • Ningyu Guo — Design of Household Robotic Arm System to sort Recyclable Resources based on Deep Learning
Alumnus (Graduate)
    • Zijun Wang (Waseda University Ph.D. Student ・Jin Lab.) — A privacy-conscious real-time fall detection system design via depth camera
    • Xuan Huang (Waseda University Ph.D.Student ・ Nishimura Lab.・ RA) –A Pose Detection based Continuous Authentication System Design via Gait Feature Analysis
    • Jie Gao (Employment in IT Corporation, Japan) –A Wearable Warning System Design for Mask Recognition via AR Smart Glasses
    • Chu Zhang (Repatriation, China) –スマートグラスに基づく手話認識と翻訳システムの開発に関する研究
    • Siwei Zhao (Repatriation, China) – –ジェスチャーと表情を両方考慮したクラウド型手話翻訳システム開発に関する研究

  • Core Technologies & Devices（コア技術） -Link-

    • Eye Tracker (Tobii Pro Glasses 3)

Tobii Pro Glasses 3 is an Eye tracker device which desigSned to enable easy, precise, and efficient collection of eye tracking data in a wide variety of research scenarios.
Accurate data and robust eye tracking capabilities can be relied on in uncontrolled situations and real-world environments.

    • Motion Capture Device (Xsens MVN)

Xsens MVN is a wearable acceleration sensor-based motion capture device.
Unlike traditional motion capture devices which usually use a 17-joint model to represent the human body, the MVN device can collect data from 23 joints.

    • Driving Simulator

Driving Simulator. By using a laboratory-built driving simulator, it is possible to investigate and study the effects on drivers by adjusting external environments including light, sound, or simulating long periods of driving.

  • Research Topics (研究例) -Link-

Analysis on Falling Risk of Elderly Workers when Mowing on a Slope

Mowing is one of the most dangerous tasks in agricultural production which may cause accidents such as falling or accidental cutting. However, in the areas of mountainous in Japan, the mowing works still need to be done via the manually operated machines. In this research, we focus more on the mowing workers’ personal factors and try to analyze the effect on their falling risk via a high precision motion capture device (Xsens MVN) and Eye tracker (Tobii Pro Glasses 3).

Multi Sensor-based Driver Behaviors Analyzing and Modeling

About 90% of traffic accidents are due to human error, human factors may affect a driver’s braking behaviors and thus their driving safety, especially . To determine the effect of different human factors on drivers’ pre-braking behaviors, This study focused on analyzing drivers’ local joints by a motion capture device. Hilbert–Huang Transform (HHT)-based local human body movement analysis method was used to decompose the realistic complex pre-braking actions.