Sinan Chen

Assistant Professor

Kobe University

Japan

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Sinan Chen is an Assistant Professor at Kobe University in Japan. His research interests encompass multimodal interaction, mobility assessment for older adults, and the integration of digital technology in education. Recent publications include works on sensor-based mobility assessment, the application of gamification in finger movement measurement, and enhancing personalized services using virtual agents. Additionally, he explores sustainable language learning solutions and the feasibility of pose detection for monitoring elderly individuals.

Sinan Chen

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Articles (17)

Towards Sensor-Based Mobility Assessment for Older Adults: A Multimodal Framework Integrating PoseNet Gait Dynamics and InBody Composition

Implementing Finger Movement Measure System with Music-Gamification Elements

Vision-Based Assessment of Skeletal Muscle Decline: Correlating Gait Variance with SPPB Performance

Enhancing Personalized Service Development with Virtual Agents and Upcycling Techniques

A Review of Multimodal Interaction in Remote Education: Technologies, Applications, and Challenges

Digital Human Technology in E-Learning: Custom Content Solutions

Enhancing Sustainable AI-Driven Language Learning: Location-Based Vocabulary Training for Learners of Japanese

Evaluating Feasibility of Pose Detection with Image Rotation for Monitoring Elderly People at Home

Long-Term Fine-Grained Forecasts of Emergency Demand Using EMS Big Data and Population Estimates

Needs Companion: A Novel Approach to Continuous User Needs Sensing Using Virtual Agents and Large Language Models

Consecutive and Effective Facial Masking Using Image-Based Bone Sensing for Remote Medicine Education

Assisting Personalized Healthcare of Elderly People: Developing a Rule-Based Virtual Caregiver System Using Mobile Chatbot

Uni-Messe: Unified Rule-Based Message Delivery Service for Efficient Context-Aware Service Integration

Toward Capturing Scientific Evidence in Elderly Care: Efficient Extraction of Changing Facial Feature Points

Nonintrusive Fine-Grained Home Care Monitoring: Characterizing Quality of In-Home Postural Changes Using Bone-Based Human Sensing

Toward Flexible and Efficient Home Context Sensing: Capability Evaluation and Verification of Image-Based Cognitive APIs

Integrating Multiple Models Using Image-as-Documents Approach for Recognizing Fine-Grained Home Contexts

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Kenji Sekiguchi

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