Research Vision
Human-Centered Intelligent Healthcare
Future healthcare systems should not only diagnose disease but also
understand the patient's cognitive, emotional, and physiological
condition. Our research explores AI-driven approaches that support
clinicians, therapists, educators, and patients through continuous,
multimodal assessment and personalized interventions.
Core Technologies
AI Meets Digital Health
We integrate physiological sensing, wearable devices, machine
learning, digital twins, and immersive environments to create
intelligent healthcare applications that improve patient outcomes and
clinical decision-making.
Physiological AI
Digital Health
Machine Learning
Wearable Sensors
Multimodal Data
Clinical Decision Support
Mental Wellbeing
Monitor Emotional Health
Develop AI models capable of estimating stress, anxiety, fatigue,
emotional state, and cognitive wellbeing using multimodal
physiological and behavioral signals.
Neurofeedback
Personalized Brain-Based Interventions
Design adaptive neurofeedback systems that help individuals regulate
attention, relaxation, emotional balance, and cognitive performance
through real-time physiological feedback.
Rehabilitation
Support Recovery Through Intelligent Technologies
Explore immersive rehabilitation environments that adapt exercises,
difficulty levels, and therapeutic feedback according to each
patient's progress and physiological responses.
Mental Health
Early Detection and Continuous Monitoring
Develop intelligent systems for monitoring stress, burnout,
depression, anxiety, cognitive fatigue, and emotional wellbeing in
both clinical and everyday environments.
Rehabilitation
Adaptive Physical and Cognitive Therapy
Support rehabilitation through immersive virtual environments,
neuroadaptive feedback, personalized exercise planning, and progress
monitoring.
Medical & Dental Training
Intelligent Clinical Education
Create immersive simulation platforms that assess trainee workload,
stress, decision-making, and technical performance to improve medical
and dental education.
Personalized Healthcare
Data-Driven Patient Support
Build personalized healthcare systems that combine multimodal sensing,
digital twins, and predictive AI to recommend individualized care and
improve long-term patient outcomes.
Future Directions
Healthcare That Understands the Individual
We envision healthcare technologies that continuously learn from each
individual, anticipate health-related changes, and provide adaptive,
transparent, and trustworthy support throughout prevention, diagnosis,
treatment, and rehabilitation.
Mental Wellbeing
Stress Detection
Neurofeedback
Digital Twins
Rehabilitation
Responsible AI
Student Opportunities
Shape the Future of Intelligent Healthcare
Students contribute to projects involving physiological signal
processing, affective computing, biomedical AI, digital health,
immersive rehabilitation, clinical decision support, neurofeedback,
wearable technologies, and human-centered healthcare innovation.
Biomedical AI
EEG
Physiological Signals
Machine Learning
VR Rehabilitation
Healthcare Analytics