Using information, systems and control engineering and advanced information technology, students will engage in research related to development of biosystem modeling, state estimation and simulation techniques along with development of technology to optimally control artificial organs, rehabilitation equipment, healthcare equipment and other medical systems as well as technology to achieve high-performance human interfaces.
Cybermedicine and Biocybernetics
Promoting healthy society using medical cybernetics
Elucidation of biological functions based on cybernetics and systems theory is essential to development of new therapeutic devices and biomedical control methods. By use of information technology, computer sciences, system engineering and control engineering, the Division of Cybermedicine and Biocybernetics studies modeling, state estimation and simulation techniques for biological systems, and also aims at development of not only optimal control technologies for artificial organs, rehabilitation devices and healthcare systems but also high-performance human interface systems.
- Internet of things (IoT) for health maintenance and estimation algorithm of physical condition
- Control and monitoring systems for in vivo medical devices
- Assessment of biological effects of digital image contents
- Virtual reality systems for rehabilitation
Tele-healthcare system based on correlation analysis of multi-dimensional biosignals obtained from distributed sensors
Tele-medical system using the Electronic Doctor's Bag
Intelligent Biomedical Systems Engineering
Imaging Neurophysiology and Intelligent Computer-aided Diagnosis and Therapy
By using multi-modal imaging techniques, we aim to accurately visualize wide range of biomedical phenomena such as microscopic neuronal activities as well as macroscopic whole brain functions. The images can then be utilized for not only extracting useful biomedical information, but also revealing mechanisms of neural information processing. We also build computational models of neural information processing inspired by highly intellectual cognition skills of human specialists, such as medical image diagnosis by radiologists. Based on the models and some machine learning techniques, we develop intelligent computer-aided systems for medical image diagnosis, interventional radiology, and image-guided therapy.Laboratory site
Multi-cellular imaging (left) and whole brain imaging (middle) for revealing brain functions and novel intelligent imaging techniques (right: tumor extraction from x-ray fluoroscopy) for diagnosis and therapy.