Field introduction´╝ÜBiomedical System Control Engineering

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

Professor Makoto Yoshizawa Professor
Makoto Yoshizawa

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.

  1. Internet of things (IoT) for health maintenance and estimation algorithm of physical condition
  2. Control and monitoring systems for in vivo medical devices
  3. Assessment of biological effects of digital image contents
  4. Virtual reality systems for rehabilitation
Laboratory site
Tele-healthcare system based on correlation analysis of multi-dimensional biosignals obtained from distributed sensors

Tele-healthcare system based on correlation analysis of multi-dimensional biosignals obtained from distributed sensors

Tele-medical system using the Electronic Doctor's Bag

Tele-medical system using the Electronic Doctor's Bag

Intelligent Biomedical Systems Engineering

Imaging Neurophysiology and Intelligent Computer-aided Diagnosis and Therapy

Professor Noriyasu Homma Professor
Noriyasu Homma
Associate Professor Noriyasu Homma Associate Professor
Makoto Osanai

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.

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.

Neuro-Robotics

Robotics for Neuroscience, Neuroscience for Robotics

Professor Mitsuhiro Hayashibe Professor
Mitsuhiro Hayashibe

Recently, the current era is referred as a century of robotics and AI. However, robot capability in real life is still rather limited then there are still a lot of things we need to deeply learn from advanced and robust motor control and sensory functions which humans have, for next step forward. Robotics is also useful as computational tool to understand human motor learning mechanism. Neuroscience knowledge can be useful to improve robot capability.
We study on neuroscience for robotics and robotics for neuroscience as [Neuro-Robotics].

  1. Study of human motor control, adaptive learning mechanism
  2. Modeling and identifying biological signals and functions
  3. Study on redundant joint control and biological motor learning of vertebrates
  4. Development of robot technology to Neuro-Rehabilitation
Laboratory site
NIRS-EEG joint imaging during transcranial direct current stimulation

NIRS-EEG joint imaging during transcranial direct current stimulation

Muscle volumetric modeling for function, physiology and deformation

Muscle volumetric modeling for function, physiology and deformation

Balance estimation independent from foot pressure measurement

Balance estimation independent from foot pressure measurement