Biomedical 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.

Intelligent Biomedical Systems Engineering

Imaging Neurophysiology and Intelligent Computer-aided Diagnosis and Therapy

  • Professor Noriyasu Homma Professor
    Noriyasu Homma

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.

  • 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
  • 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