Announcements

2023.01.10 beta version of webpage released
Lab introduction

In order to move closer to a human-friendly society, we conduct research using a wide range of simulations in the fields of bioengineering and agricultural engineering. For example, we use physical simulations of cells to understand the mechanical factors of disease, aiming to expand our knowledge by visualizing invisible phenomena. We also aim to reduce labor by analyzing and simulating data acquired on farms to support the agricultural sector, where the population is aging.

Keywords

simulation, biomechanics, computational fluid dynamics, digital twins

Research topics

Computational Biomechanics

We visualize cell behavior that cannot be computed experimentally using numerical simulations. Focusing on cells in blood, we use computational methods of computational fluid dynamics to solve the behavior of cells. The aim is to elucidate the biological and physical mechanisms in healthy and abnormal conditions, and to help in the development of future therapies.

  • Simulation of red blood cells during rupture
  • Simulation of molecules flowing around a red blood cell
  • Simulation of blood cells flowing near the wall

    • Human sensing and prediction

    We predict human behavior and internal states from limited information using deep learning and other computational methods. The objective of this project is to develop an index for objectively classifying human behavior and internal states, and to improve social functions.

  • Fatigue estimation using combined sensing
  • Detection of smartphone use while walking using deep learning

    • Agri-informatics

    Using various computational methods such as simulation, visualization techniques, and deep learning, we develop a digital twin of virtual space connected to the real world to support farmers. The aim is to reduce the burden of agricultural tasks and to facilitate adaptation to climate change.

  • 3D apple tree detection in a digital twin
  • Detection of apple trees in an orchard using deep learning
    • Past thesis topics

    Currently under preparation.

    CV

    Our research achievements can be referenced through the link below.

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    Members
    Stephanie Nix, Lecture
    Ph.D. in biomedical engineering

    Students

    currentry recruiting

    Collaborators

    Dr.Hirokazu Madokoro, Iwate Prefectural University,
    Faculty of Software and Information science
    Dr.Satoshi Yamamoto, Akita Prefectural University,
    Faculty of Bioresource Science

    Classes

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