Current Projects

  • Project Name: Development and Clinical Application of Personalised IoT System to Control the Risk of Mental and Physical Disorders of Workers.
  • Supporter: Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (Acceptance Rate: 24.3%).
  • Run Time: 01.04.2020 – 31.03.2023.
  • Role: Main Participant.
  • Partners: The University of Tokyo, Fujita Health University, Nagoya City University.
  • Abstract: The purpose of this study is to predict and control the risk of mental and physical disorders of workers by leveraging the power of artificial intelligence and IoT.
  • Project Name: Deep Learning for Intensive Longitudinal Biomedical Signals and its Health Related AI Applications.
  • Supporter: Japan Society for the Promotion of Science (JSPS), Japan (Acceptance Rate: 10.6%).
  • Run Time: 30.09.2019 – 29.09.2021.
  • Role: Author of Proposal, Principal Investigator, Grant Holder.
  • Partners: The University of Tokyo, Imperial College London, Osaka University, Carnegie Mellon University, University of Augsburg, Shizuoka University.
  • Abstract: This research aims to leverage the power of A.I. for analysing and monitoring the daily behaviour of the patients suffering from psychiatric diseases via the biomedical intensive longitudinal data. We will investigate the state-of-the-art techniques of machine learning, deep learning, and signal processing for their capacity on screening the patients from the healthy control. In addition, we will explore the feasibility to use the paradigm of A.I. to implement an automatic monitoring and evaluation system for subject’s health status by IoT sensor data. The achievements of this research can facilitate the development of smart wearables for building a human-centered A.I. world with a plenty of applications on healthcare and wellbeing.
  • Project Name: Development of Just-in-Time Adaptive Intervention for Behavioural Modification based on Continuous Psycho-behavioural Monitoring under Daily Life.
  • Supporter: Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (Acceptance Rate: 24.8%).
  • Run Time: 01.04.2017 – 31.03.2020.
  • Role: Main Participant.
  • Partners: The University of Tokyo, Fujita Health University, Nagoya City University.
  • Abstract: The purpose of this study is to develop a risk detection type intervention guidance method that conducts behavioural change intervention in Just-in-Time, and to verify its clinical applicability.