IoB Interface



IoB Interface aims to widen brain-machine interface (BMI) technology by developing technologies to extract thinking and mental states from brain activities through various devices and using them in societal applications.

Specifically, we will develop algorithms able to pull out everyday thoughts and mental states in near real-time by combining brain wave sensors (gadgets like headphones, earphones, etc.) and video from mobile phones.

Using these technologies, we aim to promote BMI technology in society by developing applications that will enable self-regulation by visualizing our day-to-day subconscious physical changes. Moreover, we will create applications to enable communications between users, and facilitate communication for those with difficulty expressing themselves.


  • USHIBA Junichi,Ph.D.

    Faculty of Science and Technology, Keio University

    In this R&D project, we will develop scalp-electroencephalogram-based brain-computer interface (BCI) technology for everyday use. A large-scale field study will be conducted with the healthcare, sports, music and research industries. We will consider the social implications of AI-aided non-surgical BCI and its application to “Cybernetic Avatars”, using evidence-based research and ethical guidelines.

  • FURUYA Shinichi,Ph.D.

    Senior Researcher (Senior Program Manager)
    Sony Computer Science Laboratories Inc. 

    In this research project, our group aims to develop and deploy a novel system enabling physical/mental conditioning of musicians who suffer from neurological disorders associated with over-training and are around the gray zone (i.e., “dynamic stereotype”). This project aims at enhancing the quality of life of the musicians, not only through forecasting fluctuation of the condition (e.g., slump and fatigue), but also through recommending appropriate conditioning, based on fusing novel mobile-sensing systems and AI technologies. Moreover, fundamental technologies derived from our research will be used for developing novel injury-prevention systems for healthy musicians, toward a goal of establishing a cultural society considering the safety and wellbeing of artists.

  • WATANABE Katsumi,Ph.D.

    School of Fundamental Science and Engineering, Waseda University

    In this study, we will investigate decoding mind-body status from explicit and implicit ambient surface information (IASI), and effective applications of IASI. Particularly, we will research the limitations and effectiveness of IASI in mind-body decoding and aim at improving IoB interfaces by combining them with the decoding of neural signals. Also, we will explore practical usage of IoB interfaces, and effective feedback methods in everyday life, by collaborating with people in the healthcare field. We plan to propose intellectual and social foundations for the augmentations of perceptual, cognitive, and physical capabilities of people from various social and ethical backgrounds, with consideration of individual differences and diversity.

  • NAKAZAWA Kimitaka,Ph.D.

    Department of Life Sciences, The University of Tokyo

    In this study we aim to develop new systems to decode mind-body status from explicit and implicit ambient surface information (IASI) in our daily life. We will carry out both laboratory-based experiments and field studies simultaneously to approach this goal. Specifically, we will try to develop systems decoding mind-body status from posture and gait IASI. To this end we will conduct both fundamental studies using neurophysiological experiments, as well as more practical field studies.

  • KOIZUMI Ai,Ph.D.

    Associate Researcher (Project Leader)
    Sony Computer Science Laboratories, Inc. 

    In this research project, we aim to develop basic technologies to monitor and predict the maladaptive mental states of humans from their ambient surface information, and to guide them into better mental states through visualization and feedback of the processed information. Various mental disorders are characterized by their bodily symptoms, in addition to their mental symptoms. By developing technologies to objectively and constantly monitor the signals of mental issues hidden in ambient surface information, including bodily information, along with neuroimaging techniques, we aim to improve the mental health care system in society.