MICRO / NANO SENSING
Bringing the real world
into sharper focus
with nano-tactile technology.
The subtle differences we feel.
We reveal the information behind them with semiconductors, sensors, and AI.
Professor, Faculty of Engineering and Design, Kagawa University
Director, Nano-Micro Structure Device Integrated Research Center
HIDEKUNI TAKAO
From the sense of touch to new possibilities.
RESEARCH
Fabrics can look alike yet feel different.
That sensation carries information about fine surface features, friction, hardness, heat transfer, and more.
We develop small sensors inspired by the fingertip to turn sensation into information we can measure and verify.
Nano-tactile sensing
We measure several components of texture, including fine surface features, friction, hardness, and heat transfer. Contact structures inspired by the fingertip and microscale sensing elements turn surface properties and their variation into quantitative data.
Semiconductor and MEMS integration
MEMS combines microscopic mechanical structures with electronic functions. We use semiconductor microfabrication to integrate contact structures, springs, and sensing circuits, pursuing both sensitivity to small forces and displacements and the spatial resolution needed to distinguish fine surface features.
Tactile sensing and AI · Medicine
Our medical-engineering collaborations include the development of pressure and tactile sensors for endoscopes. Alongside our work on AI analysis of tactile data, we aim to develop approaches for assessing conditions and supporting decisions in medical devices and advanced manufacturing processes.
Micro and nano sensors / Semiconductors and MEMS / Tactile sensing / AI / Medicine and engineering collaboration
Research Focus | Touch × AI
We combine nano-tactile sensors with AI to interpret fine surface features, friction, hardness, and heat transfer. Our research seeks to understand the condition of a target and how that condition changes.
In experiments distinguishing 14 types of tissue paper, our sensing system achieved a classification accuracy of at least 95%. This technology received the Grand Prix in the Devices Category of CEATEC AWARD 2023. Our collaboration with Panasonic has also led to the practical use of a hair cuticle diagnostic system combining nano-tactile sensors and deep learning.
For medical applications, we have developed a sensor that passes through an endoscope’s narrow tool channel to measure texture and force simultaneously. We are pursuing research that captures subtle changes during contact and turns them into information to support physicians’ judgment.
For advanced manufacturing applications, we aim to detect changes in fine surface features and frictional properties, with a view to quality assessment and early anomaly detection. By connecting semiconductor and MEMS device design, signal analysis, and AI-based condition estimation, we seek to make tactile measurements useful for improving processes and technologies.
SELECTED HIGHLIGHTS
Together with Panasonic, we developed a hair cuticle diagnostic system using nano-tactile sensors. Information obtained by touching the hair surface helps us assess hair condition.
Research highlights from Kagawa University (external website, opens in a new tab)Research from the JST-CREST project won the Grand Prix in the Devices Category of the CEATEC AWARD 2023. The award recognized the application potential of visualizing tactile sensations and combining them with AI.
Award-winning technology (Kagawa University) (external website, opens in a new tab)LABORATORY VIDEO
Watch our video to discover the laboratory’s work.
Watch the video YouTube (opens in a new tab)
