Professor Lee Seong-whan’s team publishes paper in Science Advances
World’s first homeostatic biosensor that imitates leaf epidermis

Professor Lee Seong-whan of the Department of Artificial Intelligence and doctoral student Kim Ji-yong published a paper in the leading scientific journal Science Advances on April 16.

* Title of paper: Leaf-inspired homeostatic cellulose biosensors

In the paper titled “Leaf-inspired homeostatic cellulose biosensors,” the team developed a homeostatic biosensor that provides stable measurements of electrophysiological signals by imitating the leaf homeostasis system responsible for preserving leaf inner water content and thereby maintaining a stable skin-biosensor interface. Homeostasis is the tendency of living systems to maintain a steady internal environment despite environmental changes.

The current biosensor technology used to measure electrophysiological signals is unable to provide stable measurements long-term as it does not consider skin homeostasis, including the secretion of sweat and other substances. The proposed homeostatic biosensor imitates the leaf homeostasis system, which adjusts water content inside the plant by regulating stomata during floods and droughts. Unlike existing homeostatic sensors that rely on complex synthesis techniques, the proposed sensor uses a mesoporous cellulose membrane, which was identified by the team as a new homeostatic material based on an analysis of electrical, chemical, and mechanical changes during the absorption of saline solution. The homeostatic biosensor accommodates skin changes and maintains the electrical interface through self-regulation via the diffusion gradient between the skin and sensor surface.

Professor Lee Seong-whan, the corresponding author, said, “The skin plays a key role in homeostasis, protecting the body from viruses and contaminants, and maintaining body temperature and moisture in response to changes in the environment. Our team developed a new interface technology that allows the stable long-term measurement of electrophysiological signals based on an in-depth understanding of skin from a dermatological perspective.” He added, “Noninvasive biosensor technology has developed at a rapid pace, but does not consider skin homeostasis. When such devices are attached to the skin over long periods, problems, such as measurement unreliability and allergic reactions, can develop. Our findings present new opportunities for biosensor technology. Of course, further research and experimentation are needed, but we have laid the foundation for the reliable measurement of biosignals while ensuring outstanding biocompatibility.” The combination of homeostatic biosensors and brain-computer interfacing is expected to open new doors for applications that utilize biosignals.

The study was supported as part of the Development of BCI-based Brain and Cognitive Computing Technology for Recognizing User’s Intentions using Deep Learning, and the Artificial Intelligence Graduate School Program by the Ministry of Science and ICT.