Researchers in Korea have developed a 'smart patch' that can precisely measure changes in the body using only sweat. It is expected to greatly contribute to chronic disease management and the advancement of personalized healthcare technology.
A research team led by Professor Jeong Gi-hoon from the Korea Advanced Institute of Science and Technology (KAIST) announced on the 7th that they have developed a wearable sensor capable of simultaneously analyzing various metabolites in sweat in real-time. The results of this research were published in the international journal 'Nature Communications' on Aug. 27.
Recently, research on wearable sensors that analyze sweat metabolites to monitor precise physiological states of the human body has been actively conducted. However, the existing methods involving fluorescent labeling or staining have limitations in effectively collecting and controlling sweat, making it difficult to accurately observe changes in metabolites over time in the human body.
To overcome these limitations, the researchers developed a thin and flexible wearable sweat patch that adheres directly to the skin. This patch is equipped with a microscale 'nanoplasmonic structure' that collects sweat and precisely analyzes its components using fine channels and light. The nanoplasmonic structure is an optical sensor designed with metal patterns of nanometer (nm, one billionth of a meter) size that interact with light to enable the high sensitivity detection of the presence or concentration changes of specific molecules.
In addition, a 'microfluidic technology' was integrated to precisely control the movement of sweat components in channels thinner than human hair. The structure allows for the sequential filling of the sweat produced during exercise into the internal storage space (chamber) of the patch.
The research team successfully applied the developed patch to actual individuals, continuously tracking changes in the components of sweat over time during exercise. While the existing methods could only check about two components at the same time, this study analyzed how important metabolites related to metabolism, exercise, and diseases, such as uric acid, lactate, and tyrosine, changed according to exercise and diet.
In particular, the research team succeeded in accurately isolating the signals of desired metabolites from the complex components mixed in sweat by applying artificial intelligence (AI) analysis techniques. This can help identify not only changes in endurance and muscle mass during activities such as running, marathons, and workouts, but also potential risks such as gout, liver dysfunction, and kidney diseases through numeric changes.
Professor Jeong Gi-hoon noted, "This research has laid the foundation for precisely monitoring metabolic changes in the body over time using only a sweat patch without blood collection. This enables not only routine health monitoring but also the detection of muscle changes and diseases in individuals who enjoy exercising. In the future, it is expected to expand into various fields such as chronic disease management, tracking drug responses, monitoring environmental exposure, and discovering next-generation biomarkers for metabolic diseases."
References
Nature Communications (2025), DOI: https://doi.org/10.1038/s41467-025-63510-2