CHANGCHUN -- A research team led by Zhang Qiang with the Changchun Institute of Applied Chemistry under the Chinese Academy of Sciences has successfully developed a fully integrated wearable sweat sensing patch for online analysis of multiple Parkinson's disease-related biomarkers.

The research was published on Tuesday (Beijing time) in the international journal "Advanced Materials." According to this study, the system enables real-time detection of biomarkers in sweat, allowing non-invasive, dynamic tracking of the disease's progression. This offers new possibilities for early intervention during the "golden window" of treatment for Parkinson's patients.

Parkinson's disease is a progressive neurodegenerative disorder that is difficult to find in its early stages. Symptoms such as tremors and slowed movement may not appear until many years after the initial degeneration of neurons. With no current cure, patients primarily rely on long-term medication to manage the condition. Therefore, early diagnosis and prediction play an incredibly important role in Parkinson's disease treatment.

"It's only the size of a band-aid, but it contains a 'miniature detector' developed by ourselves," Zhang said.

Zhang's team spent nearly three years developing the wearable system. The Parkinson-related biomarkers in sweat, such as L-Dopa, ascorbic acid, and glucose, can be monitored by the sensing system in a wearable manner. Parkinson's patients do not need to draw blood or receive injections.

The system integrates a biomimetic microfluidic module for sedentary sweat collection, an advanced electrochemical sensing platform for biomarker detection, on-site signal processing circuitry for data handling, and custom software for real-time data visualization.

"It's like installing a translator for the body, converting biological signals in sweat into user-friendly information that patients can understand," Zhang said.

Compared to traditional invasive testing, the flexible sensor patch overcomes multiple technical challenges. For instance, its self-driven sweat collection chip ensures stable sampling even during physical activity, and its flexible sensing electrodes allow simultaneous assessment of multiple biomarkers. The data processing module wirelessly emits sensing data and displays monitoring results in a real-time. "It's as easy to use as wearing a watch," he added.

"We hope that in the future, people at high risk for Parkinson's will be able to access this health monitoring system," Zhang said. "It will provide key technological support for early diagnosis and prediction of Parkinson's disease."