Recently, ETH Zurich published a research paper titled “A Wearable In-Pad Diagnostic for the Detection of Disease Biomarkers in Menstruation Blood.” The study developed a fully integrated, wearable microfluidic monitoring platform (MenstruAI) embedded within sanitary pads, enabling detection of disease biomarkers in menstrual blood without requiring external electronic devices. Two key innovations include: direct detection of undiluted menstrual blood; and a unique fluid control mechanism ensuring precise blood volume for testing while preventing overflow, thereby guaranteeing result validity.
MenstruAI enables semi-quantitative detection of gynecological tumor markers such as C-reactive protein (CRP), carcinoembryonic antigen (CEA), cancer antigen 125 (CA-125), and endometriosis marker CA-125. Biomarker-induced color changes can be interpreted visually or analyzed semi-quantitatively via a smartphone application powered by machine learning algorithms.
The MenstruAI platform also offers significant cost advantages: a single 6mm LFA test strip costs less than $0.40, with soft silicone packaging adding approximately $0.50. The total per-use cost for the entire platform is about $1, demonstrating strong potential for scaling. However, realizing its full public health value requires large-scale population studies to address challenges like high menstrual blood variability and uncertain sampling conditions.
It is important to emphasize that the MenstruAI platform does not currently replace clinical diagnosis. Instead, it serves as a convenient early warning and high-frequency monitoring tool, enabling users to promptly identify potential health risks. In the future, the biomarker detection panel can be expanded based on user needs and disease prevalence trends, potentially covering additional health indicators such as sexually transmitted diseases (STDs). This menstrual blood-based multi-detection platform holds promise to advance self-health management among women globally, particularly in developing countries, through non-invasive, low-cost, and accessible health monitoring.
