Multimodal magnetic modulation QCM for motion-based detection of biomolecule concentration and base liquid viscosity

Accurate and synchronized assessment of biochemical parameters, such as biomarker concentration and body fluid viscosity, is crucial for advancing early disease detection and health management. Conventional biomolecular multiparameter detection methods often rely on multiple sensors or analytical techniques, which introduce cross-talk between sensing modalities, data inconsistencies, and complex calibration requirements, ultimately compromising detection precision and adaptability. We propose a streamlined detection approach that leverages a single uncoated Quartz Crystal Microbalance (QCM) sensor to monitor the dynamic magnetized motion of biomolecules under multimodal magnetic field modulation. Unlike conventional QCM methods that rely on static mass loading effects, this approach enables the sensor to capture motion signals that encode information about biomolecule concentration and base liquid viscosity. A backpropagation (BP) neural network is employed to model the nonlinear coupling between these motion-derived signal characteristics and the target biochemical parameters. The proposed method is validated using prostate-specific antigen (PSA) as a biomolecular model analyte. Experimental results from blind tests, where both concentration and viscosity were simultaneously unknown, demonstrate a prediction accuracy of 90 % for concentrations ranging from 0.01 to 1000 ng/mL and 87 % for viscosities between 1 and 6 cP. By integrating multimodal magnetic modulation with QCM-based motion sensing and machine learning, the BP-MMM-QCM technique provides a versatile and high-precision solution for biomolecule analysis. Accurate detection of biomolecule concentrations is essential for early disease diagnosis as well as monitoring disease progression and therapeutic responses. This approach overcomes the limitations of conventional QCM methods and enables real-time, multi-parameter detection in a single assay, making it a promising tool for disease diagnostics and health monitoring applications.