Multimodal biosensing platforms for sensor-computing integration towards intelligent healthcare

Abstract

Integrated multimodal biosensing platforms are transforming the landscape of bioanalytical technologies by enabling real-time, high-resolution, and multifunctional detection of physiological and environmental biomarkers. This review summarizes the evolution from traditional single-modal biosensors to advanced multimodal systems that unify diverse sensing modalities with computation and storage functionalities. The introduction on the transduction mechanisms of different biosensors and the representative biomarkers was first provided, highlighting the advantages of multimodal sensing with enhanced sensitivity, specificity, and robustness. The advances in fabrication techniques were then discussed, with particular emphasis on printable strategies that facilitate heterogeneous material integration and micro/nanoscale patterning. Moreover, artificial intelligence-driven data processing for on-device decision-making was discussed. Representative applications were then presented in healthcare monitoring, environment detection, and food safety tracking. Finally, current challenges related to material compatibility, data heterogeneity, device scalability, and regulatory barriers were proposed with possible strategies toward fully autonomous and intelligent biosensing systems.

Keywords

Flexible electronics / multimodal biosensors / integrated systems / artificial intelligence / sensor-computing integration

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