Advancements in biosensor-integrated biomedical devices for early detection of metabolic disorders: a comprehensive review.
Abstract
Lifestyle, genetic, and environmental influences are implicated in metabolic disorders, an emerging global health concern, including diabetes mellitus, dyslipidaemia, obesity, and hyperuricemia. The success of disease treatment and the prevention of long-term complications depend on the early identification and ongoing monitoring of metabolic markers. Even though these are accurate, traditional approaches for diagnosis are invasive, labor-intensive, and not amenable to real-time monitoring. By enabling the rapid, sensitive, and minimally invasive detection of biomarkers such as glucose, insulin, lipids, and uric acid, recent developments in biosensor-integrated biomedical technology have revolutionized metabolic diagnostics. This review provides a comprehensive overview of the various forms of biosensors, including electrochemical, optical, piezoelectric, and nanobiosensors, and their classification, mechanisms, and detection principles. High-performance materials such as graphene, carbon nanotubes, and metallic nanoparticles have been incorporated to significantly enhance biosensor performance, and microfluidic lab-on-a-chip systems have facilitated the convenience of collecting non-invasive samples of interstitial fluid, perspiration, or saliva. To ensure the analytical precision and clinical reliability of biosensor responses, validation methods based on bioinformatics and High-Performance Liquid Chromatography (HPLC) are highlighted. In addition, continuous monitoring, predictive medicine, and tailored healthcare management have been enabled by the incorporation of artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) in wearable and intelligent biomedical devices. Widespread clinical translation is hindered by challenges like sensor drift, biofouling, calibration variability, and regulatory constraints, although tremendous progress has been achieved. Future biosensor technology will be developed towards anticipatory, patient-focused, precision-based management of metabolic disorders by synergistic implementation of nanotechnology, AI-enabled analytics, and telemedicine.
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