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Non-invasive biochemical sensing with AI-driven analytics: a comprehensive review of technologies, applications, and
1Department of Biomedical Engineering, KIT-Kalaignarkarunanidhi Institute of Technology, Coimbatore, India. umapathi.uit@gmail.com.
Abstract:
Artificial Intelligence (AI) combined with non-invasive biochemical sensing is transforming healthcare monitoring and diagnostics. This review explores the scope of smart sensing systems, highlighting their core components, enabling technologies, design challenges, and potential solutions. It examines key biofluids and their analytes to understand suitable sensing modalities and the adaptations required for different biological environments. The review also discusses methods for functionalizing biosensors to achieve higher sensitivity, improving data analytics, and ensuring data security and system robustness. Beyond technical aspects, it emphasizes the importance of regulatory standards and examines the current status of developments in wearable biochemical sensing devices and the market forces driving their growth. Looking ahead, it highlights the future of biochemical sensing applications where advanced technologies such as quantum sensing, transformer models, and neuro-symbolic AI could significantly enhance performance. With this comprehensive analysis, the review aims to guide researchers, clinicians, and industry professionals in understanding both the present landscape and the future directions of AI-driven, non-invasive biochemical sensing systems.

