摘要
Edge computing has emerged as a key enabler of next-generation healthcare by supporting low-latency data processing, intelligent decision-making, and secure management of medical data at the point of care. The integration of the Internet of Medical Things (IoMT), artificial intelligence (AI), wearable biosensors, and fifth-generation (5G) communication has accelerated the development of edge-enabled healthcare systems for continuous patient monitoring, remote diagnostics, and personalized treatment. This review presents an overview of edge computing in healthcare, highlighting its architecture, role in intelligent medical devices, and integration with AI-driven clinical applications. Recent advances in wearable electrocardiogram systems, continuous glucose monitoring devices, smart insulin pumps, digital stethoscopes, portable ultrasound systems, and wearable biosensors are discussed. The review also summarizes the application of edge computing in precision medicine, intelligent drug delivery, medication adherence, and decentralized healthcare services. Finally, current challenges related to interoperability, cybersecurity, resource constraints, and regulatory compliance are outlined, together with emerging research directions including Edge AI, federated learning, digital twins, and sixth-generation (6G) communication. Overall, edge computing provides a scalable and patient-centric framework for intelligent healthcare, supporting improved clinical outcomes and future digital health ecosystems.