Comprehensive Review of Modern Health Monitoring Technologies and Digital Healthcare Services
Abstract
The rapid evolution of digital healthcare systems has transformed traditional patient monitoring into intelligent, data-driven, and interconnected health ecosystems. This review critically examines modern health monitoring technologies and digital healthcare services with a focus on Internet of Things (IoT), wireless body area networks (WBAN), cloud–fog architectures, wearable sensing systems, and machine learning-based diagnostic frameworks. The study synthesizes existing literature to identify technological advancements, architectural models, and real-world applications in remote patient monitoring, elderly care, and chronic disease management. Particular attention is given to hybrid sensing infrastructures and their role in enabling continuous physiological tracking, as demonstrated in RFID–WSN integrated environments (Adame et al., 2018). The review further explores how machine learning and decentralized systems enhance predictive analytics, early diagnosis, and healthcare service delivery efficiency. Key findings reveal that while health monitoring technologies significantly improve accessibility and responsiveness of healthcare systems, challenges remain in data security, interoperability, energy efficiency, and clinical adoption. The study concludes that future healthcare systems will rely on integrated, scalable, and intelligent platforms combining edge computing, AI-driven analytics, and wearable sensor networks to achieve fully autonomous health monitoring ecosystems.
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