A Study on Wireless Sensor Networks in Healthcare and Biomedical Applications

Abstract

Wireless Sensor Networks (WSNs) have emerged as a transformative technology in healthcare and biomedical applications, enabling real-time monitoring, remote supervision, and data-driven decision-making. Comprising low-power, autonomous sensor nodes, WSNs collect physiological data such as heart rate, blood pressure, glucose levels, and ECG/EEG signals, supporting applications like remote patient monitoring, smart hospitals, wearable health devices, telemedicine, and chronic disease management. This study explores the architecture, communication protocols, energy-efficient routing, and security/privacy considerations in healthcare WSNs. The integration of WSNs with IoT, cloud computing, and AI-based analytics enhances system scalability, intelligence, and patient-centered care. Despite their potential, challenges remain in energy efficiency, reliability, latency, and data security, which are critical for safe deployment in real-world environments. This research highlights the opportunities, current limitations, and future directions of healthcare WSNs, emphasizing their role in improving healthcare accessibility, efficiency, and patient outcomes.