Enhancing Healthcare Monitoring through Wearable Computing and Massive MIMO Technology in 5G IoT Networks

The growing need for continuous, real-time monitoring of vital physiological parameters like heart rate and blood pressure is driven by the demand for enhanced healthcare, particularly in remote or critical scenarios. Traditional healthcare systems often struggle with delays, inaccuracies, and high costs, making timely medical interventions more challenging. This study aims to design and implement a portable health monitoring system that use widely available technology and advanced wireless communication to address these issues effectively. The system integrates various sensors to track key physiological metrics and applies biomedical signal acquisition along with pre-processing and feature extraction techniques to reduce noise and improve signal quality. Wireless transmission enables real-time data transfer, supporting remote monitoring and analysis. To enhance communication efficiency, the system incorporates Massive Multiple-Input Multiple-Output (MIMO) technology within 5G Internet of Things (IoT) networks, ensuring higher data transfer speeds, reduced latency, and reliable connectivity. The findings demonstrate notable improvements in signal clarity and data transmission, reflected in a significant boost in Signal-to-Noise Ratio (SNR) and a reduction in Bit Error Rate (BER), underscoring the system’s effectiveness. By integrating 5G Massive MIMO technology, the performance of Wireless Body Area Networks (WBANs) is substantially improved, leading to more efficient patient monitoring.