Smart Healthcare Monitoring and Patient Tracking Using Neural Wireless Systems

Abstract

The rapid advancement of wireless communication technologies and artificial intelligence has significantly transformed modern healthcare systems. Smart healthcare monitoring and patient tracking have emerged as critical components in improving patient safety, enhancing healthcare service delivery, and enabling real-time medical interventions. Traditional healthcare monitoring systems often face challenges related to limited coverage, inaccurate localization, delayed emergency response, and inefficient utilization of healthcare resources. To address these limitations, this study proposes a Smart Healthcare Monitoring and Patient Tracking Framework using Neural Wireless Systems (SHMPT-NWS), integrating wireless sensing technologies with deep neural intelligence for continuous patient monitoring and accurate indoor localization. The proposed framework employs wireless communication infrastructures such as Wi-Fi, Bluetooth Low Energy (BLE), wearable sensors, and Internet of Medical Things (IoMT) devices to collect real-time physiological and location-based information. Advanced neural learning mechanisms are utilized to extract meaningful features from heterogeneous sensor data and generate intelligent predictions regarding patient location, movement patterns, and health status. An adaptive feature fusion mechanism combines physiological measurements with wireless signal characteristics to enhance localization precision and monitoring reliability. Experimental evaluations demonstrate that the proposed SHMPT-NWS framework significantly improves tracking accuracy, patient activity recognition, monitoring efficiency, and emergency detection performance compared to conventional machine learning and wireless monitoring approaches. The neural wireless architecture effectively reduces localization errors, improves response times, and supports continuous healthcare supervision in assisted living environments, hospitals, and smart healthcare facilities.