Wearable Health Monitoring System Using Embedded Sensors and Edge Computing

The demand for real-time, continuous health monitoring has increased with a growing interest in preventive health care and chronic disease management. Wearable health monitoring systems are emerging as potentially effective solutions to address these demands, as these systems use embedded sensors together with edge computing as health monitoring “on-body” diagnostics. This paper provides a thorough examination of a wearable health monitoring system with embedded sensors for data collection and edge computing for on-site analysis, improving latency, privacy and energy savings. The proposed health monitoring system is capable of monitoring critical signs, such as heart rate, temperature, bloodoxygen saturation, and motion characteristics through a lightweight, low-power embedded system. With edge computing, this system reduces reliance and usage of cloud infrastructure by doing data filtering, anomaly detection, and pre-processing onsite which allows for more immediate medical interventions. In addition, the study identifies current technology gaps, presents an optimized framework, and evaluates system performance based on simulation and real-time evaluations. The results demonstrate faster response time, better energy usage, and trustworthy health data accuracy. The wearable system can play an important role in remote health care, particularly for older adults in care, fitness tracking, and chronic disease management, thus improving healthcare access and patient outcomes.

Перевод пока недоступен