A Secure IoT Framework for Sleep Apnea Detection and Analysis

This work presents the development of a secure Internet of Things (IoT)-based system for sleep Apnea analysis, emphasizing real-time physiological monitoring, accurate diagnosis, and robust measures for data security and privacy. Sleep Apnea, a disorder characterized by breathing interruptions during sleep, can lead to serious health conditions such as cardiovascular issues, cognitive impairment, and fatigue. The proposed system integrates patient data collection, encryption, transmission, and monitoring, with a key emphasis on advanced encryption techniques to safeguard sensitive health data. Heart Rate Variability (HRV) metrics are extracted and encrypted using Advanced Encryption Standard (AES) and custom lightweight AES models, optimizing system performance for IoT applications. The encrypted data are then transmitted to a cloud-based server for analysis. This approach provides a secure, efficient, and lowcost solution for remote patient monitoring in healthcare IoT systems, addressing critical security concerns.