The integration of Internet of Things in healthcare has revolutionized patient monitoring, offering real-time insights and personalized care. However, ensuring the security and privacy of sensitive patient data, across different contexts, remains a challenge. This paper presents an Adaptive Security Framework for IoT-based patient monitoring systems, leveraging Edge AI to dynamically adjust security levels based on contextual factors such as patient location, communication channels, and internet connectivity. The framework addresses diverse threats through a weighted decision-making algorithm, enhancing data protection while maintaining high-quality healthcare services. Also, ethical considerations, including transparency and patient consent, are discussed. This research advances secure and efficient IoT applications in healthcare, paving the way for patient-centric innovations.