The integration of embedded AI and real-time sensor fusion in healthcare offers a critical advancement in addressing elderly fall-related injuries. This paper presents SAFEGUARD, an Embedded AI-Driven fall protection system designed to bridge the gap between fall detection and active physical protection. Unlike conventional systems that mainly focus on post-fall alerting, SAFEGUARD verifies fall events through a two-stage process before initiating a protective response. The IMU first identifies a potential fall based on acceleration and angular velocity, followed by posture verification from camera frames using the MoveNet model. Once a fall is confirmed, a servo-based puncture mechanism is used to release CO2 for airbag deployment. At the same time, a GSM module sends an emergency notification to the caregiver. The individual modules were experimentally tested to verify their operation and support their future integration into a complete wearable fall protection system.