This research paper introduces an innovative solution to the prevalent challenge of limited user-prosthetic limb connection in current technologies. While traditional prosthetic limbs effectively restore basic functionality, they often lack a nuanced and intuitive link between the user and the artificial limb. Our proposed system pioneers a bidirectional communication channel between the user's nervous system and the prosthetic limb, harnessing state-of-the-art technologies like brain-machine interfaces and nerve interfaces. This integration aims to recreate a natural sense of touch, temperature, and proprioception within the prosthetic limb, effectively closing the existing gap. Employing adaptive machine learning algorithms, the system tailors itself to individual user‘s unique neural patterns over time, ensuring a highly personalized and user-friendly prosthetic experience. Encouraging preliminary results showcase a significant enhancement in sensory feedback and motor control, heralding the potential for a remarkably natural and immersive interaction with prosthetic limbs. In summary, this research contributes a groundbreaking neural interface approach, effectively overcoming the limitations of current prosthetic technologies and providing a more intuitive, responsive, and personalized prosthetic experience for individuals with limb loss.