Active Prosthesis

Active prostheses aim to restore lost limb function through powered, controlled movement, addressing the limitations of passive devices and improving amputee quality of life. Current research focuses on developing more intuitive control systems, often employing machine learning models like recurrent neural networks and feed-forward neural networks, to interpret user intent from various sensor inputs (e.g., EMG, inertial measurement units, vision) and adapt to diverse environments and activities. This involves creating lightweight, integrated designs that accurately mimic natural limb kinematics and dynamics, incorporating haptic feedback and synthetic reflexes to enhance dexterity and safety. These advancements hold significant promise for improving prosthetic usability and adoption rates, leading to greater independence and mobility for amputees.