TrueMotion is a non-invasive HD-sEMG + AI control system designed to decode fine motor intent for prosthetics, exoskeletons, and mobility-assist devices. Built in 8 hours for the Metropolitan Engineering Competition (Bioengineering Stream), the project earned 2nd place, showcasing both a robust AI architecture and a functional physical prototype. Alongside the system schematics, CNN-LSTM model, and full CAD design, we also built a working prosthetic hand prototype to demonstrate baseline movement capabilities. Using an ESP8266, MG90S servos, high-strength string, and elastic harvested from COVID mask straps for natural extension, the prototype successfully performed combinational grip patterns such as pinch, power grasp, and partial finger flexion. This validated the tendon-driven mechanical design and showed how the AI intent decoder could eventually drive full finger-level control.