To address the lack of effective ergonomic evaluation methods for HOTAS (Hands-On Throttle And Stick) control sticks in dynamic operation scenarios, this study proposes a virtual hand motion data acquisition system based on Unreal Engine 5, combined with Leap Motion tracking technology. This system captures and records hand movements and interaction processes in real time, providing key quantitative indicators such as movement trajectories, operation durations, and key positioning deviations. Through four-stage HOTAS task experiments, the efficiency and accuracy differences of various operation types are quantitatively analyzed to provide data-driven support for the ergonomic optimization of HOTAS control rods. The experimental results verify the effectiveness of the system for dynamic human factors evaluation, and it is expected to serve as a preliminary virtual evaluation tool for the ergonomic optimization of HOTAS.