This paper describes a quasi-passive transradial prosthesis designed to restore drumstick grip control for amputee drummers. A compact motor with low rotor resistance driven by Electromyography (EMG) is implemented in the prosthesis to support real-time drum performances. A variety of grip profiles are achieved by adjusting the stiffness and damping of an impedance controller based on machine learning predictions from EMG data. In addition to the prosthetic design, the paper presents a dynamic model that simulates the drumstick trajectories and estimates the control gains for various natural bouncing patterns. We evaluate the effectiveness of the design through human experiments under real-time performing scenarios for two common drumming grip techniques. The results demonstrate that the prosthetic model can support similar bouncing patterns to the drummer’s healthy hand for single, double, and triple-stroke rolling techniques. The results also show that the system supports usable real-time periodic grip change from single to double-stroke, successfully simulating the common paradiddle drumming technique.