Virtual cycling platforms such as Zwift have become widely used for indoor training and competition but remain primarily optimized for traditional leg-powered bicycles. As a result, handcyclists face a significant disadvantage, since upper-body power output is inherently lower than that generated by the legs—leading to an unbalanced, often discouraging experience. This study presents the development and validation of a power correction model designed to bridge this performance gap and promote inclusivity in virtual cycling environments. A custom-designed handbike was created to produce a digital twin and was physically modified for improved comfort and stability. The setup included a crankset-driven handcycle connected to a CompuTrainer, with an Arduino Due-based interface programmed to acquire and adjust power signals in real time before transmitting them to Zwift.