In response to the metaverse's expansion and the progress in VR technology, traditional VR controllers, designed with able-bodied users in mind, fall short for forearm amputees. To address this, our study introduces a VR controller designed from the ground up for forearm amputees, integrating both technological innovations and user experience insights. Through semi-structured interviews and the KANO model, we identified the unique needs of forearm amputees for VR interactions. Our solution is a VR control system based on surface electromyography (sEMG) signals. Utilizing the muscle synergy theory and the nonnegative matrix factorization (NMF) method, we extracted signals that predict hand movements, translating them into VR interactions. We also explore application concepts for “MetaArm,” aiming to enhance the device's usability and integration into various VR settings. This approach not only fosters inclusivity within the VR landscape but also demonstrates the potential of tailored technological adaptations to enrich the VR experience for individuals with diverse needs, ensuring everyone can fully engage with the virtual world.