Additive manufacturing used with custom electromyographic sensors has been demonstrated for neuroprosthetic limb manufacturing and is now translating to the clinical environment. These manufacturing methods have dramatically reduced device weight while increasing the capability for multi-finger dexterity. Using wearable electromyography sensors standalone from the prosthetic limb, a new virtual training method has been designed and tested to improve human–machine interaction. This type of training leverages real-time visual feedback to user inputs, supporting improved timing and magnitudes of muscle contractions. The combination of these technologies may provide a stronger affinity between the pediatric patient group and the device.