Magnetomyography (MMG) is an informative bio-signal that has received considerable attention in recent years. This paper proposes a method to convert noisy MMG to clean electromyography (EMG) that also stems from muscle activities. The conversion is done by using a recently proposed electrical Rotating Neuron Reservoir (eRNR) model with high efficiency and strong system approximation ability. After training, the model can successfully map the MMG signal to EMG with acceptable normalised root mean square error (0.3894), offering a new pathway for extracting desirable information from the noisy bio-signal.