In this study, the relationship between the electromyographic (EMG) and neural signals (ENG) recorded during hand control is investigated. EMG and ENG signals are both recorded from an amputee during the ENG control of a hand prosthesis. The EMG signal was processed with standard techniques to compute the envelope. For the neural signal, the processing involved the evaluation of the energy of the recordings with a moving average and the best combination of window width and multiplier for the standard deviation was searched for. Hence, a new curve for the neural signal was generated, gathering information about amplitude and occurrence of action potentials during the motion task. Its correlation with the EMG envelope was studied by means of a parameter purposely conceived, which accounts for the ratio between the areas under the two curves. The proposed approach has been applied to little finger flexion and open hand tasks. Ten movements for each task have been processed for the aim of this study and a comparative analysis with the Pearson coefficient has been carried out.