In this study, a complete artificial arm controlling system was implemented using the electromyogram (EMG) signal. First, arm EMG signals were acquired from the MYO armband, and then the features of certain arm movements were extracted by applying the signal processing. In addition, the present study used fuzzy control in the artificial arm controlling system with EMG signals and designed a CMOS fuzzy chip for pattern recognition and controlling the artificial arm. The test scenario included an MYO armband transferring the actual movements of the human arm to the microcontroller, the signal issue to the fuzzy chip that generates the controlling signals to the artificial arm to perform the movement. Based on the comparison between this work and the previous related work, the difference between the two methods was the use of the fuzzy controlling circuit that causes the additional softness of the movements of the artificial arm in our proposed method and the designing of a CMOS chip instead of a computer causing the system to have low power consumption and mobility. This movement, which was created by the fuzzy controller, was quite similar to the real movement of the hand.