Electroencephalography (EEG) is a technique commonly used in medical and research fields to record the electrical activities of the brain. The EEG signals are recorded from the surface of the scalp using a different number of metallic electrodes. The locations of these electrodes on the scalp are specified according to the 10-20 international system. The EEG signals are within the range of 0.5-50μV, and the raw signals are originated from different areas of the brain. Measuring the EEG signals is usually difficult due to small signal magnitude of the EEG signals and large DC offset voltage incorporated with the measuring process. The DC-offset in EEG signal is a result of many factors, like electrode-skin interface, amplifier input bias current mismatch, input impedance, amplifier offset voltage, and voltage drift with temperature and aging. The amplifier input bias current mismatch degrade the Common Mode Rejection Ratio (CMRR) of the amplifier, and create more offset voltage at the input terminals of the amplifier. The higher input impedance of the amplifier will lead to lower current being drawn, and hence the EEG signal will be more immune from picking up noise (like motion artifacts, heart beats eye motion, 50Hz electrical lines, etc.). The EEG signal is amplified in multistage amplifier and digitized using 24-bit analog to digital convertor (ADC). The DC-offset voltage was treated using auto-zeroing technique, along with the use of high precision electronic components. The system was designed so as the amplification is performed mainly in two stages; the first stage is a differential amplifier with ultralow offset, drift, and bias current specifications, the second stage with higher gain and auto-zeroing technique is performed to cancel the total offset voltage that was generated and amplified by the two stages. RC low pass filter with cutoff frequency at 35Hz is used too, and finally the signal is digitized using 24-bit ADC. The theoretical design was first simulated using (TINA Design Suite) software and (NI Multisim 10) software, then the PCB's were designed using Eagle software, and implemented experimentally. EEG signals were acquired and recorded for different people and it seems satisfactory for the diagnosis by doctors.