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This work was concerned on development of the EEG acquisition and EEG signal processing by adding active electrodes and implementing multithread techniques. By using active electrodes, mounting them on the scalp surface would be easier to capture low signals of less than 1µV. The active electrodes were used to reduce noise when transfer signals from the electrode to the acquisition systems which equipped 20 gain. The verification was performed by comparing the active and passive electrodes using NETECH MiniSIM EEG Simulator 330. The advantage of this research was to reduce time delay for EEG signal computation on 32 channels. The acquisition system was based on Raspberry Pi and ADS1299 with multithread signal treatment. Signal filtering was performed into different threads and put all the EEG features into the database. A PC was used to process signal calculation such as processing FFT, signal feature extractions, and signal analysis. These calculations were divided into several functionally independent computations. The signals of each channel were calculated into different threads. The results of this work showed the effectiveness of the multithreaded method for processing large amounts of data (32 channels of 24 bits EEG signal) with low noise levels on the active electrodes.

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