Fast fourier analysis and EEG classification brainwave controlled wheelchair

Abstract

In this paper, a Fast Fourier Analysis (FFA) with electroencephalogram (EEG) classification based brainwave controlled wheelchair is constructed. This wheelchair is directly controlled by the brain. Thus, it does not require physical feedback from the user. This project is aimed to improve the mind power. It is known as the focusing strength of the brain. By increasing the usage and focusing strength of the brain, it will reduce the risk of brain's degeneration. The method employed in this project is the Brain-Computer Interface (BCI). This method allows the brain to directly communicate with the electrical wheelchair. The recording of the brain's response is then implemented through EEG. This EEG signal is known as brainwaves signal. For EEG signal processing, the signal processing method is known as Fast-Fourier Transform Analysis and EEG Classification (FFTA & EEGC). This processing method generates the mental command of the user. Then, output electrical signal is generated according to the mental command. This electrical signal is sent wirelessly to the microcontroller of the electrical wheelchair. Through this, the electrical wheelchair performs the desired movement based on user's directional thought. In additional, the strength of the brain signal is also recorded for further analysis of user's mind power.