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Electroencephalography (EEG) is a standard method in which electrical signals of cerebral activities are collected using electrodes set along the scalp. It is a non-invasive technique used for clinical applications. The common problem with EEG data is that it is susceptible to the imitation of the distinct biological or environmental noise interferences well known as artefacts. Researchers have proposed various methods to eliminate different types of artefacts from the contaminated EEG signal, yet nothing stands standard for endorsement of recorded EEG signals in clinical usage. Consequently, exploration of artefacts removal research remains engaging and challenging even today. In this paper, simulations are performed using a proficient fast independent component analysis (ICA)-based automatic EEG artifact detection based on joint use of spatial and temporal features (ADJUST) method to remove ocular …