Removal of Physiological Artifacts from Electroencephalogram Signals: A Review and Case Study

Abstract

The non-invasive nature of electroencephalogram (EEG) has made it an extensively used method to understand the working of the human brain. Due to the high sensitivity of EEG, it is prone to have extrinsic and intrinsic artifacts. The noisy EEG signals can cause difficulty in the analysis of the brain signals and may lead to a false interpretation of the brain activities. Over the past few decades, several methods have been introduced to remove these artifacts. In this paper, we will discuss different types of extrinsic and intrinsic artifacts followed by methods to remove these artifacts. A comparison of these artifact removal techniques is provided which features the usefulness of each method under different conditions. Automatic artifact removal techniques may be implemented on resting-state EEG but for event-based EEG data, the algorithm might confuse the EEG events with artifacts and remove useful data. In this paper, a case study is presented with event-based EEG recording, in which artifacts are removed. In the end, the authors recommend some artifact removal techniques depending upon the type of artifacts in the EEG data.